WorldWideScience

Sample records for random noise signal

  1. Introduction to Random Signals and Noise

    NARCIS (Netherlands)

    van Etten, Wim

    Random signals and noise are present in many engineering systems and networks. Signal processing techniques allow engineers to distinguish between useful signals in audio, video or communication equipment, and interference, which disturbs the desired signal. With a strong mathematical grounding,

  2. Random signals and noise a mathematical introduction

    CERN Document Server

    Engelberg, Shlomo

    2011-01-01

    Understanding the nature of random signals and noise is critically important for detecting signals and for reducing and minimizing the effects of noise in applications such as communications and control systems. Outlining a variety of techniques and explaining when and how to use them, Random Signals and Noise: A Mathematical Introduction focuses on applications and practical problem solving rather than probability theory.A Firm FoundationBefore launching into the particulars of random signals and noise, the author outlines the elements of probability that are used throughout the book and incl

  3. Calibration of Correlation Radiometers Using Pseudo-Random Noise Signals

    Directory of Open Access Journals (Sweden)

    Sebastián Pantoja

    2009-08-01

    Full Text Available The calibration of correlation radiometers, and particularly aperture synthesis interferometric radiometers, is a critical issue to ensure their performance. Current calibration techniques are based on the measurement of the cross-correlation of receivers’ outputs when injecting noise from a common noise source requiring a very stable distribution network. For large interferometric radiometers this centralized noise injection approach is very complex from the point of view of mass, volume and phase/amplitude equalization. Distributed noise injection techniques have been proposed as a feasible alternative, but are unable to correct for the so-called “baseline errors” associated with the particular pair of receivers forming the baseline. In this work it is proposed the use of centralized Pseudo-Random Noise (PRN signals to calibrate correlation radiometers. PRNs are sequences of symbols with a long repetition period that have a flat spectrum over a bandwidth which is determined by the symbol rate. Since their spectrum resembles that of thermal noise, they can be used to calibrate correlation radiometers. At the same time, since these sequences are deterministic, new calibration schemes can be envisaged, such as the correlation of each receiver’s output with a baseband local replica of the PRN sequence, as well as new distribution schemes of calibration signals. This work analyzes the general requirements and performance of using PRN sequences for the calibration of microwave correlation radiometers, and particularizes the study to a potential implementation in a large aperture synthesis radiometer using an optical distribution network.

  4. Calibration of correlation radiometers using pseudo-random noise signals.

    Science.gov (United States)

    Pérez, Isaac Ramos; Bosch-Lluis, Xavi; Camps, Adriano; Alvarez, Nereida Rodriguez; Hernandez, Juan Fernando Marchán; Domènech, Enric Valencia; Vernich, Carlos; de la Rosa, Sonia; Pantoja, Sebastián

    2009-01-01

    The calibration of correlation radiometers, and particularly aperture synthesis interferometric radiometers, is a critical issue to ensure their performance. Current calibration techniques are based on the measurement of the cross-correlation of receivers' outputs when injecting noise from a common noise source requiring a very stable distribution network. For large interferometric radiometers this centralized noise injection approach is very complex from the point of view of mass, volume and phase/amplitude equalization. Distributed noise injection techniques have been proposed as a feasible alternative, but are unable to correct for the so-called "baseline errors" associated with the particular pair of receivers forming the baseline. In this work it is proposed the use of centralized Pseudo-Random Noise (PRN) signals to calibrate correlation radiometers. PRNs are sequences of symbols with a long repetition period that have a flat spectrum over a bandwidth which is determined by the symbol rate. Since their spectrum resembles that of thermal noise, they can be used to calibrate correlation radiometers. At the same time, since these sequences are deterministic, new calibration schemes can be envisaged, such as the correlation of each receiver's output with a baseband local replica of the PRN sequence, as well as new distribution schemes of calibration signals. This work analyzes the general requirements and performance of using PRN sequences for the calibration of microwave correlation radiometers, and particularizes the study to a potential implementation in a large aperture synthesis radiometer using an optical distribution network.

  5. Large Signal Excitation Measurement Techniques for Random Telegraph Signal Noise in MOSFETs

    NARCIS (Netherlands)

    Hoekstra, E.

    2005-01-01

    This paper introduces large signal excitation measurement techniques to analyze random telegraph signal (RTS) noise originating from oxide-traps in MOSFETs. The paper concentrates on the trap-occupancy, which relates directly to the generated noise. The proposed measurement technique makes

  6. Large Signal Excitation Measurement Techniques for Random Telegraph Signal Noise in MOSFETs

    NARCIS (Netherlands)

    Hoekstra, E.; Kolhatkar, J.S.; van der Wel, A.P.; Salm, Cora; Klumperink, Eric A.M.

    2005-01-01

    This paper introduces large signal excitation measurement techniques to analyze Random Telegraph Signal (RTS) noise originating from oxide-traps in MOSFETs. The paper concentrates on the trap-occupancy, which relates directly to the generated noise. The proposed measurement technique makes

  7. Random noise de-noising and direct wave eliminating based on SVD method for ground penetrating radar signals

    Science.gov (United States)

    Liu, Cai; Song, Chao; Lu, Qi

    2017-09-01

    In this paper, we present a method using singular value decomposition (SVD) which aims at eliminating the random noise and direct wave from ground penetrating radar (GPR) signals. To demonstrate the validity and high efficiency of the SVD method in eliminating random noise, we compare the SVD de-noising method with wavelet threshold de-noising method and bandpass filtering method on both noisy synthetic data and field data. After that, we compare the SVD method with the mean trace deleting in eliminating direct wave on synthetic data and field data. We set general and quantitative criteria on choosing singular values to carry out the random noise de-noising and direct wave eliminating process. We find that by choosing appropriate singular values, SVD method can eliminate the random noise and direct wave in the GPR data validly and efficiently to improve the signal-to-noise ratio (SNR) of the GPR profiles and make effective reflection signals clearer.

  8. Signal preserving and seismic random noise attenuation by Hurst exponent based time-frequency peak filtering

    Science.gov (United States)

    Zhang, Chao; Li, Yue; Lin, Hongbo; Yang, Baojun

    2015-11-01

    Attenuating random noise is of great significance in seismic data processing. In recent years, time-frequency peak filtering (TFPF) has been successfully applied to seismic random noise attenuation field. However, a fixed window length (WL) is used in the conventional TFPF. Since a short WL in the TFPF is used to preserve signals while a long WL can eliminate random noise effectively, signal preserving and noise attenuation cannot be balanced by a fixed WL especially when the signal-to-noise ratio of the noisy seismic record is low. Thus, we need to divide a noisy signal into signal and noise segments before the filtering. Then a short WL is used to the signal segments to preserve signals and a long WL is chosen for noise segments to eliminate random noise. In this paper, we test the smoothness of signals and random noise in time using the Hurst exponent which is a statistic for representing smoothness characteristics of signals. The time-series of signals with higher smoothness which lead to larger Hurst exponent values, however random noise is a random series in time without fixed waveforms and thus its smoothness is low, so the signal and noise segments can be divided by the Hurst exponent values. After the segmentation, we can adopt different filtering WLs in the TFPF for different segments to make a trade-off between signal preserving and random noise attenuation. Synthetic and real data experiments demonstrate that the proposed method can remove random noise from seismic record and preserve reflection events effectively.

  9. Random wavelet transforms, algebraic geometric coding, and their applications in signal compression and de-noising

    Energy Technology Data Exchange (ETDEWEB)

    Bieleck, T.; Song, L.M.; Yau, S.S.T. [Univ. of Illinois, Chicago, IL (United States); Kwong, M.K. [Argonne National Lab., IL (United States). Mathematics and Computer Science Div.

    1995-07-01

    The concepts of random wavelet transforms and discrete random wavelet transforms are introduced. It is shown that these transforms can lead to simultaneous compression and de-noising of signals that have been corrupted with fractional noises. Potential applications of algebraic geometric coding theory to encode the ensuing data are also discussed.

  10. Detection of random signals in dependent Gaussian noise

    CERN Document Server

    Gualtierotti, Antonio F

    2015-01-01

    The book presents the necessary mathematical basis to obtain and rigorously use likelihoods for detection problems with Gaussian noise. To facilitate comprehension the text is divided into three broad areas –  reproducing kernel Hilbert spaces, Cramér-Hida representations and stochastic calculus – for which a somewhat different approach was used than in their usual stand-alone context. One main applicable result of the book involves arriving at a general solution to the canonical detection problem for active sonar in a reverberation-limited environment. Nonetheless, the general problems dealt with in the text also provide a useful framework for discussing other current research areas, such as wavelet decompositions, neural networks, and higher order spectral analysis. The structure of the book, with the exposition presenting as many details as necessary, was chosen to serve both those readers who are chiefly interested in the results and those who want to learn the material from scratch. Hence, the text...

  11. Novel evidence that attributing affectively salient signal to random noise is associated with psychosis.

    Science.gov (United States)

    Catalan, Ana; Simons, Claudia J P; Bustamante, Sonia; Drukker, Marjan; Madrazo, Aranzazu; de Artaza, Maider Gonzalez; Gorostiza, Iñigo; van Os, Jim; Gonzalez-Torres, Miguel A

    2014-01-01

    We wished to replicate evidence that an experimental paradigm of speech illusions is associated with psychotic experiences. Fifty-four patients with a first episode of psychosis (FEP) and 150 healthy subjects were examined in an experimental paradigm assessing the presence of speech illusion in neutral white noise. Socio-demographic, cognitive function and family history data were collected. The Positive and Negative Syndrome Scale (PANSS) was administered in the patient group and the Structured Interview for Schizotypy-Revised (SIS-R), and the Community Assessment of Psychic Experiences (CAPE) in the control group. Patients had a much higher rate of speech illusions (33.3% versus 8.7%, ORadjusted: 5.1, 95% CI: 2.3-11.5), which was only partly explained by differences in IQ (ORadjusted: 3.4, 95% CI: 1.4-8.3). Differences were particularly marked for signals in random noise that were perceived as affectively salient (ORadjusted: 9.7, 95% CI: 1.8-53.9). Speech illusion tended to be associated with positive symptoms in patients (ORadjusted: 3.3, 95% CI: 0.9-11.6), particularly affectively salient illusions (ORadjusted: 8.3, 95% CI: 0.7-100.3). In controls, speech illusions were not associated with positive schizotypy (ORadjusted: 1.1, 95% CI: 0.3-3.4) or self-reported psychotic experiences (ORadjusted: 1.4, 95% CI: 0.4-4.6). Experimental paradigms indexing the tendency to detect affectively salient signals in noise may be used to identify liability to psychosis.

  12. Detection of signals in noise

    CERN Document Server

    Whalen, Anthony D; Declaris, Nicholas

    1971-01-01

    Detection of Signals in Noise serves as an introduction to the principles and applications of the statistical theory of signal detection. The book discusses probability and random processes; narrowband signals, their complex representation, and their properties described with the aid of the Hilbert transform; and Gaussian-derived processes. The text also describes the application of hypothesis testing for the detection of signals and the fundamentals required for statistical detection of signals in noise. Problem exercises, references, and a supplementary bibliography are included after each c

  13. Effect of signal-temporal uncertainty in children and adults: tone detection in noise or a random-frequency masker.

    Science.gov (United States)

    Bonino, Angela Yarnell; Leibold, Lori J; Buss, Emily

    2013-12-01

    A cue indicating when in time to listen can improve adults' tone detection thresholds, particularly for conditions that produce substantial informational masking. The purpose of this study was to determine if 5- to 13-yr-old children likewise benefit from a light cue indicating when in time to listen for a masked pure-tone signal. Each listener was tested in one of two continuous maskers: Broadband noise (low informational masking) or a random-frequency, two-tone masker (high informational masking). Using a single-interval method of constant stimuli, detection thresholds were measured for two temporal conditions: (1) Temporally-defined, with the listening interval defined by a light cue, and (2) temporally-uncertain, with no light cue. Thresholds estimated from psychometric functions fitted to the data indicated that children and adults benefited to the same degree from the visual cue. Across listeners, the average benefit of a defined listening interval was 1.8 dB in the broadband noise and 8.6 dB in the random-frequency, two-tone masker. Thus, the benefit of knowing when in time to listen was more robust for conditions believed to be dominated by informational masking. An unexpected finding of this study was that children's thresholds were comparable to adults' in the random-frequency, two-tone masker.

  14. Single vacancy defect spectroscopy on HfO2 using random telegraph noise signals from scanning tunneling microscopy

    Science.gov (United States)

    Thamankar, R.; Raghavan, N.; Molina, J.; Puglisi, F. M.; O'Shea, S. J.; Shubhakar, K.; Larcher, L.; Pavan, P.; Padovani, A.; Pey, K. L.

    2016-02-01

    Random telegraph noise (RTN) measurements are typically carried out at the device level using standard probe station based electrical characterization setup, where the measured current represents a cumulative effect of the simultaneous response of electron capture/emission events at multiple oxygen vacancy defect (trap) sites. To better characterize the individual defects in the high-κ dielectric thin film, we propose and demonstrate here the measurement and analysis of RTN at the nanoscale using a room temperature scanning tunneling microscope setup, with an effective area of interaction of the probe tip that is as small as 10 nm in diameter. Two-level and multi-level RTN signals due to single and multiple defect locations (possibly dispersed in space and energy) are observed on 4 nm HfO2 thin films deposited on n-Si (100) substrate. The RTN signals are statistically analyzed using the Factorial Hidden Markov Model technique to decode the noise contribution of more than one defect (if any) and estimate the statistical parameters of each RTN signal (i.e., amplitude of fluctuation, capture and emission time constants). Observation of RTN at the nanoscale presents a new opportunity for studies on defect chemistry, single-defect kinetics and their stochastics in thin film dielectric materials. This method allows us to characterize the fast traps with time constants ranging in the millisecond to tens of seconds range.

  15. Communicating the Signal of Climate Change in The Presence of Non-Random Noise

    Science.gov (United States)

    Mann, M. E.

    2015-12-01

    The late Stephen Schneider spoke eloquently of the double ethical bind that we face: we must strive to communicate effectively but honestly. This is no simple task given the considerable "noise" generated in our public discourse by vested interests instead working to misinform the public. To do so, we must convey what is known in plainspoken jargon-free language, while acknowledging the real uncertainties that exist. Further, we must explain the implications of those uncertainties, which in many cases imply the possibility of greater, not lesser, risk. Finally, we must not be averse to discussing the policy implications of the science, lest we fail to provide our audience with critical information that can help them make informed choices about their own actions as citizens. I will use examples from my current collaboration with Washington Post editorial cartoonist Tom Toles.

  16. The Signal Importance of Noise

    Science.gov (United States)

    Macy, Michael; Tsvetkova, Milena

    2015-01-01

    Noise is widely regarded as a residual category--the unexplained variance in a linear model or the random disturbance of a predictable pattern. Accordingly, formal models often impose the simplifying assumption that the world is noise-free and social dynamics are deterministic. Where noise is assigned causal importance, it is often assumed to be a…

  17. Critical ratios in harbor porpoises (Phocoena phocoena) for tonal signals between 0.315 and 150 kHz in random Gaussian white noise.

    Science.gov (United States)

    Kastelein, Ronald A; Wensveen, Paul J; Hoek, Lean; Au, Whitlow W L; Terhune, John M; de Jong, Christ A F

    2009-09-01

    A psychoacoustic behavioral technique was used to determine the critical ratios (CRs) of two harbor porpoises for tonal signals with frequencies between 0.315 and 150 kHz, in random Gaussian white noise. The masked 50% detection hearing thresholds were measured using a "go/no-go" response paradigm and an up-down staircase psychometric method. CRs were determined at one masking noise level for each test frequency and were similar in both animals. For signals between 0.315 and 4 kHz, the CRs were relatively constant at around 18 dB. Between 4 and 150 kHz the CR increased gradually from 18 to 39 dB ( approximately 3.3 dB/octave). Generally harbor porpoises can detect tonal signals in Gaussian white noise slightly better than most odontocetes tested so far. By combining the mean CRs found in the present study with the spectrum level of the background noise levels at sea, the basic audiogram, and the directivity index, the detection threshold levels of harbor porpoises for tonal signals in various sea states can be calculated.

  18. Estimates of Small Signal/Noise Ratios

    Science.gov (United States)

    Howard, L. D.

    1985-01-01

    Signal/Noise Ratio Meter measures ratio of signal power to noise power in input that contains both signal and noise. Signal and noise first filtered and normalized in analog circuitry, then digitized and sampled. Performance of SNR meter determined by statistical algorithm chosen for analysis of samples.

  19. Pseudo random signal processing theory and application

    CERN Document Server

    Zepernick, Hans-Jurgen

    2013-01-01

    In recent years, pseudo random signal processing has proven to be a critical enabler of modern communication, information, security and measurement systems. The signal's pseudo random, noise-like properties make it vitally important as a tool for protecting against interference, alleviating multipath propagation and allowing the potential of sharing bandwidth with other users. Taking a practical approach to the topic, this text provides a comprehensive and systematic guide to understanding and using pseudo random signals. Covering theoretical principles, design methodologies and applications

  20. Adaptive Noise Suppression Using Digital Signal Processing

    Science.gov (United States)

    Kozel, David; Nelson, Richard

    1996-01-01

    A signal to noise ratio dependent adaptive spectral subtraction algorithm is developed to eliminate noise from noise corrupted speech signals. The algorithm determines the signal to noise ratio and adjusts the spectral subtraction proportion appropriately. After spectra subtraction low amplitude signals are squelched. A single microphone is used to obtain both eh noise corrupted speech and the average noise estimate. This is done by determining if the frame of data being sampled is a voiced or unvoiced frame. During unvoice frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Applications include the emergency egress vehicle and the crawler transporter.

  1. Modeling Random Telegraph Noise Under Switched Bias Conditions Using Cyclostationary RTS Noise

    NARCIS (Netherlands)

    van der Wel, A.P.; Klumperink, Eric A.M.; Vandamme, L.K.J.; Nauta, Bram

    In this paper, we present measurements and simulation of random telegraph signal (RTS) noise in n-channel MOSFETs under periodic large signal gate-source excitation (switched bias conditions). This is particularly relevant to analog CMOS circuit design where large signal swings occur and where LF

  2. Signal-to-noise ratio determination circuit

    Science.gov (United States)

    Deerkoski, L. F. (Inventor)

    1973-01-01

    A signal-to-noise ratio (SNR) determination of an input is described, having signal components within a given frequency range and noise components, without actual measurement of the noise components. Bandpass limiter having a constant signal plus noise output level is connected to the output of the first filter, the signal-to-noise ratio of the input to the bandpass limiter being linearly related to the dbm level of signal components at the output. Calibration is connected to the bandpass limiter and is responsive to the signal components at the output to derive the SNR of the input to the determination circuit. The SNR determination circuit is disclosed for use in a diversity receiver having a plurality of input channels.

  3. Signal processing in noise waveform radar

    CERN Document Server

    Kulpa, Krzysztof

    2013-01-01

    This book is devoted to the emerging technology of noise waveform radar and its signal processing aspects. It is a new kind of radar, which use noise-like waveform to illuminate the target. The book includes an introduction to basic radar theory, starting from classical pulse radar, signal compression, and wave radar. The book then discusses the properties, difficulties and potential of noise radar systems, primarily for low-power and short-range civil applications. The contribution of modern signal processing techniques to making noise radar practical are emphasized, and application examples

  4. Noise Cancellation in ECG Signals using Computationally

    OpenAIRE

    D.V. Rama Koti Reddy; Mohammad Zia Ur Rahman; Rafi Ahamed Shaik

    2009-01-01

    Several signed LMS based adaptive filters, which are computationally superior having multiplier free weight update loops are proposed for noise cancellation in the ECG signal. The adaptive filters essentially minimizes the mean-squared error between a primary input, which is the noisy ECG, and a reference input, which is either noise that is correlated in some way with the noise in the primary input or a signal that is correlated only with ECG in the primary input. Different filter structures...

  5. Advanced digital signal processing and noise reduction

    CERN Document Server

    Vaseghi, Saeed V

    2008-01-01

    Digital signal processing plays a central role in the development of modern communication and information processing systems. The theory and application of signal processing is concerned with the identification, modelling and utilisation of patterns and structures in a signal process. The observation signals are often distorted, incomplete and noisy and therefore noise reduction, the removal of channel distortion, and replacement of lost samples are important parts of a signal processing system. The fourth edition of Advanced Digital Signal Processing and Noise Reduction updates an

  6. Orbiter CCTV video signal noise analysis

    Science.gov (United States)

    Lawton, R. M.; Blanke, L. R.; Pannett, R. F.

    1977-01-01

    The amount of steady state and transient noise which will couple to orbiter CCTV video signal wiring is predicted. The primary emphasis is on the interim system, however, some predictions are made concerning the operational system wiring in the cabin area. Noise sources considered are RF fields from on board transmitters, precipitation static, induced lightning currents, and induced noise from adjacent wiring. The most significant source is noise coupled to video circuits from associated circuits in common connectors. Video signal crosstalk is the primary cause of steady state interference, and mechanically switched control functions cause the largest induced transients.

  7. Voltage fluctuations in neurons: signal or noise?

    DEFF Research Database (Denmark)

    Yarom, Yosef; Hounsgaard, Jorn

    2011-01-01

    Noise and variability are fundamental companions to ion channels and synapses and thus inescapable elements of brain function. The overriding unresolved issue is to what extent noise distorts and limits signaling on one hand and at the same time constitutes a crucial and fundamental enrichment th...

  8. Seismic random noise attenuation using modified wavelet thresholding

    Directory of Open Access Journals (Sweden)

    Qi-sheng Zhang

    2017-01-01

    Full Text Available In seismic exploration, random noise deteriorates the quality of acquired data. This study analyzed existing denoising methods used in seismic exploration from the perspective of random noise. Wavelet thresholding offers a new approach to reducing random noise in simulation results, synthetic data, and real data. A modified wavelet threshold function was developed by considering the merits and demerits of conventional soft and hard thresholding schemes. A MATLAB (matrix laboratory simulation model was used to compare the signal-to-noise ratios (SNRs and mean square errors (MSEs of the soft, hard, and modified threshold functions. The results demonstrated that the modified threshold function can avoid the pseudo-Gibbs phenomenon and produce a higher SNR than the soft and hard threshold functions. A seismic convolution model was built using seismic wavelets to verify the effectiveness of different denoising methods. The model was used to demonstrate that the modified thresholding scheme can effectively reduce random noise in seismic data and retain the desired signal. The application of the proposed tool to a real raw seismogram recorded during a land seismic exploration experiment located in north China clearly demonstrated its efficiency for random noise attenuation.

  9. ”Sound [signal] noise

    DEFF Research Database (Denmark)

    Bjørnsten, Thomas

    2012-01-01

    The article discusses the intricate relationship between sound and signification through notions of noise. The emergence of new fields of sonic artistic practices has generated several questions of how to approach sound as aesthetic form and material. During the past decade an increased attention...... has been paid to, for instance, a category such as ‘sound art’ together with an equally strengthened interest in phenomena and concepts that fall outside the accepted aesthetic procedures and constructions of what we traditionally would term as musical sound – a recurring example being ‘noise’....

  10. Signal detection amid noise with known statistics

    Science.gov (United States)

    Zepka, A. F.; Cordes, J. M.; Wasserman, I.

    1994-01-01

    Conventional methods of signal detection are based on the comparison of a local signal-to-noise ratio S/N to some threshold value. We present a new method that compares instead the histogram of the data with the one expected for background noise alone. Signals are detected from discrepancies between the two. We expect it to be applicable in the detection of signals from any data whose background statistics is known. To illustrate the method, we apply it to the case of photon-limited imaging data where the underlying background is Poissonian. Numerical simulations are used to check the efficiency of our method, finding that for signals with low S/N (less than 5), it detects signals with a higher degree of reliability than the conventional method.

  11. Random noise attenuation using an improved anisotropic total variation regularization

    Science.gov (United States)

    Gemechu, Diriba; Yuan, Huan; Ma, Jianwei

    2017-09-01

    In seismic data processing, attenuation of random noise from the observed data is the basic step which improves the signal-to-noise ratio (SNR) of seismic data. In this paper, we proposed an anisotropic total bounded variation regularization approach to attenuate noise. An improved constraint convex optimization model is formulated for this approach and then the split Bregman algorithm is used to solve the optimization model. Generalized cross validation (GCV) technique is used to estimate the regularization parameter. Synthetic and real seismic data are considered to show the out performance of the proposed method in terms of event-preserving denoising, in comparison with FX deconvolution, shearlet hard thresholding, and anisotropic total variation methods. The numerical results indicate that the proposed method effectively attenuates random noise by preserving the structure and important features of seismic data.

  12. Detection of signals in noise

    CERN Document Server

    McDonough, Robert N

    1995-01-01

    The Second Edition is an updated revision to the authors highly successful and widely used introduction to the principles and application of the statistical theory of signal detection. This book emphasizes those theories that have been found to be particularly useful in practice including principles applied to detection problems encountered in digital communications, radar, and sonar.Detection processing based upon the fast Fourier transform

  13. Nonlinear biochemical signal processing via noise propagation.

    Science.gov (United States)

    Kim, Kyung Hyuk; Qian, Hong; Sauro, Herbert M

    2013-10-14

    Single-cell studies often show significant phenotypic variability due to the stochastic nature of intra-cellular biochemical reactions. When the numbers of molecules, e.g., transcription factors and regulatory enzymes, are in low abundance, fluctuations in biochemical activities become significant and such "noise" can propagate through regulatory cascades in terms of biochemical reaction networks. Here we develop an intuitive, yet fully quantitative method for analyzing how noise affects cellular phenotypes based on identifying a system's nonlinearities and noise propagations. We observe that such noise can simultaneously enhance sensitivities in one behavioral region while reducing sensitivities in another. Employing this novel phenomenon we designed three biochemical signal processing modules: (a) A gene regulatory network that acts as a concentration detector with both enhanced amplitude and sensitivity. (b) A non-cooperative positive feedback system, with a graded dose-response in the deterministic case, that serves as a bistable switch due to noise-induced ultra-sensitivity. (c) A noise-induced linear amplifier for gene regulation that requires no feedback. The methods developed in the present work allow one to understand and engineer nonlinear biochemical signal processors based on fluctuation-induced phenotypes.

  14. Signal processing and electronic noise in LZ

    Science.gov (United States)

    Khaitan, D.

    2016-03-01

    The electronics of the LUX-ZEPLIN (LZ) experiment, the 10-tonne dark matter detector to be installed at the Sanford Underground Research Facility (SURF), consists of low-noise dual-gain amplifiers and a 100-MHz, 14-bit data acquisition system for the TPC PMTs. Pre-prototypes of the analog amplifiers and the 32-channel digitizers were tested extensively with simulated pulses that are similar to the prompt scintillation light and the electroluminescence signals expected in LZ. These studies are used to characterize the noise and to measure the linearity of the system. By increasing the amplitude of the test signals, the effect of saturating the amplifier and the digitizers was studied. The RMS ADC noise of the digitizer channels was measured to be 1.19± 0.01 ADCC. When a high-energy channel of the amplifier is connected to the digitizer, the measured noise remained virtually unchanged, while the noise added by a low-energy channel was estimated to be 0.38 ± 0.02 ADCC (46 ± 2 μV). A test facility is under construction to study saturation, mitigate noise and measure the performance of the LZ electronics and data acquisition chain.

  15. Random Noise Monopulse Radar System for Covert Tracking of Targets

    Science.gov (United States)

    Narayanan, Ram M.

    2002-07-01

    The University of Nebraska is currently developing a unique monopulse radar concept based on the use of random noise signal for covert tracking applications. This project is funded by the Missile Defense Agency (MDA). The advantage of this system over conventional frequency-modulated continuous wave (FMCW) or short pulse systems is its covertness resulting from the random waveform's immunity from interception and jamming. The system integrates a novel heterodyne correlation receiver with conventional monopulse architecture. Based on the previous work such as random noise interferometry, a series of theoretical analysis and simulations were conducted to examine the potential performance of this monopulse system. Furthermore, a prototype system is under development to exploit practical design aspects of phase comparison angle measurement. It is revealed that random noise monopulse radar can provide the same function as traditional monopulse radar, i.e., implement range and angular estimation and tracking in real time. The bandwidth of random noise signal can be optimized to achieve the best range resolution as well as the angular accuracy.

  16. IKONOS Signal-to-Noise Ratio Estimation

    Science.gov (United States)

    Zanoni, Vicki; Ryan, Robert; Holekamp, Kara; Pagnutti, Mary

    2002-01-01

    This viewgraph presentation focuses on the differences in Signal-to-Noise Ratio (SNR) between IKONOS imagery with and without Modulation Transfer Function Correction (MTFC). The researchers used a simulated scene to evaluate the effects of MTFC on SNR. They also used four very uniform IKONOS scenes, two of Antarctica, one of Ivanpah, CA, and one of Mali to estimate SNR.

  17. A review and tutorial discussion of noise and signal-to-noise ratios in analytical spectrometry—III. Multiplicative noises

    NARCIS (Netherlands)

    Alkemade, C.T.J.; Snelleman, W.; Boutilier, G.D.; Winefordner, J.D.

    1980-01-01

    In this review, signal-to-noise ratios are discussed in a tutorial fashion for the case of multiplicative noise. Multiplicative noise is introduced simultaneously with the analyte signal and is therefore much more difficult to reduce than additive noise. The sources of noise, the mathematical

  18. Application of variational mode decomposition to seismic random noise reduction

    Science.gov (United States)

    Liu, Wei; Cao, Siyuan; Wang, Zhiming

    2017-08-01

    We have proposed a new denoising method for the simultaneous noise reduction and preservation of seismic signals based on variational mode decomposition (VMD). VMD is a recently developed adaptive signal decomposition method and an advance in non-stationary signal analysis. It solves the mode-mixing and non-optimal reconstruction performance problems of empirical mode decomposition that have existed for a long time. By using VMD, a multi-component signal can be non-recursively decomposed into a series of quasi-orthogonal intrinsic mode functions (IMFs), each of which has a relatively local frequency range. Meanwhile, the signal will focus on a smaller number of obtained IMFs after decomposition, and thus the denoised result is able to be obtained by reconstructing these signal-dominant IMFs. Synthetic examples are given to demonstrate the effectiveness of the proposed approach and comparison is made with the complete ensemble empirical mode decomposition, which demonstrates that the VMD algorithm has lower computational cost and better random noise elimination performance. The application of on field seismic data further illustrates the superior performance of our method in both random noise attenuation and the recovery of seismic events.

  19. Optical signal to noise ratio improvement through unbalanced noise beating in phase-sensitive parametric amplifiers

    OpenAIRE

    Malik, R; Kumpera, A.; Olsson, S. L. I.; Andrekson, P.A.; Karlsson, M

    2014-01-01

    We investigate the beating of signal and idler waves, which have imbalanced signal to noise ratios, in a phase-sensitive parametric amplifier. Imbalanced signal to noise ratios are achieved in two ways; first by imbalanced noise loading; second by varying idler to signal input power ratio. In the case of imbalanced noise loading the phase-sensitive amplifier improved the signal to noise ratio from 3 to 6 dB, and in the case of varying idler to signal input power ratio, the signal to noise rat...

  20. M-ary suprathreshold stochastic resonance in multilevel threshold systems with signal-dependent noise

    Science.gov (United States)

    Cheng, Chaojun; Zhou, Bingchang; Gao, Xiao; McDonnell, Mark D.

    2017-08-01

    We investigate multilevel threshold systems with signal-dependent noise that transmit a common random input signal. We demonstrate the occurrence of M-ary suprathreshold stochastic resonance caused by the signal-dependent noise, and quantify the information enhancement that results relative to the absence of noise. We also find that in the case of M-ary threshold systems, the values of mutual information and signal-to-quantization-noise ratio are larger than the corresponding values in the case of binary threshold systems. These results are potentially useful for understanding the encoding mechanism of inner-ear hair cells and other biological sensory systems.

  1. Seismic signal and noise on Europa

    Science.gov (United States)

    Panning, Mark; Stähler, Simon; Bills, Bruce; Castillo Castellanos, Jorge; Huang, Hsin-Hua; Husker, Allen; Kedar, Sharon; Lorenz, Ralph; Pike, William T.; Schmerr, Nicholas; Tsai, Victor; Vance, Steven

    2017-10-01

    Seismology is one of our best tools for detailing interior structure of planetary bodies, and a seismometer is included in the baseline and threshold mission design for the upcoming Europa Lander mission. Guiding mission design and planning for adequate science return, though, requires modeling of both the anticipated signal and noise. Assuming ice seismicity on Europa behaves according to statistical properties observed in Earth catalogs and scaling cumulative seismic moment release to the moon, we can simulate long seismic records and estimate background noise and peak signal amplitudes (Panning et al., 2017). This suggests a sensitive instrument comparable to many broadband terrestrial instruments or the SP instrument from the InSight mission to Mars will be able to record signals, while high frequency geophones are likely inadequate. We extend this analysis to also begin incorporation of spatial and temporal variation due to the tidal cycle, which can help inform landing site selection. We also begin exploration of how chaotic terrane at the bottom of the ice shell and inter-ice heterogeneities (i.e. internal melt structures) may affect anticipated seismic observations using 2D numerical seismic simulations.M. P. Panning, S. C. Stähler, H.-H. Huang, S. D. Vance, S. Kedar, V. C. Tsai, W. T. Pike, R. D. Lorenz, “Expected seismicity and the seismic noise environment of Europa,” J. Geophys. Res., in revision, 2017.

  2. Frequency-space prediction filtering for acoustic clutter and random noise attenuation in ultrasound imaging

    Science.gov (United States)

    Shin, Junseob; Huang, Lianjie

    2016-04-01

    Frequency-space prediction filtering (FXPF), also known as FX deconvolution, is a technique originally developed for random noise attenuation in seismic imaging. FXPF attempts to reduce random noise in seismic data by modeling only real signals that appear as linear or quasilinear events in the aperture domain. In medical ultrasound imaging, channel radio frequency (RF) signals from the main lobe appear as horizontal events after receive delays are applied while acoustic clutter signals from off-axis scatterers and electronic noise do not. Therefore, FXPF is suitable for preserving only the main-lobe signals and attenuating the unwanted contributions from clutter and random noise in medical ultrasound imaging. We adapt FXPF to ultrasound imaging, and evaluate its performance using simulated data sets from a point target and an anechoic cyst. Our simulation results show that using only 5 iterations of FXPF achieves contrast-to-noise ratio (CNR) improvements of 67 % in a simulated noise-free anechoic cyst and 228 % in a simulated anechoic cyst contaminated with random noise of 15 dB signal-to-noise ratio (SNR). Our findings suggest that ultrasound imaging with FXPF attenuates contributions from both acoustic clutter and random noise and therefore, FXPF has great potential to improve ultrasound image contrast for better visualization of important anatomical structures and detection of diseased conditions.

  3. Cortical signal-in-noise coding varies by noise type, signal-to-noise ratio, age, and hearing status.

    Science.gov (United States)

    Maamor, Nashrah; Billings, Curtis J

    2017-01-01

    The purpose of this study was to determine the effects of noise type, signal-to-noise ratio (SNR), age, and hearing status on cortical auditory evoked potentials (CAEPs) to speech sounds. This helps to explain the hearing-in-noise difficulties often seen in the aging and hearing impaired population. Continuous, modulated, and babble noise types were presented at varying SNRs to 30 individuals divided into three groups according to age and hearing status. Significant main effects of noise type, SNR, and group were found. Interaction effects revealed that the SNR effect varies as a function of noise type and is most systematic for continuous noise. Effects of age and hearing loss were limited to CAEP latency and were differentially modulated by energetic and informational-like masking. It is clear that the spectrotemporal characteristics of signals and noises play an important role in determining the morphology of neural responses. Participant factors such as age and hearing status, also play an important role in determining the brain's response to complex auditory stimuli and contribute to the ability to listen in noise. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  4. Analyses and Measures of GPR Signal with Superimposed Noise

    Science.gov (United States)

    Chicarella, Simone; Ferrara, Vincenzo; D'Atanasio, Paolo; Frezza, Fabrizio; Pajewski, Lara; Pavoncello, Settimio; Prontera, Santo; Tedeschi, Nicola; Zambotti, Alessandro

    2014-05-01

    The influence of EM noises and environmental hard conditions on the GPR surveys has been examined analytically [1]. In the case of pulse radar GPR, many unwanted signals as stationary clutter, non-stationary clutter, random noise, and time jitter, influence the measurement signal. When GPR is motionless, stationary clutter is the most dominant signal component due to the reflections of static objects different from the investigated target, and to the direct antenna coupling. Moving objects like e.g. persons and vehicles, and the swaying of tree crown, produce non-stationary clutter. Device internal noise and narrowband jamming are e.g. two potential sources of random noises. Finally, trigger instabilities generate random jitter. In order to estimate the effective influence of these noise signal components, we organized some experimental setup of measurement. At first, we evaluated for the case of a GPR basic detection, simpler image processing of radargram. In the future, we foresee experimental measurements for detection of the Doppler frequency changes induced by movements of targets (like physiological movements of survivors under debris). We obtain image processing of radargram by using of GSSI SIR® 2000 GPR system together with the UWB UHF GPR-antenna (SUB-ECHO HBD 300, a model manufactured by Radarteam company). Our work includes both characterization of GPR signal without (or almost without) a superimposed noise, and the effect of jamming originated from the coexistence of a different radio signal. For characterizing GPR signal, we organized a measurement setup that includes the following instruments: mod. FSP 30 spectrum analyser by Rohde & Schwarz which operates in the frequency range 9 KHz - 30 GHz, mod. Sucoflex 104 cable by Huber Suhner (10 MHz - 18 GHz), and HL050 antenna by Rohde & Schwarz (bandwidth: from 850 MHz to 26.5 GHz). The next analysis of superimposed jamming will examine two different signal sources: by a cellular phone and by a

  5. Inversion-based data-driven time-space domain random noise attenuation method

    Science.gov (United States)

    Zhao, Yu-Min; Li, Guo-Fa; Wang, Wei; Zhou, Zhen-Xiao; Tang, Bo-Wen; Zhang, Wen-Bo

    2017-12-01

    Conventional time-space domain and frequency-space domain prediction filtering methods assume that seismic data consists of two parts, signal and random noise. That is, the so-called additive noise model. However, when estimating random noise, it is assumed that random noise can be predicted from the seismic data by convolving with a prediction error filter. That is, the source-noise model. Model inconsistencies, before and after denoising, compromise the noise attenuation and signal-preservation performances of prediction filtering methods. Therefore, this study presents an inversion-based time-space domain random noise attenuation method to overcome the model inconsistencies. In this method, a prediction error filter (PEF), is first estimated from seismic data; the filter characterizes the predictability of the seismic data and adaptively describes the seismic data's space structure. After calculating PEF, it can be applied as a regularized constraint in the inversion process for seismic signal from noisy data. Unlike conventional random noise attenuation methods, the proposed method solves a seismic data inversion problem using regularization constraint; this overcomes the model inconsistency of the prediction filtering method. The proposed method was tested on both synthetic and real seismic data, and results from the prediction filtering method and the proposed method are compared. The testing demonstrated that the proposed method suppresses noise effectively and provides better signal-preservation performance.

  6. Estimation of signal-to-noise - A new procedure applied to AVIRIS data

    Science.gov (United States)

    Curran, Paul J.; Dungan, Jennifer L.

    1989-01-01

    To make the best use of narrowband airborne visible/infrared imaging spectrometer (AVIRIS) data, an investigator needs to know the ratio of signal to random variability or noise (signal-to-noise ratio or SNR). The signal is land cover dependent and varies with both wavelength and atmospheric absorption; random noise comprises sensor noise and intrapixel variability (i.e., variability within a pixel). The three existing methods for estimating the SNR are inadequate, since typical laboratory methods inflate while dark current and image methods deflate the SNR. A new procedure is proposed called the geostatistical method. It is based on the removal of periodic noise by notch filtering in the frequency domain and the isolation of sensor noise and intrapixel variability using the semi-variogram. This procedure was applied easily and successfully to five sets of AVIRIS data from the 1987 flying season and could be applied to remotely sensed data from broadband sensors.

  7. Optimal Correlation Filters for Images with Signal-Dependent Noise

    Science.gov (United States)

    Downie, John D.; Walkup, John F.

    1994-01-01

    We address the design of optimal correlation filters for pattern detection and recognition in the presence of signal-dependent image noise sources. The particular examples considered are film-grain noise and speckle. Two basic approaches are investigated: (1) deriving the optimal matched filters for the signal-dependent noise models and comparing their performances with those derived for traditional signal-independent noise models and (2) first nonlinearly transforming the signal-dependent noise to signal-independent noise followed by the use of a classical filter matched to the transformed signal. We present both theoretical and computer simulation results that demonstrate the generally superior performance of the second approach in terms of the correlation peak signal-to-noise ratio.

  8. Stochastic resonance with colored noise for neural signal detection.

    Science.gov (United States)

    Duan, Fabing; Chapeau-Blondeau, François; Abbott, Derek

    2014-01-01

    We analyze signal detection with nonlinear test statistics in the presence of colored noise. In the limits of small signal and weak noise correlation, the optimal test statistic and its performance are derived under general conditions, especially concerning the type of noise. We also analyze, for a threshold nonlinearity-a key component of a neural model, the conditions for noise-enhanced performance, establishing that colored noise is superior to white noise for detection. For a parallel array of nonlinear elements, approximating neurons, we demonstrate even broader conditions allowing noise-enhanced detection, via a form of suprathreshold stochastic resonance.

  9. Adaptive EMG noise reduction in ECG signals using noise level approximation

    Science.gov (United States)

    Marouf, Mohamed; Saranovac, Lazar

    2017-12-01

    In this paper the usage of noise level approximation for adaptive Electromyogram (EMG) noise reduction in the Electrocardiogram (ECG) signals is introduced. To achieve the adequate adaptiveness, a translation-invariant noise level approximation is employed. The approximation is done in the form of a guiding signal extracted as an estimation of the signal quality vs. EMG noise. The noise reduction framework is based on a bank of low pass filters. So, the adaptive noise reduction is achieved by selecting the appropriate filter with respect to the guiding signal aiming to obtain the best trade-off between the signal distortion caused by filtering and the signal readability. For the evaluation purposes; both real EMG and artificial noises are used. The tested ECG signals are from the MIT-BIH Arrhythmia Database Directory, while both real and artificial records of EMG noise are added and used in the evaluation process. Firstly, comparison with state of the art methods is conducted to verify the performance of the proposed approach in terms of noise cancellation while preserving the QRS complex waves. Additionally, the signal to noise ratio improvement after the adaptive noise reduction is computed and presented for the proposed method. Finally, the impact of adaptive noise reduction method on QRS complexes detection was studied. The tested signals are delineated using a state of the art method, and the QRS detection improvement for different SNR is presented.

  10. NAFASS: Discrete spectroscopy of random signals

    Energy Technology Data Exchange (ETDEWEB)

    Nigmatullin, R.R., E-mail: nigmat@knet.r [Institute of Physics, Kazan (Volga Region) Federal University, Kremlevskaya str.18, Kazan, Tatarstan 420008 (Russian Federation); Osokin, S.I. [Institute of Physics, Kazan (Volga Region) Federal University, Kremlevskaya str.18, Kazan, Tatarstan 420008 (Russian Federation); Toboev, V.A. [Department of Mathematics, Chuvash State University, Moskovskiy pr., 15, Cheboksary 428015 (Russian Federation)

    2011-04-15

    Research highlights: The successful solution of the Prony's problem has been obtained. It means that for any random signal its amplitude-frequency response can be found. This solution opens quite new possibilities in creation of new discrete spectroscopy in analysis of different nanoscopic and intermolecular signals. Real NIR spectra and biological data were considered and analyzed as examples. The conception of the pseudo-ergodic noise is introduced. It helps to fit the auto-correlation function that is related to remnant function. The three basic principles of the fluctuation metrology are formulated. - Abstract: In this paper we suggest a new discrete spectroscopy for analysis of random signals and fluctuations. This discrete spectroscopy is based on successful solution of the modified Prony's problem for the strongly-correlated random sequences. As opposed to the general Prony's problem where the set of frequencies is supposed to be unknown in the new approach suggested the distribution of the unknown frequencies can be found for the strongly-correlated random sequences. Preliminary information about the frequency distribution facilitates the calculations and attaches an additional stability in the presence of a noise. This spectroscopy uses only the informative-significant frequency band that helps to fit the given signal with high accuracy. It means that any random signal measured in t-domain can be 'read' in terms of its amplitude-frequency response (AFR) without model assumptions related to the behavior of this signal in the frequency region. The method overcomes some essential drawbacks of the conventional Prony's method and can be determined as the non-orthogonal amplitude frequency analysis of the smoothed sequences (NAFASS). In this paper we outline the basic principles of the NAFASS procedure and show its high potential possibilities based on analysis of some actual NIR data. The AFR obtained serves as a specific

  11. Signal processing of aircraft flyover noise

    Science.gov (United States)

    Kelly, J. J.

    1993-01-01

    A detailed analysis of signal processing concerns for measuring aircraft flyover noise is presented. Development of a de-Dopplerization scheme for both corrected time history and spectral data is discussed along with an analysis of motion effects on measured spectra. A computer code was written to implement the de-Dopplerization scheme. Input to the code is the aircraft position data and the pressure time histories. To facilitate ensemble averaging, a level uniform flyover is considered in the study, but the code can accept more general flight profiles. The effects of spectral smearing and its removal are discussed. Using test data acquired from an XV-15 tilt-rotor flyover, comparisons are made between the measured and corrected spectra. Frequency shifts are accurately accounted for by the de-Dopplerization procedure. It is shown that by correcting for spherical spreading and Doppler amplitude, along with frequency, can give some idea about noise source directivity. The analysis indicated that smearing increases with frequency and is more severe on approach than recession.

  12. Computational study of noise in a large signal transduction network

    Directory of Open Access Journals (Sweden)

    Ruohonen Keijo

    2011-06-01

    Full Text Available Abstract Background Biochemical systems are inherently noisy due to the discrete reaction events that occur in a random manner. Although noise is often perceived as a disturbing factor, the system might actually benefit from it. In order to understand the role of noise better, its quality must be studied in a quantitative manner. Computational analysis and modeling play an essential role in this demanding endeavor. Results We implemented a large nonlinear signal transduction network combining protein kinase C, mitogen-activated protein kinase, phospholipase A2, and β isoform of phospholipase C networks. We simulated the network in 300 different cellular volumes using the exact Gillespie stochastic simulation algorithm and analyzed the results in both the time and frequency domain. In order to perform simulations in a reasonable time, we used modern parallel computing techniques. The analysis revealed that time and frequency domain characteristics depend on the system volume. The simulation results also indicated that there are several kinds of noise processes in the network, all of them representing different kinds of low-frequency fluctuations. In the simulations, the power of noise decreased on all frequencies when the system volume was increased. Conclusions We concluded that basic frequency domain techniques can be applied to the analysis of simulation results produced by the Gillespie stochastic simulation algorithm. This approach is suited not only to the study of fluctuations but also to the study of pure noise processes. Noise seems to have an important role in biochemical systems and its properties can be numerically studied by simulating the reacting system in different cellular volumes. Parallel computing techniques make it possible to run massive simulations in hundreds of volumes and, as a result, accurate statistics can be obtained from computational studies.

  13. Seismic random noise attenuation using shearlet and total generalized variation

    Science.gov (United States)

    Kong, Dehui; Peng, Zhenming

    2015-12-01

    Seismic denoising from a corrupted observation is an important part of seismic data processing which improves the signal-to-noise ratio (SNR) and resolution. In this paper, we present an effective denoising method to attenuate seismic random noise. The method takes advantage of shearlet and total generalized variation (TGV) regularization. Different regularity levels of TGV improve the quality of the final result by suppressing Gibbs artifacts caused by the shearlet. The problem is formulated as mixed constraints in a convex optimization. A Bregman algorithm is proposed to solve the proposed model. Extensive experiments based on one synthetic datum and two post-stack field data are done to compare performance. The results demonstrate that the proposed method provides superior effectiveness and preserve the structure better.

  14. Signal and noise in bridging PCR

    Directory of Open Access Journals (Sweden)

    Thaler David S

    2002-07-01

    Full Text Available Abstract Background In a variant of the standard PCR reaction termed bridging, or jumping, PCR the primer-bound sequences are originally on separate template molecules. Bridging can occur if, and only if, the templates contain a region of sequence similarity. A 3' end of synthesis in one round of synthesis that terminates in this region of similarity can prime on the other. In principle, Bridging PCR (BPCR can detect a subpopulation of one template that terminates synthesis in the region of sequence shared by the other template. This study considers the sensitivity and noise of BPCR as a quantitative assay for backbone interruptions. Bridging synthesis is also important to some methods for computing with DNA. Results In this study, BPCR was tested over a 328 base pair segment of the E. coli lac operon and a signal to noise ratio (S/N of approximately 10 was obtained under normal PCR conditions with Taq polymerase. With special precautions in the case of Taq or by using the Stoffel fragment the S/N was improved to 100, i.e. 1 part of cut input DNA yielded the same output as 100 parts of intact input DNA. Conclusions In the E. coli lac operator region studied here, depending on details of protocol, between 3 and 30% per kilobase of final PCR product resulted from bridging. Other systems are expected to differ in the proportion of product that is bridged consequent to PCR protocol and the sequence analyzed. In many cases physical bridging during PCR will have no informational consequence because the bridged templates are of identical sequence, but in a number of special cases bridging creates, or, destroys, information.

  15. ADAPTIVE NOISE CANCELLATION OF DOPPLER SHIFTED SIGNALS: A LINEAR FRAMEWORK

    OpenAIRE

    Stewart, R. W.; Weiss, S.

    1996-01-01

    In this paper we investigate the performance of single channel adaptive noise cancellation techniques for situations where the noise signal received by the two microphones cannot be related by a fixed weight canceller's (linear) digital filter due to Doppler shift on the two signals. A mathematical signal model is produced, which shows that the adaptive filter is in fact required to identify a time-varying system which incorporates Doppler shift, and potential rapid variations in signal power...

  16. Optimized signal-to-noise ratio with shot noise limited detection in Stimulated Raman Scattering microscopy

    NARCIS (Netherlands)

    Moester, M.J.B.; Ariese, F.; de Boer, J.F.

    2015-01-01

    We describe our set-up for Stimulated Raman Scattering (SRS) microscopy with shot noise limited detection for a broad window of biologically relevant laser powers. This set-up is used to demonstrate that the highest signal-to-noise ratio (SNR) in SRS with shot noise limited detection is achieved

  17. Enhanced signal detectability in comodulated noise introduced by compression.

    Science.gov (United States)

    Buschermöhle, Michael; Feudel, Ulrike; Freund, Jan A

    2008-12-01

    Many examples of natural noise show common amplitude modulations at different frequency regions. This kind of noise has been termed comodulated noise and is widely examined in hearing research, where an enhanced detectability of pure tones and narrow noise bands in comodulated noise compared to unmodulated noise is well known as the CMR or CDD effects, respectively. Here it is shown that only one signal processing step, a compressive nonlinearity motivated by the peripheral auditory system, is sufficient to explain a considerable contribution to these effects. Using an analytical approach, the influence of compression on the detectability of periodic and narrow band signals in the presence of unmodulated and comodulated noise is investigated. This theoretical treatment allows for identifying the mechanism leading to improved signal detection. The compressive nonlinearity constitutes an adaptive gain which selectively boosts a stimulus during time spans of inherently increased signal-to-noise ratio and attenuates it during time spans dominated by noise. On average, these time spans are more pronounced in stimuli with comodulated noise than with unmodulated noise, thus giving rise to the observed CMR and CDD effects.

  18. Random telegraphic voltage noise due to thermal bi-stability in a superconducting weak link

    Science.gov (United States)

    Biswas, Sourav; Kumar, Nikhil; Winkelmann, C. B.; Courtois, Herve; Gupta, Anjan K.

    2016-05-01

    We investigated the random telegraphic voltage noise signal in the hysteretic bi-stable state of a superconducting weak link device. Fluctuation induced random switching between zero voltage state and non-zero-voltage state gives rise to a random telegraphic voltage signal in time domain. This telegraphic noise is used to find the mean lifetime of each of the two states. The mean life time in the zero voltage state is found to decrease with increasing bias current while that of resistive state increases and thus the two cross at certain bias current. We qualitatively discuss this observed switching behavior as arising from the bi-stable nature.

  19. Biologically-based signal processing system applied to noise removal for signal extraction

    Science.gov (United States)

    Fu, Chi Yung; Petrich, Loren I.

    2004-07-13

    The method and system described herein use a biologically-based signal processing system for noise removal for signal extraction. A wavelet transform may be used in conjunction with a neural network to imitate a biological system. The neural network may be trained using ideal data derived from physical principles or noiseless signals to determine to remove noise from the signal.

  20. The influence of amplifier, interface and biological noise on signal quality in high-resolution EEG recordings.

    Science.gov (United States)

    Scheer, Hans J; Sander, Tilmann; Trahms, Lutz

    2006-02-01

    First, the intrinsic random noise sources of a biopotential measurement in general are reviewed. For the special case of an electroencephalographic (EEG) measurement we have extended the commonly used amplifier noise model by biological generated background noise. As the strongest of all noise sources involved will dominate the resulting signal to noise ratio (S/N), we have investigated under which conditions this will be the case. We illustrate experimentally that up to 100 Hz S/N practically depends only on cortical generated background noise, while at a few hundred Hz or more amplifier and thermal noise of interelectrode resistance are the major sources.

  1. Noise characterization for the FID signal from proton precession magnetometer

    Science.gov (United States)

    Liu, H.; Dong, H.; Liu, Z.; Ge, J.; Bai, B.; Zhang, C.

    2017-07-01

    Proton precession magnetometer is a high-precision device for weak magnetostatic field measurement. The measurement accuracy depends on the frequency measurement of free induction decay (FID) signal, while the signal to noise ratio (SNR) is an important factor affecting the results. Many signal processing methods have been proposed to improve the SNR of FID signal. However, the theoretical analysis of different types of noises for FID signal has not be conducted yet. In addition, the relationship between the frequency measurement accuracy and SNR has not been explicitly established and quantified. This paper first proposes a background noise model based on the extracted features from the FID signal. With this model, background noises, such as white noise, narrow-band noise, and phase noise etc., can be calculated and estimated. Secondly, the relationship between the frequency measurement accuracy and SNR is identified. We also built a prototype proton magnetometer for field tests and validation purpose. Experiments were conducted to investigate this relation through simulation. Different values for frequency accuracy were obtained with different SNRs from the acquired FID signals from field tests. The consistence between the measurement and computational results is observed. When SNR is larger than 30 dB, the absolute frequency accuracy becomes constant which is about 0.04 Hz. With the stability taken into account, the accuracy can be better even when the SNR is higher than 30 dB. This study provides a reference to optimize the design of proton precession magnetometer and the frequency calculation for FID signal.

  2. Fluorescence microscopy image noise reduction using a stochastically-connected random field model.

    Science.gov (United States)

    Haider, S A; Cameron, A; Siva, P; Lui, D; Shafiee, M J; Boroomand, A; Haider, N; Wong, A

    2016-02-17

    Fluorescence microscopy is an essential part of a biologist's toolkit, allowing assaying of many parameters like subcellular localization of proteins, changes in cytoskeletal dynamics, protein-protein interactions, and the concentration of specific cellular ions. A fundamental challenge with using fluorescence microscopy is the presence of noise. This study introduces a novel approach to reducing noise in fluorescence microscopy images. The noise reduction problem is posed as a Maximum A Posteriori estimation problem, and solved using a novel random field model called stochastically-connected random field (SRF), which combines random graph and field theory. Experimental results using synthetic and real fluorescence microscopy data show the proposed approach achieving strong noise reduction performance when compared to several other noise reduction algorithms, using quantitative metrics. The proposed SRF approach was able to achieve strong performance in terms of signal-to-noise ratio in the synthetic results, high signal to noise ratio and contrast to noise ratio in the real fluorescence microscopy data results, and was able to maintain cell structure and subtle details while reducing background and intra-cellular noise.

  3. Noise contributions to the fMRI signal: An overview.

    Science.gov (United States)

    Liu, Thomas T

    2016-12-01

    The ability to discriminate signal from noise plays a key role in the analysis and interpretation of functional magnetic resonance imaging (fMRI) measures of brain activity. Over the past two decades, a number of major sources of noise have been identified, including system-related instabilities, subject motion, and physiological fluctuations. This article reviews the characteristics of the various noise sources as well as the mechanisms through which they affect the fMRI signal. Approaches for distinguishing signal from noise and the associated challenges are also reviewed. These challenges reflect the fact that some noise sources, such as respiratory activity, are generated by the same underlying brain networks that give rise to functional signals that are of interest. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. Phase-Noise and Amplitude-Noise Measurement of Low-Power Signals

    Science.gov (United States)

    Rubiola, Enrico; Salik, Ertan; Yu, Nan; Maleki, Lute

    2004-01-01

    Measuring the phase fluctuation between a pair of low-power microwave signals, the signals must be amplified before detection. In such cases the phase noise of the amplifier pair is the main cause of 1/f background noise of the instrument. this article proposes a scheme that makes amplification possible while rejecting the close in 1/f (flicker) noise of the two amplifiers. Noise rejection, which relies upon the understanding of the amplifier noise mechanism does not require averaging. Therefore, our scheme can also be the detector of a closed loop noise reduction system. the first prototype, compared to a traditional saturated mixer system under the same condition, show a 24 dB noise reduction of the 1/f region.

  5. Noise Filtering and Prediction in Biological Signaling Networks

    CERN Document Server

    Hathcock, David; Weisenberger, Casey; Ilker, Efe; Hinczewski, Michael

    2016-01-01

    Information transmission in biological signaling circuits has often been described using the metaphor of a noise filter. Cellular systems need accurate, real-time data about their environmental conditions, but the biochemical reaction networks that propagate, amplify, and process signals work with noisy representations of that data. Biology must implement strategies that not only filter the noise, but also predict the current state of the environment based on information delayed due to the finite speed of chemical signaling. The idea of a biochemical noise filter is actually more than just a metaphor: we describe recent work that has made an explicit mathematical connection between signaling fidelity in cellular circuits and the classic theories of optimal noise filtering and prediction that began with Wiener, Kolmogorov, Shannon, and Bode. This theoretical framework provides a versatile tool, allowing us to derive analytical bounds on the maximum mutual information between the environmental signal and the re...

  6. On signal design by the R/0/ criterion for non-white Gaussian noise channels

    Science.gov (United States)

    Bordelon, D. L.

    1977-01-01

    The use of the cut-off rate criterion for modulation system design is investigated for channels with non-white Gaussian noise. A signal space representation of the waveform channel is developed, and the cut-off rate for vector channels with additive non-white Gaussian noise and unquantized demodulation is derived. When the signal input to the channel is a continuous random vector, maximization of the cut-off rate with constrained average signal energy leads to a water-filling interpretation of optimal energy distribution in signal space. The necessary condition for a finite signal set to maximize the cut-off rate with constrained energy and an equally likely probability assignment of signal vectors is presented, and an algorithm is outlined for numerically computing the optimum signal set. As an example, the rectangular signal set which has the water-filling average energy distribution and the optimum rectangular set are compared.

  7. Removal of signal-dependent noise for a digital camera

    Science.gov (United States)

    Saito, Takahiro; Ishii, Yuki; Nosaka, Reina; Komatsu, Takashi

    2007-02-01

    In a digital camera, several factors cause signal-dependency of additive noise. Many denoising methods have been proposed, but unfortunately most of them do not work well for the actual signal-dependent noise. To solve the problem of removing the signal-dependent noise of a digital camera, we present a denoising approach via the nonlinear imagedecomposition. In the nonlinear decomposition-and-denoising approach, at the first nonlinear image-decomposition stage, multiplicative image-decomposition is performed, and a noisy image is represented as a product of its two components so that its structural component corresponding to a cartoon approximation of the noisy image may not be corrupted by the noise and its texture component may collect almost all the noise. At the successive nonlinear denoising stage, intensity of the separated structural component is utilized instead of the unknown true signal value, to adapt the soft-thresholding-type denoising manipulation of the texture component to the signal dependency of the noise. At the final image-synthesis stage, the separated structure component is combined with the denoised texture component, and thus a sharpness-improved denoised image is reproduced. The nonlinear decomposition-and-denoising approach can selectively remove the signal-dependent noise of a digital camera without not only blurring sharp edges but also destroying visually important textures.

  8. Explicit signal to noise ratio in reproducing kernel Hilbert spaces

    DEFF Research Database (Denmark)

    Gomez-Chova, Luis; Nielsen, Allan Aasbjerg; Camps-Valls, Gustavo

    2011-01-01

    an alternative kernel MNF (KMNF) in which the noise is explicitly estimated in the reproducing kernel Hilbert space. This enables KMNF dealing with non-linear relations between the noise and the signal features jointly. Results show that the proposed KMNF provides the most noise-free features when confronted...... with PCA, MNF, KPCA, and the previous version of KMNF. Extracted features with the explicit KMNF also improve hyperspectral image classification....

  9. Signal-to-Noise Ratio in Physical Education Settings

    Science.gov (United States)

    Ryan, Stu; Grube, Dan; Mokgwathi, Martin M.

    2010-01-01

    It is generally known that in educational settings, excessive noise masks what the teacher is saying; thus, and for maximum learning to occur, the teacher's voice must be highly intelligible to all children (Crandell, Smaldino, & Flexer, 1995). The difference between what the teacher is saying (signal) and the classroom noise level is commonly…

  10. Measurement of MOSFET LF Noise Under Large Signal RF Excitation

    NARCIS (Netherlands)

    van der Wel, A.P.; Klumperink, Eric A.M.; Nauta, Bram

    A new measurement technique is presented that allows measurement of MOSFET LF noise under large signal RF excitation. Measurements indicate that MOSFETS exhibit a reduction in LF noise when they are cycled from inversion to accummulation and that this reduction does not depend on the frequency of

  11. Removing Background Noise with Phased Array Signal Processing

    Science.gov (United States)

    Podboy, Gary; Stephens, David

    2015-01-01

    Preliminary results are presented from a test conducted to determine how well microphone phased array processing software could pull an acoustic signal out of background noise. The array consisted of 24 microphones in an aerodynamic fairing designed to be mounted in-flow. The processing was conducted using Functional Beam forming software developed by Optinav combined with cross spectral matrix subtraction. The test was conducted in the free-jet of the Nozzle Acoustic Test Rig at NASA GRC. The background noise was produced by the interaction of the free-jet flow with the solid surfaces in the flow. The acoustic signals were produced by acoustic drivers. The results show that the phased array processing was able to pull the acoustic signal out of the background noise provided the signal was no more than 20 dB below the background noise level measured using a conventional single microphone equipped with an aerodynamic forebody.

  12. A signal theoretic introduction to random processes

    CERN Document Server

    Howard, Roy M

    2015-01-01

    A fresh introduction to random processes utilizing signal theory By incorporating a signal theory basis, A Signal Theoretic Introduction to Random Processes presents a unique introduction to random processes with an emphasis on the important random phenomena encountered in the electronic and communications engineering field. The strong mathematical and signal theory basis provides clarity and precision in the statement of results. The book also features:  A coherent account of the mathematical fundamentals and signal theory that underpin the presented material Unique, in-depth coverage of

  13. Pump to signal noise transfer in parametric fiber amplifiers

    DEFF Research Database (Denmark)

    Lund-Hansen, Toke; Rottwitt, Karsten; Peucheret, Christophe

    2010-01-01

    Fiber optic parametric amplifiers have been suggested due to their potential low spontaneous emission. However, by nature the parametric amplifier only work in a forward pumped configuration, which result in transfer of relative intensity noise in the pump to the signal.......Fiber optic parametric amplifiers have been suggested due to their potential low spontaneous emission. However, by nature the parametric amplifier only work in a forward pumped configuration, which result in transfer of relative intensity noise in the pump to the signal....

  14. Stimulus configuration determines the detectability of motion signals in noise

    Science.gov (United States)

    Verghese, P.; McKee, S. P.; Grzywacz, N. M.

    2000-01-01

    We measured the detectability of moving signal dots in dynamic noise to determine whether local motion signals are preferentially combined along an axis parallel to the direction of motion. Observers were asked to detect a signal composed of three dots moving in a linear trajectory among dynamic noise dots. The signal dots were collinear and equally spaced in a configuration that was either parallel to or perpendicular to their trajectory. The probability of detecting the signal was measured as a function of noise density, over a range of signal dot spacings from 0.5 degrees to 5.0 degrees. At any given noise density, the signal in the parallel configuration was more detectable than that in the perpendicular configuration. Our four observers could tolerate 1.5-2.5 times more noise in the parallel configuration. This improvement is not due merely to temporal summation between consecutive dots in the parallel trajectory. Temporal summation functions measured on our observers indicate that the benefit from spatial coincidence of the dots lasts for no more than 50 ms, whereas the increased detectability of the parallel configuration is observed up to the largest temporal separations tested (210 ms). These results demonstrate that dots arranged parallel to the signal trajectory are more easily detected than those arranged perpendicularly. Moreover, this enhancement points to the existence of visual mechanisms that preferentially organize motion information parallel to the direction of motion.

  15. Light field reconstruction robust to signal dependent noise

    Science.gov (United States)

    Ren, Kun; Bian, Liheng; Suo, Jinli; Dai, Qionghai

    2014-11-01

    Capturing four dimensional light field data sequentially using a coded aperture camera is an effective approach but suffers from low signal noise ratio. Although multiplexing can help raise the acquisition quality, noise is still a big issue especially for fast acquisition. To address this problem, this paper proposes a noise robust light field reconstruction method. Firstly, scene dependent noise model is studied and incorporated into the light field reconstruction framework. Then, we derive an optimization algorithm for the final reconstruction. We build a prototype by hacking an off-the-shelf camera for data capturing and prove the concept. The effectiveness of this method is validated with experiments on the real captured data.

  16. Power Quality Signal De-noising with Subband Adaptive Algorithm

    Directory of Open Access Journals (Sweden)

    Yingjun Sang

    2013-07-01

    Full Text Available A new level-dependent subband adaptive noise reduction algorithm based on wavelet transform is proposed in order to improve the effect of power quality signal de-noising for power quality monitoring system. This threshold algorithm has two adjustable parameters to adjust the threshold both fine and coarsely, and the optimal parameters are determined by BP neural networks algorithm. Power disturbance data is refered to actual power disturbance data at IEEE open source and applied for test. The test results indicate that the proposed algorithm could denoise the different kind of power disturbances effectively, and the signal noise ratio is improved further with a smaller mean square error.

  17. Separating Decision and Encoding Noise in Signal Detection Tasks

    Science.gov (United States)

    Cabrera, Carlos Alexander; Lu, Zhong-Lin; Dosher, Barbara Anne

    2015-01-01

    In this paper we develop an extension to the Signal Detection Theory (SDT) framework to separately estimate internal noise arising from representational and decision processes. Our approach constrains SDT models with decision noise by combining a multi-pass external noise paradigm with confidence rating responses. In a simulation study we present evidence that representation and decision noise can be separately estimated over a range of representative underlying representational and decision noise level configurations. These results also hold across a number of decision rules and show resilience to rule miss-specification. The new theoretical framework is applied to a visual detection confidence-rating task with three and five response categories. This study compliments and extends the recent efforts of researchers (Benjamin, Diaz, & Wee, 2009; Mueller & Weidemann, 2008; Rosner & Kochanski, 2009, Kellen, Klauer, & Singmann, 2012) to separate and quantify underlying sources of response variability in signal detection tasks. PMID:26120907

  18. Signal-to-noise ratio limitations for intensity correlation imaging.

    Science.gov (United States)

    Fried, David L; Riker, Jim; Agrawal, Brij

    2014-07-01

    Intensity correlation imaging (ICI) is a concept which has been considered for the task of providing images of satellites in geosynchronous orbit using ground-based equipment. This concept is based on the intensity interferometer principle first developed by Hanbury Brown and Twiss. It is the objective of this paper to establish that a sun-lit geosynchronous satellite is too faint a target object to allow intensity interferometry to be used in developing image information about it-at least not in a reasonable time and with a reasonable amount of equipment. An analytic treatment of the basic phenomena is presented. This is an analysis of one aspect of the statistics of the very high frequency random variations of a very narrow portion of the optical spectra of the incoherent (black-body like-actually reflected sunlight) radiation from the satellite, an analysis showing that the covariance of this radiation as measured by a pair of ground-based telescopes is directly proportional to the square of the magnitude of one component of the Fourier transform of the image of the satellite-the component being the one for a spatial frequency whose value is determined by the separation of the two telescopes. This analysis establishes the magnitude of the covariance. A second portion of the analysis considers shot-noise effects. It is shown that even with much less than one photodetection event (pde) per signal integration time an unbiased estimate of the covariance of the optical field's random variations can be developed. Also, a result is developed for the standard deviation to be associated with the estimated value of the covariance. From these results an expression is developed for what may be called the signal-to-noise ratio to be associated with an estimate of the covariance. This signal-to-noise ratio, it turns out, does not depend on the measurement's integration time, Δt (in seconds), or on the optical spectral bandwidth, Δν (in Hertz), utilized-so long as

  19. Signal processing of jet noise from flyover test data

    Science.gov (United States)

    Kelly, Jeffrey J.; Wilson, Mark R.

    1993-01-01

    Narrow-band spectra characterizing jet noise are constructed from flyover acoustic measurements. Radar and c-band tracking systems provided the aircraft position histories which enabled directivity and smear angles from the aircraft to each microphone to be computed. These angles are based on source emission time and thus give some idea about the directivity of the radiated sound field due to jet noise. Simulated spectra are included in the paper to demonstrate spectral broadening due to smear angle. The acoustic data described in the study has application to community noise analysis, noise source characterization and validation of prediction models. Both broadband-shock noise and turbulent mixing noise are observed in the spectra. A detailed description of the signal processing procedures is provided.

  20. Measuring the signal-to-noise ratio of a neuron.

    Science.gov (United States)

    Czanner, Gabriela; Sarma, Sridevi V; Ba, Demba; Eden, Uri T; Wu, Wei; Eskandar, Emad; Lim, Hubert H; Temereanca, Simona; Suzuki, Wendy A; Brown, Emery N

    2015-06-09

    The signal-to-noise ratio (SNR), a commonly used measure of fidelity in physical systems, is defined as the ratio of the squared amplitude or variance of a signal relative to the variance of the noise. This definition is not appropriate for neural systems in which spiking activity is more accurately represented as point processes. We show that the SNR estimates a ratio of expected prediction errors and extend the standard definition to one appropriate for single neurons by representing neural spiking activity using point process generalized linear models (PP-GLM). We estimate the prediction errors using the residual deviances from the PP-GLM fits. Because the deviance is an approximate χ(2) random variable, we compute a bias-corrected SNR estimate appropriate for single-neuron analysis and use the bootstrap to assess its uncertainty. In the analyses of four systems neuroscience experiments, we show that the SNRs are -10 dB to -3 dB for guinea pig auditory cortex neurons, -18 dB to -7 dB for rat thalamic neurons, -28 dB to -14 dB for monkey hippocampal neurons, and -29 dB to -20 dB for human subthalamic neurons. The new SNR definition makes explicit in the measure commonly used for physical systems the often-quoted observation that single neurons have low SNRs. The neuron's spiking history is frequently a more informative covariate for predicting spiking propensity than the applied stimulus. Our new SNR definition extends to any GLM system in which the factors modulating the response can be expressed as separate components of a likelihood function.

  1. Signal and Noise in 3D Environments

    Science.gov (United States)

    2015-09-30

    complicated 3D environments. I have also been doing a great deal of work in modeling the noise field (the ocean soundscape ) due to various sources... soundscape to learn about the ocean environment. I distinguish this from geoacoustic inversion and ocean tomography, in that the methods envisioned will rely...on broader features of the soundscape . OBJECTIVES In the first phase of this effort we will focus on the 3D modeling solutions, documenting the

  2. Effects of noise suppression on intelligibility: dependency on signal-to-noise ratios.

    Science.gov (United States)

    Hilkhuysen, Gaston; Gaubitch, Nikolay; Brookes, Mike; Huckvale, Mark

    2012-01-01

    The effects on speech intelligibility of three different noise reduction algorithms (spectral subtraction, minimal mean squared error spectral estimation, and subspace analysis) were evaluated in two types of noise (car and babble) over a 12 dB range of signal-to-noise ratios (SNRs). Results from these listening experiments showed that most algorithms deteriorated intelligibility scores. Modeling of the results with a logit-shaped psychometric function showed that the degradation in intelligibility scores was largely congruent with a constant shift in SNR, although some additional degradation was observed at two SNRs, suggesting a limited interaction between the effects of noise suppression and SNR. © 2012 Acoustical Society of America.

  3. Cascaded analysis of signal and noise propagation through a heterogeneous breast model

    Energy Technology Data Exchange (ETDEWEB)

    Mainprize, James G.; Yaffe, Martin J. [Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5 (Canada); Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5 (Canada) and Department of Medical Biophysics, University of Toronto, Toronto, Ontario M4N 3M5 (Canada)

    2010-10-15

    Purpose: The detectability of lesions in radiographic images can be impaired by patterns caused by the surrounding anatomic structures. The presence of such patterns is often referred to as anatomic noise. Others have previously extended signal and noise propagation theory to include variable background structure as an additional noise term and used in simulations for analysis by human and ideal observers. Here, the analytic forms of the signal and noise transfer are derived to obtain an exact expression for any input random distribution and the ''power law'' filter used to generate the texture of the tissue distribution. Methods: A cascaded analysis of propagation through a heterogeneous model is derived for x-ray projection through simulated heterogeneous backgrounds. This is achieved by considering transmission through the breast as a correlated amplification point process. The analytic forms of the cascaded analysis were compared to monoenergetic Monte Carlo simulations of x-ray propagation through power law structured backgrounds. Results: As expected, it was found that although the quantum noise power component scales linearly with the x-ray signal, the anatomic noise will scale with the square of the x-ray signal. There was a good agreement between results obtained using analytic expressions for the noise power and those from Monte Carlo simulations for different background textures, random input functions, and x-ray fluence. Conclusions: Analytic equations for the signal and noise properties of heterogeneous backgrounds were derived. These may be used in direct analysis or as a tool to validate simulations in evaluating detectability.

  4. Reducing Noise by Repetition: Introduction to Signal Averaging

    Science.gov (United States)

    Hassan, Umer; Anwar, Muhammad Sabieh

    2010-01-01

    This paper describes theory and experiments, taken from biophysics and physiological measurements, to illustrate the technique of signal averaging. In the process, students are introduced to the basic concepts of signal processing, such as digital filtering, Fourier transformation, baseline correction, pink and Gaussian noise, and the cross- and…

  5. Perceptually optimized gain function for cochlear implant signal-to-noise ratio based noise reduction.

    Science.gov (United States)

    Mauger, Stefan J; Dawson, Pam W; Hersbach, Adam A

    2012-01-01

    Noise reduction in cochlear implants has achieved significant speech perception improvements through spectral subtraction and signal-to-noise ratio based noise reduction techniques. Current methods use gain functions derived through mathematical optimization or motivated by normal listening psychoacoustic experiments. Although these gain functions have been able to improve speech perception, recent studies have indicated that they are not optimal for cochlear implant noise reduction. This study systematically investigates cochlear implant recipients' speech perception and listening preference of noise reduction with a range of gain functions. Results suggest an advantageous gain function and show that gain functions currently used for noise reduction are not optimal for cochlear implant recipients. Using the cochlear implant optimised gain function, a 27% improvement over the current advanced combination encoder (ACE) stimulation strategy in speech weighted noise and a 7% improvement over current noise reduction strategies were observed in babble noise conditions. The optimized gain function was also most preferred by cochlear implant recipients. The CI specific gain function derived from this study can be easily incorporated into existing noise reduction strategies, to further improve listening performance for CI recipients in challenging environments. © 2012 Acoustical Society of America.

  6. Reduction of PMT Signal-Induced Noise in Lidar Receivers

    Science.gov (United States)

    Williamson, Cynthia K.; DeYoung, Russell J.

    1998-01-01

    Signal-induced noise is generated when a photomultiplier tube (PMT) is subjected to an intense light pulse. The PMT signal does not return to the dark current level after the signal is removed, but decays slowly (i.e., signal-induced noise). This is of practical significance for DIAL (Differential Absorption lidar) measurements where signal-induced noise decays are superimposed on the on-line (absorption) and off-line signals. Errors in the ozone density calculation result for stratosphere measurements. Other researchers have implemented mechanical choppers that block the intense pulse which may be from near field return scattering or scattering from a cloud. This configuration cannot be implemented for the DIAL system employed for aircraft measurements since the on-line and off-line pulses are 300 microseconds apart. A scheme has been developed in this study to electronically attenuate the signal induced noise. A ring electrode, external to the PMT photocathode, is utilized to perturb the electron trajectories between the photocathode and the first dynode. This effect has been used for position sensitive PMTs and suggested for gating PMTS.

  7. Diffusion MRI noise mapping using random matrix theory

    Science.gov (United States)

    Veraart, Jelle; Fieremans, Els; Novikov, Dmitry S.

    2016-01-01

    Purpose To estimate the spatially varying noise map using a redundant magnitude MR series. Methods We exploit redundancy in non-Gaussian multi-directional diffusion MRI data by identifying its noise-only principal components, based on the theory of noisy covariance matrices. The bulk of PCA eigenvalues, arising due to noise, is described by the universal Marchenko-Pastur distribution, parameterized by the noise level. This allows us to estimate noise level in a local neighborhood based on the singular value decomposition of a matrix combining neighborhood voxels and diffusion directions. Results We present a model-independent local noise mapping method capable of estimating noise level down to about 1% error. In contrast to current state-of-the art techniques, the resultant noise maps do not show artifactual anatomical features that often reflect physiological noise, the presence of sharp edges, or a lack of adequate a priori knowledge of the expected form of MR signal. Conclusions Simulations and experiments show that typical diffusion MRI data exhibit sufficient redundancy that enables accurate, precise, and robust estimation of the local noise level by interpreting the PCA eigenspectrum in terms of the Marchenko-Pastur distribution. PMID:26599599

  8. Muon Signals at a Low Signal-to-Noise Ratio Environment

    CERN Document Server

    Zakareishvili, Tamar; The ATLAS collaboration

    2017-01-01

    Calorimeters provide high-resolution energy measurements for particle detection. Muon signals are important for evaluating electronics performance, since they produce a signal that is close to electronic noise values. This work provides a noise RMS analysis for the Demonstrator drawer of the 2016 Tile Calorimeter (TileCal) Test Beam in order to help reconstruct events in a low signal-to-noise environment. Muon signals were then found for a beam penetrating through all three layers of the drawer. The Demonstrator drawer is an electronic candidate for TileCal, part of the ATLAS experiment for the Large Hadron Collider that operates at the European Organization for Nuclear Research (CERN).

  9. DS/LPI autocorrelation detection in noise plus random-tone interference

    Science.gov (United States)

    Hinedi, Sami; Polydoros, Andreas

    1990-01-01

    An analysis is presented of a frequency-noncoherent, two-lag autocorrelation statistic for the wideband detection of random binary phase-shift keying (BPSK) signals in noise plus random multitone interference. It is shown that this detector is quite robust to the presence or absence of interference and its specific parameter values contrary to an energy detector. The rule assumes knowledge of the data rate and the active scenario under H0. The purpose of the paper is to promote the real-time autocorrelation domain and its samples (lags) as a viable approach for detecting random signals in dense environments.

  10. Effects of random noise in a dynamical model of love

    Energy Technology Data Exchange (ETDEWEB)

    Xu Yong, E-mail: hsux3@nwpu.edu.cn [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China); Gu Rencai; Zhang Huiqing [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China)

    2011-07-15

    Highlights: > We model the complexity and unpredictability of psychology as Gaussian white noise. > The stochastic system of love is considered including bifurcation and chaos. > We show that noise can both suppress and induce chaos in dynamical models of love. - Abstract: This paper aims to investigate the stochastic model of love and the effects of random noise. We first revisit the deterministic model of love and some basic properties are presented such as: symmetry, dissipation, fixed points (equilibrium), chaotic behaviors and chaotic attractors. Then we construct a stochastic love-triangle model with parametric random excitation due to the complexity and unpredictability of the psychological system, where the randomness is modeled as the standard Gaussian noise. Stochastic dynamics under different three cases of 'Romeo's romantic style', are examined and two kinds of bifurcations versus the noise intensity parameter are observed by the criteria of changes of top Lyapunov exponent and shape of stationary probability density function (PDF) respectively. The phase portraits and time history are carried out to verify the proposed results, and the good agreement can be found. And also the dual roles of the random noise, namely suppressing and inducing chaos are revealed.

  11. Noise reduction in intracranial pressure signal using causal shape manifolds.

    Science.gov (United States)

    Rajagopal, Abhejit; Hamilton, Robert B; Scalzo, Fabien

    2016-07-01

    We present the Iterative/Causal Subspace Tracking framework (I/CST) for reducing noise in continuously monitored quasi-periodic biosignals. Signal reconstruction of the basic segments of the noisy signal (e.g. beats) is achieved by projection to a reduced space on which probabilistic tracking is performed. The attractiveness of the presented method lies in the fact that the subspace, or manifold, is learned by incorporating temporal, morphological, and signal elevation constraints, so that segment samples with similar shapes, and that are close in time and elevation, are also close in the subspace representation. Evaluation of the algorithm's effectiveness on the intracranial pressure (ICP) signal serves as a practical illustration of how it can operate in clinical conditions on routinely acquired biosignals. The reconstruction accuracy of the system is evaluated on an idealized 20-min ICP recording established from the average ICP of patients monitored for various ICP related conditions. The reconstruction accuracy of the ground truth signal is tested in presence of varying levels of additive white Gaussian noise (AWGN) and Poisson noise processes, and measures significant increases of 758% and 396% in the average signal-to-noise ratio (SNR).

  12. Behavior of quantization noise for sinusoidal signals. A revision.

    Directory of Open Access Journals (Sweden)

    P. R. Pérez‐Alcázar

    2009-08-01

    Full Text Available This paper presents a brief revision of several studies presented in the literature about the behavior of quantization noise forsinusoidal signals and for uniform quantizers. From this revision, the conclusion is that quantization noise has been assumed tobe additive and has a white spectrum, although some published studies, considering the problem either from a deterministicpoint of view or from a stochastic one, have shown a different noise behavior for some specific cases. Some of these cases arerelated with the parameters that characterize the sinusoidal signal and other with the conditions under which the process ofconversion is realized. There are some cases that have not very been well considered in the previous literature and about whichit is convenient to call attention. By this reason and using computer simulations with sinusoidal input signals, it is illustrated herethat the quantization noise spectrum can show a discrete or complex structure depending on the relation between the samplingrate used and the frequency of the signal. Moreover, some points to consider in order to get a better description of thequantization noise are presented.

  13. Mathematical Analysis of Random Noise - and Appendixes

    Science.gov (United States)

    1952-01-01

    ONLY; ADMINISTRATIVE/OPERATIONAL USE; 24 FEB 1999. OTHER REQUESTS SHALL BE REFERRED THROUGH DEFENSE TECHNICAL INFORMATION CENTER, DTIC-BCS, 8725 JOHN J...and (2.1-6) give fw(g) dg = .- , () slic 7r go (2.2-4) 00r) = j cos 2rfr d[j w(g) dg] 1’ This is done by Wiener,ŕ loc. cit., and by G. W. Kenrick ...pp. 176-196 (Jan. 1929). Kenrick appears to be one of the first to apply, to noise problems, the correlatir’ functi.rn mlthnd of camputing the power

  14. Innovative signal processing for Johnson Noise thermometry

    Energy Technology Data Exchange (ETDEWEB)

    Ezell, N. Dianne Bull [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Britton, Jr, Charles L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Roberts, Michael [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2016-07-01

    This report summarizes the newly developed algorithm that subtracted the Electromagnetic Interference (EMI). The EMI performance is very important to this measurement because any interference in the form on pickup from external signal sources from such as fluorescent lighting ballasts, motors, etc. can skew the measurement. Two methods of removing EMI were developed and tested at various locations. This report also summarizes the testing performed at different facilities outside Oak Ridge National Laboratory using both EMI removal techniques. The first EMI removal technique reviewed in previous milestone reports and therefore this report will detail the second method.

  15. Detecting and estimating signals in noisy cable structure, I: neuronal noise sources.

    Science.gov (United States)

    Manwani, A; Koch, C

    1999-11-15

    In recent theoretical approaches addressing the problem of neural coding, tools from statistical estimation and information theory have been applied to quantify the ability of neurons to transmit information through their spike outputs. These techniques, though fairly general, ignore the specific nature of neuronal processing in terms of its known biophysical properties. However, a systematic study of processing at various stages in a biophysically faithful model of a single neuron can identify the role of each stage in information transfer. Toward this end, we carry out a theoretical analysis of the information loss of a synaptic signal propagating along a linear, one-dimensional, weakly active cable due to neuronal noise sources along the way, using both a signal reconstruction and a signal detection paradigm. Here we begin such an analysis by quantitatively characterizing three sources of membrane noise: (1) thermal noise due to the passive membrane resistance, (2) noise due to stochastic openings and closings of voltage-gated membrane channels (NA+ and K+), and (3) noise due to random, background synaptic activity. Using analytical expressions for the power spectral densities of these noise sources, we compare their magnitudes in the case of a patch of membrane from a cortical pyramidal cell and explore their dependence on different biophysical parameters.

  16. Radar antenna pointing for optimized signal to noise ratio.

    Energy Technology Data Exchange (ETDEWEB)

    Doerry, Armin Walter; Marquette, Brandeis

    2013-01-01

    The Signal-to-Noise Ratio (SNR) of a radar echo signal will vary across a range swath, due to spherical wavefront spreading, atmospheric attenuation, and antenna beam illumination. The antenna beam illumination will depend on antenna pointing. Calculations of geometry are complicated by the curved earth, and atmospheric refraction. This report investigates optimizing antenna pointing to maximize the minimum SNR across the range swath.

  17. Operating regimes of signaling cycles: statics, dynamics, and noise filtering.

    Directory of Open Access Journals (Sweden)

    Carlos Gomez-Uribe

    2007-12-01

    Full Text Available A ubiquitous building block of signaling pathways is a cycle of covalent modification (e.g., phosphorylation and dephosphorylation in MAPK cascades. Our paper explores the kind of information processing and filtering that can be accomplished by this simple biochemical circuit. Signaling cycles are particularly known for exhibiting a highly sigmoidal (ultrasensitive input-output characteristic in a certain steady-state regime. Here, we systematically study the cycle's steady-state behavior and its response to time-varying stimuli. We demonstrate that the cycle can actually operate in four different regimes, each with its specific input-output characteristics. These results are obtained using the total quasi-steady-state approximation, which is more generally valid than the typically used Michaelis-Menten approximation for enzymatic reactions. We invoke experimental data that suggest the possibility of signaling cycles operating in one of the new regimes. We then consider the cycle's dynamic behavior, which has so far been relatively neglected. We demonstrate that the intrinsic architecture of the cycles makes them act--in all four regimes--as tunable low-pass filters, filtering out high-frequency fluctuations or noise in signals and environmental cues. Moreover, the cutoff frequency can be adjusted by the cell. Numerical simulations show that our analytical results hold well even for noise of large amplitude. We suggest that noise filtering and tunability make signaling cycles versatile components of more elaborate cell-signaling pathways.

  18. Operating regimes of signaling cycles: statics, dynamics, and noise filtering.

    Science.gov (United States)

    Gomez-Uribe, Carlos; Verghese, George C; Mirny, Leonid A

    2007-12-01

    A ubiquitous building block of signaling pathways is a cycle of covalent modification (e.g., phosphorylation and dephosphorylation in MAPK cascades). Our paper explores the kind of information processing and filtering that can be accomplished by this simple biochemical circuit. Signaling cycles are particularly known for exhibiting a highly sigmoidal (ultrasensitive) input-output characteristic in a certain steady-state regime. Here, we systematically study the cycle's steady-state behavior and its response to time-varying stimuli. We demonstrate that the cycle can actually operate in four different regimes, each with its specific input-output characteristics. These results are obtained using the total quasi-steady-state approximation, which is more generally valid than the typically used Michaelis-Menten approximation for enzymatic reactions. We invoke experimental data that suggest the possibility of signaling cycles operating in one of the new regimes. We then consider the cycle's dynamic behavior, which has so far been relatively neglected. We demonstrate that the intrinsic architecture of the cycles makes them act--in all four regimes--as tunable low-pass filters, filtering out high-frequency fluctuations or noise in signals and environmental cues. Moreover, the cutoff frequency can be adjusted by the cell. Numerical simulations show that our analytical results hold well even for noise of large amplitude. We suggest that noise filtering and tunability make signaling cycles versatile components of more elaborate cell-signaling pathways.

  19. Increasing the Signal to Noise Ratio in a Chemistry Laboratory ...

    African Journals Online (AJOL)

    If the signal to noise ratio is too low, it can obscure the 'chemical message' which the lecturer is trying to convey. This study reports on an action research driven attempt to improve on a Hess's Law experiment, well known in most first year curricula. Data collected in 2000 indicated that students struggled primarily because ...

  20. Multipath noise reduction spread spectrum signals

    Science.gov (United States)

    Meehan, Thomas K. (Inventor)

    1994-01-01

    The concepts of early-prompt delay tracking, multipath correction of early-prompt delay tracking from correlation shape, and carrier phase multipath correction are addressed. In early-prompt delay tracking, since multipath is always delayed with respect to the direct signals, the system derives phase and pseudorange observables from earlier correlation lags. In multipath correction of early-prompt delay tracking from correlation shape, the system looks for relative variations of amplitude across the code correlation function that do not match the predicted multipath-free code cross-correlation shape. The system then uses deviations from the multipath-free shape to infer the magnitude of multipath, and to generate corrections pseudorange observables. In carrier phase multipath correction, the system looks for variations of phase among plural early and prompt lags. The system uses the measured phase variations, along with the general principle that the multipath errors are larger for later lags, to infer the presence of multipath, and to generate corrections for carrier-phase observables.

  1. Signal-to-noise considerations for sky-subtracted CCD data

    Science.gov (United States)

    Newberry, Michael V.

    1991-01-01

    The standard equation for calculating the uncertainty of photometry obtained from CCDs does not correctly consider the random errors, or 'noise', introduced into observations by procedures used in reducing the data. This paper presents a thorough derivation of the theoretical error equation that considers the contributions from all internal noise sources in the signal-to-noise ratio (S/N) of a sky-subtracted image. A simplified version used for estimating the internal errors from empirical data is also derived. The propagation of noise through the data-reduction process is illustrated through a series of equations for the change in S/N that results from a variety of different operations performed on a CCD frame. Comparing these effects with the results expected for an observation made with an ideal detector suggests a number of ways to improve the precision of photometry through the practices employed in obtaining and reducing the observations.

  2. Intelligent Noise Removal from EMG Signal Using Focused Time-Lagged Recurrent Neural Network

    OpenAIRE

    Kale, S. N.; Dudul, S. V.

    2009-01-01

    Electromyography (EMG) signals can be used for clinical/biomedical application and modern human computer interaction. EMG signals acquire noise while traveling through tissue, inherent noise in electronics equipment, ambient noise, and so forth. ANN approach is studied for reduction of noise in EMG signal. In this paper, it is shown that Focused Time-Lagged Recurrent Neural Network (FTLRNN) can elegantly solve to reduce the noise from EMG signal. After rigorous computer simulations, authors d...

  3. Photonic microwave signals with zeptosecond level absolute timing noise

    CERN Document Server

    Xie, Xiaopeng; Nicolodi, Daniele; Giunta, Michele; Hänsel, Wolfgang; Lezius, Matthias; Joshi, Abhay; Datta, Shubhashish; Alexandre, Christophe; Lours, Michel; Tremblin, Pierre-Alain; Santarelli, Giorgio; Holzwarth, Ronald; Coq, Yann Le

    2016-01-01

    Photonic synthesis of radiofrequency revived the quest for unrivalled microwave purity by its seducing ability to convey the benefits of the optics to the microwave world. In this work, we perform a high-fidelity transfer of frequency stability between an optical reference and a microwave signal via a low-noise fiber-based frequency comb and cutting-edge photo-detection techniques. We demonstrate the generation of the purest microwave signal with a fractional frequency stability below 6.5 x 10^-16 at 1 s and a timing noise floor below 41 zs.Hz^-1/2 (phase noise below -173 dBc.Hz^-1 for a 12 GHz carrier). This outclasses existing sources and promises a new era for state-of-the-art microwave generation. The characterization is achieved by building two auxiliary low noise optoelectronic microwave reference and using a heterodyne cross-correlation scheme with lowermost detection noise. This unprecedented level of purity can impact domains such as radar systems, telecommunications and time-frequency metrology. Fur...

  4. The effects of noise on speech and warning signals

    Science.gov (United States)

    Suter, Alice H.

    1989-06-01

    To assess the effects of noise on speech communication it is necessary to examine certain characteristics of the speech signal. Speech level can be measured by a variety of methods, none of which has yet been standardized, and it should be kept in mind that vocal effort increases with background noise level and with different types of activity. Noise and filtering commonly degrade the speech signal, especially as it is transmitted through communications systems. Intelligibility is also adversely affected by distance, reverberation, and monaural listening. Communication systems currently in use may cause strain and delays on the part of the listener, but there are many possibilities for improvement. Individuals who need to communicate in noise may be subject to voice disorders. Shouted speech becomes progressively less intelligible at high voice levels, but improvements can be realized when talkers use clear speech. Tolerable listening levels are lower for negative than for positive S/Ns, and comfortable listening levels should be at a S/N of at least 5 dB, and preferably above 10 dB. Popular methods to predict speech intelligibility in noise include the Articulation Index, Speech Interference Level, Speech Transmission Index, and the sound level meter's A-weighting network. This report describes these methods, discussing certain advantages and disadvantages of each, and shows their interrelations.

  5. Theory of amplitude quantization of random signals

    OpenAIRE

    Knyshev, I. P.

    2008-01-01

    Conditions of ideal amplitude quantization of random signal with exact restoration of two-dimension probability density distribution function are defined. Interrelation of time discretization interval and amplitude quantization is shown. As an example transformation of normal random process is considered.

  6. Random noise characterization on the carrying capacities of a ...

    African Journals Online (AJOL)

    We have utilised the technique of a numerical simulation to study the impact of environmental random noise on the carrying capacities of a mathematical model of ... some sort of a sustainable mitigation strategy that is capable of providing a long term solution to the impact of crude oil pollution on the Ogoni ecosystem.

  7. Nonlinear transfer of signal and noise correlations in cortical networks.

    Science.gov (United States)

    Lyamzin, Dmitry R; Barnes, Samuel J; Donato, Roberta; Garcia-Lazaro, Jose A; Keck, Tara; Lesica, Nicholas A

    2015-05-27

    Signal and noise correlations, a prominent feature of cortical activity, reflect the structure and function of networks during sensory processing. However, in addition to reflecting network properties, correlations are also shaped by intrinsic neuronal mechanisms. Here we show that spike threshold transforms correlations by creating nonlinear interactions between signal and noise inputs; even when input noise correlation is constant, spiking noise correlation varies with both the strength and correlation of signal inputs. We characterize these effects systematically in vitro in mice and demonstrate their impact on sensory processing in vivo in gerbils. We also find that the effects of nonlinear correlation transfer on cortical responses are stronger in the synchronized state than in the desynchronized state, and show that they can be reproduced and understood in a model with a simple threshold nonlinearity. Since these effects arise from an intrinsic neuronal property, they are likely to be present across sensory systems and, thus, our results are a critical step toward a general understanding of how correlated spiking relates to the structure and function of cortical networks. Copyright © 2015 Lyamzin et al.

  8. Photonic microwave signals with zeptosecond-level absolute timing noise

    Science.gov (United States)

    Xie, Xiaopeng; Bouchand, Romain; Nicolodi, Daniele; Giunta, Michele; Hänsel, Wolfgang; Lezius, Matthias; Joshi, Abhay; Datta, Shubhashish; Alexandre, Christophe; Lours, Michel; Tremblin, Pierre-Alain; Santarelli, Giorgio; Holzwarth, Ronald; Le Coq, Yann

    2017-01-01

    Photonic synthesis of radiofrequency (RF) waveforms revived the quest for unrivalled microwave purity because of its ability to convey the benefits of optics to the microwave world. In this work, we perform a high-fidelity transfer of frequency stability between an optical reference and a microwave signal via a low-noise fibre-based frequency comb and cutting-edge photodetection techniques. We demonstrate the generation of the purest microwave signal with a fractional frequency stability below 6.5 × 10-16 at 1 s and a timing noise floor below 41 zs Hz-1/2 (phase noise below -173 dBc Hz-1 for a 12 GHz carrier). This outperforms existing sources and promises a new era for state-of-the-art microwave generation. The characterization is achieved through a heterodyne cross-correlation scheme with the lowermost detection noise. This unprecedented level of purity can impact domains such as radar systems, telecommunications and time-frequency metrology. The measurement methods developed here can benefit the characterization of a broad range of signals.

  9. Stochastic model for detection of signals in noise

    Science.gov (United States)

    Klein, Stanley A.; Levi, Dennis M.

    2010-01-01

    Fifty years ago Birdsall, Tanner, and colleagues made rapid progress in developing signal detection theory into a powerful psychophysical tool. One of their major insights was the utility of adding external noise to the signals of interest. These methods have been enhanced in recent years by the addition of multipass and classification-image methods for opening up the black box. There remain a number of as yet unresolved issues. In particular, Birdsall developed a theorem that large amounts of external input noise can linearize nonlinear systems, and Tanner conjectured, with mathematical backup, that what had been previously thought of as a nonlinear system could actually be a linear system with uncertainty. Recent findings, both experimental and theoretical, have validated Birdsall’s theorem and Tanner’s conjecture. However, there have also been experimental and theoretical findings with the opposite outcome. In this paper we present new data and simulations in an attempt to sort out these issues. Our simulations and experiments plus data from others show that Birdsall’s theorem is quite robust. We argue that uncertainty can serve as an explanation for violations of Birdsall’s linearization by noise and also for reports of stochastic resonance. In addition, we modify present models to better handle detection of signals with both noise and pedestal backgrounds. PMID:19884912

  10. On signal design by the R sub 0 criterion for non-white Gaussian noise channels

    Science.gov (United States)

    Bordelon, D. L.

    1976-01-01

    The use of the R sub 0 criterion for modulation system design is investigated for channels with non-white Gaussian noise. A signal space representation of the waveform channel is developed, and the cut-off rate R sub 0 for vector channels with additive nonwhite Gaussian noise and unquantized demodulation is derived. When the signal unput to the channel is a continuous random vector, maximization of R sub 0 with constrained average signal energy leads to a water-filling interpretation of optimal energy distribution in signal space. The necessary condition for a finite signal set to maximize R sub 0 with constrained energy and an equally likely probability assignment of signal vectors is presented, and an algorithm is outlined for numerically computing the optimum signal set. A necessary condition on a constrained energy, finite signal set is found which maximizes a Taylor series approximation of R sub 0. This signal set is compared with the finite signal set which has the water-filling average energy distribution.

  11. A correlation polarimeter for noise-like signals. [optimum estimation of linearly polarized electromagnetic wave

    Science.gov (United States)

    Ohlson, J. E.

    1976-01-01

    Optimum estimation (tracking) of the polarization plane of a linearly polarized electromagnetic wave is determined when the signal is a narrow-band Gaussian random process with a polarization plane angle which is also a Gaussian random process. This model is compared to previous work and is applicable to space communication. The estimator performs a correlation operation similar to an amplitude-comparison monopulse angle tracker, giving the name correlation polarimeter. Under large signal-to-noise ratio (SNR), the estimator is causal. Performance of the causal correlation polarimeter is evaluated for arbitrary SNR. Optimum precorrelation filtering is determined. With low SNR, the performance of this system is far better than that of previously developed systems. Practical implementation is discussed. A scheme is given to reduce the effect of linearly polarized noise.

  12. Signal processing method and system for noise removal and signal extraction

    Science.gov (United States)

    Fu, Chi Yung; Petrich, Loren

    2009-04-14

    A signal processing method and system combining smooth level wavelet pre-processing together with artificial neural networks all in the wavelet domain for signal denoising and extraction. Upon receiving a signal corrupted with noise, an n-level decomposition of the signal is performed using a discrete wavelet transform to produce a smooth component and a rough component for each decomposition level. The n.sup.th level smooth component is then inputted into a corresponding neural network pre-trained to filter out noise in that component by pattern recognition in the wavelet domain. Additional rough components, beginning at the highest level, may also be retained and inputted into corresponding neural networks pre-trained to filter out noise in those components also by pattern recognition in the wavelet domain. In any case, an inverse discrete wavelet transform is performed on the combined output from all the neural networks to recover a clean signal back in the time domain.

  13. Unsupervised reduction of random noise in complex data by a row-specific, sorted principal component-guided method

    Directory of Open Access Journals (Sweden)

    Katagiri Fumiaki

    2008-11-01

    Full Text Available Abstract Background Large biological data sets, such as expression profiles, benefit from reduction of random noise. Principal component (PC analysis has been used for this purpose, but it tends to remove small features as well as random noise. Results We interpreted the PCs as a mere signal-rich coordinate system and sorted the squared PC-coordinates of each row in descending order. The sorted squared PC-coordinates were compared with the distribution of the ordered squared random noise, and PC-coordinates for insignificant contributions were treated as random noise and nullified. The processed data were transformed back to the initial coordinates as noise-reduced data. To increase the sensitivity of signal capture and reduce the effects of stochastic noise, this procedure was applied to multiple small subsets of rows randomly sampled from a large data set, and the results corresponding to each row of the data set from multiple subsets were averaged. We call this procedure Row-specific, Sorted PRincipal component-guided Noise Reduction (RSPR-NR. Robust performance of RSPR-NR, measured by noise reduction and retention of small features, was demonstrated using simulated data sets. Furthermore, when applied to an actual expression profile data set, RSPR-NR preferentially increased the correlations between genes that share the same Gene Ontology terms, strongly suggesting reduction of random noise in the data set. Conclusion RSPR-NR is a robust random noise reduction method that retains small features well. It should be useful in improving the quality of large biological data sets.

  14. Open quantum random walk in terms of quantum Bernoulli noise

    Science.gov (United States)

    Wang, Caishi; Wang, Ce; Ren, Suling; Tang, Yuling

    2018-03-01

    In this paper, we introduce an open quantum random walk, which we call the QBN-based open walk, by means of quantum Bernoulli noise, and study its properties from a random walk point of view. We prove that, with the localized ground state as its initial state, the QBN-based open walk has the same limit probability distribution as the classical random walk. We also show that the probability distributions of the QBN-based open walk include those of the unitary quantum walk recently introduced by Wang and Ye (Quantum Inf Process 15:1897-1908, 2016) as a special case.

  15. Invisible noise obscures visible signal in insect motion detection.

    Science.gov (United States)

    Tarawneh, Ghaith; Nityananda, Vivek; Rosner, Ronny; Errington, Steven; Herbert, William; Cumming, Bruce G; Read, Jenny C A; Serrano-Pedraza, Ignacio

    2017-06-14

    The motion energy model is the standard account of motion detection in animals from beetles to humans. Despite this common basis, we show here that a difference in the early stages of visual processing between mammals and insects leads this model to make radically different behavioural predictions. In insects, early filtering is spatially lowpass, which makes the surprising prediction that motion detection can be impaired by "invisible" noise, i.e. noise at a spatial frequency that elicits no response when presented on its own as a signal. We confirm this prediction using the optomotor response of praying mantis Sphodromantis lineola. This does not occur in mammals, where spatially bandpass early filtering means that linear systems techniques, such as deriving channel sensitivity from masking functions, remain approximately valid. Counter-intuitive effects such as masking by invisible noise may occur in neural circuits wherever a nonlinearity is followed by a difference operation.

  16. A Stochastic Simulation Framework for the Prediction of Strategic Noise Mapping and Occupational Noise Exposure Using the Random Walk Approach

    Science.gov (United States)

    Haron, Zaiton; Bakar, Suhaimi Abu; Dimon, Mohamad Ngasri

    2015-01-01

    Strategic noise mapping provides important information for noise impact assessment and noise abatement. However, producing reliable strategic noise mapping in a dynamic, complex working environment is difficult. This study proposes the implementation of the random walk approach as a new stochastic technique to simulate noise mapping and to predict the noise exposure level in a workplace. A stochastic simulation framework and software, namely RW-eNMS, were developed to facilitate the random walk approach in noise mapping prediction. This framework considers the randomness and complexity of machinery operation and noise emission levels. Also, it assesses the impact of noise on the workers and the surrounding environment. For data validation, three case studies were conducted to check the accuracy of the prediction data and to determine the efficiency and effectiveness of this approach. The results showed high accuracy of prediction results together with a majority of absolute differences of less than 2 dBA; also, the predicted noise doses were mostly in the range of measurement. Therefore, the random walk approach was effective in dealing with environmental noises. It could predict strategic noise mapping to facilitate noise monitoring and noise control in the workplaces. PMID:25875019

  17. Random telegraph noise analysis in AlOx/WOy resistive switching memories

    Science.gov (United States)

    Zhang, Ye; Wu, Huaqiang; Wu, Minghao; Deng, Ning; Yu, Zhiping; Zhang, Jinyu; Qian, He

    2014-03-01

    In this Letter, the origins of current fluctuations of Al/AlOx/WOy/W bilayer resistive random access memory (RRAM) devices are investigated through detailed noise analysis. Random telegraph noise (RTN) measurements were performed on RRAMs with three different resistance states. An obvious RTN signal with 40.7% amplitude difference was found at high resistance state, and the trapping/de-trapping process leading to the RTN signal was studied in detail by extracting the trap energy from energy diagram. For median and low resistance states, the resistance fluctuations were 34.0% and 0.3%, respectively. To further study the RTN characteristics, the normalized power spectral density (PSD) was analyzed. It is found that, for one dominant-trap caused RTN phenomena, the normalized noise PSD behaves as 1/f 2 on the high resistance state; while for median and low resistance states, the noise follows 1/f rule, suggesting that the current fluctuations are associated with the envelop of multiple RTNs caused by traps located near/in the conductive filament. Based on the noise analyses in time and frequency domains, a conduction mechanism is proposed to describe the trap effects on the current fluctuations of different resistance states.

  18. Listening to the noise: random fluctuations reveal gene network parameters

    Energy Technology Data Exchange (ETDEWEB)

    Munsky, Brian [Los Alamos National Laboratory; Khammash, Mustafa [UCSB

    2009-01-01

    The cellular environment is abuzz with noise. The origin of this noise is attributed to the inherent random motion of reacting molecules that take part in gene expression and post expression interactions. In this noisy environment, clonal populations of cells exhibit cell-to-cell variability that frequently manifests as significant phenotypic differences within the cellular population. The stochastic fluctuations in cellular constituents induced by noise can be measured and their statistics quantified. We show that these random fluctuations carry within them valuable information about the underlying genetic network. Far from being a nuisance, the ever-present cellular noise acts as a rich source of excitation that, when processed through a gene network, carries its distinctive fingerprint that encodes a wealth of information about that network. We demonstrate that in some cases the analysis of these random fluctuations enables the full identification of network parameters, including those that may otherwise be difficult to measure. This establishes a potentially powerful approach for the identification of gene networks and offers a new window into the workings of these networks.

  19. Human Evoked Cortical Activity to Signal-to-Noise Ratio and Absolute Signal Level

    Science.gov (United States)

    Billings, Curtis J.; Tremblay, Kelly L.; Stecker, G. Christopher; Tolin, Wendy M.

    2009-01-01

    The purpose of this study was to determine the effect of signal level and signal-to-noise ratio (SNR) on the latency and amplitude of evoked cortical activity to further our understanding of how the human central auditory system encodes signals in noise. Cortical auditory evoked potentials (CAEPs) were recorded from 15 young normal-hearing adults in response to a 1000 Hz tone presented at two tone levels in quiet and while continuous background noise levels were varied in five equivalent SNR steps. These 12 conditions were used to determine the effects of signal level and SNR level on CAEP components P1, N1, P2, and N2. Based on prior signal-in-noise experiments conducted in animals, we hypothesized that SNR, would be a key contributor to human CAEP characteristics. As hypothesized, amplitude increased and latency decreased with increasing SNR; in addition, there was no main effect of tone level across the two signal levels tested (60 and 75 dB SPL). Morphology of the P1-N1-P2 complex was driven primarily by SNR, highlighting the importance of noise when recording CAEPs. Results are discussed in terms of the current interest in recording CAEPs in hearing aid users. PMID:19364526

  20. Peak signal-to-noise ratio revisited: Is simple beautiful?

    DEFF Research Database (Denmark)

    Korhonen, Jari; You, Junyong

    2012-01-01

    Heavy criticism has been directed against using peak signal-to-noise ratio (PSNR) as a full reference quality metric for digitally processed images and video, since many studies have shown a weak correlation between subjective quality scores and the respective PSNR values. In this paper, we show...... quality models known from the literature. Therefore, the use of PSNR may be justified for comparative quality assessment with fixed content....

  1. Noise and signal modeling of various VCSEL structures

    OpenAIRE

    Rissons, Angélique; Perchoux, Julien; Mollier, Jean-Claude; Grabherr, Martin

    2004-01-01

    Current evolution in Datacoms and Gigabit Ethernet have made 850nm Vertical Cavity Surface Emitting Lasers(VCSEL) the most important and promising emitter. Numerous different structures have been growth, to obtain bestcurrent confinement and then to control the emitted light modal behavior. We have developed a small signal equivalent electrical model of VCSEL including Bragg reflectors, active area, chip connection and noise behavior. Easy tointegrate with classical software for circuit studi...

  2. Performance Analysis of Recurrence Matrix Statistics for the Detection of Deterministic Signals in Noise

    National Research Council Canada - National Science Library

    Michalowicz, Joseph V; Nichols, Jonathan M; Bucholtz, Frank

    2008-01-01

    Understanding the limitations to detecting deterministic signals in the presence of noise, especially additive, white Gaussian noise, is of importance for the design of LPI systems and anti-LPI signal defense...

  3. Linear signal noise summer accurately determines and controls S/N ratio

    Science.gov (United States)

    Sundry, J. L.

    1966-01-01

    Linear signal noise summer precisely controls the relative power levels of signal and noise, and mixes them linearly in accurately known ratios. The S/N ratio accuracy and stability are greatly improved by this technique and are attained simultaneously.

  4. Lateral line canal morphology and signal to noise ratio

    Science.gov (United States)

    Klein, Adrian; Herzog, Hendrik; Bleckmann, Horst

    2011-04-01

    The lateral line system of fish is important for many behaviors, including spatial orientation, prey detection, shoaling, intra specific communication and entraining. The smallest sensory unit of the lateral line is the neuromast that occurs free standing on the skin and in fluid filled canals. With aid of the lateral line fish perceive minute water motions. In their natural habitat fish are not only faced with biotic water motion but also with the abiotic fluctuations caused by various inanimate sources. The detection of meaningful signals is crucial for survival, and therefore animals should be able to separate meaningful signals from noise. Fishes live in various habitats (e.g. in still water or in running water). Therefore it is not surprising that the number and distribution of neuromasts as well as canal dimension, canal shape and canal branching patterns differ among fish species. We studied how lateral line canal parameters influence the filter properties of lateral line canals. To do so we exposed artificial lateral line canals, equipped with artificial neuromasts (sensors), to the vortex street shed by a submerged cylinder and to air bubble noise. We found that certain canal parameters significantly can enhance the signal to noise ratio.

  5. Acoustics of fish shelters: background noise and signal-to-noise ratio.

    Science.gov (United States)

    Lugli, Marco

    2014-12-01

    Fish shelters (flat stones, shells, artificial covers, etc., with a hollow beneath) increase the sound pressure levels of low frequency sounds (signal-to-noise ratio (SNR) in the nest. Background noise amplification by the shelter was examined under both laboratory (stones and shells) and field (stones) conditions, and the SNR of tones inside the nest cavity was measured by performing acoustic tests on stones in the stream. Stone and shell shelters amplify the background noise pressure levels inside the cavity with comparable gains and at similar frequencies of an active sound source. Inside the cavity of stream stones, the mean SNR of tones increased significantly below 125 Hz and peaked at 65 Hz (+10 dB). Implications for fish acoustic communication inside nest enclosures are discussed.

  6. Signal-to-Noise Ratio Analysis of a Phase-Sensitive Voltmeter for Electrical Impedance Tomography.

    Science.gov (United States)

    Murphy, Ethan K; Takhti, Mohammad; Skinner, Joseph; Halter, Ryan J; Odame, Kofi

    2017-04-01

    In this paper, thorough analysis along with mathematical derivations of the matched filter for a voltmeter used in electrical impedance tomography systems are presented. The effect of the random noise in the system prior to the matched filter, generated by other components, are considered. Employing the presented equations allow system/circuit designers to find the maximum tolerable noise prior to the matched filter that leads to the target signal-to-noise ratio (SNR) of the voltmeter, without having to over-design internal components. A practical model was developed that should fall within 2 dB and 5 dB of the median SNR measurements of signal amplitude and phase, respectively. In order to validate our claims, simulation and experimental measurements have been performed with an analog-to-digital converter (ADC) followed by a digital matched filter, while the noise of the whole system was modeled as the input referred at the ADC input. The input signal was contaminated by a known value of additive white Gaussian noise (AWGN) noise, and the noise level was swept from 3% to 75% of the least significant bit (LSB) of the ADC. Differences between experimental and both simulated and analytical SNR values were less than 0.59 and 0.35 dB for RMS values ≥ 20% of an LSB and less than 1.45 and 2.58 dB for RMS values circuit designers in EIT, and a more accurate error analysis that was previously missing in EIT literature.

  7. STUDY ON DE-NOISING METHODS FOR SOIL COMPRESSIVE STRESS SIGNAL DURING VIBRATION COMPACTION

    Directory of Open Access Journals (Sweden)

    Qingzhe Zhang

    2017-12-01

    Full Text Available The compressive stress signal of soil during vibration compaction is an unstable and transient saltation signal accompanied by broadband noise, and the spectra of the signal and noise always overlap. To extract the ideal original signal from noisy data, this paper studies several signal de-noising methods such as low-pass filtering, multi-resolution wavelet transform, spectrum subtraction and independent component analysis. Experiments show that the traditional low-pass filter is only applicable when the spectra of the signal and noise can be separated in the frequency domain. The multi-resolution wavelet transform can decompose the signal into different frequency bands and remove the noise efficiently by extracting useful the frequency band of the signal, but this method is not reliable when the signal to noise ratio (SNR is low. Spectrum subtraction can remove strong background noise with stationary statistical characteristics even if the noise level is high and the spectrum of the signal overlaps with that of the noise. Independent component analysis can extract weak signals which are combined with heavy noise and can separate the noise from signal effectively when the independent channel hypothesis holds. These de-noising methods are of great importance for further analysing vibration signals in engineering.

  8. Signal-to-noise ratio losses in full spectrum combining of signals with a downconverted subcarrier

    Science.gov (United States)

    Feria, Y.; Statman, J.

    1993-01-01

    This article presents the results of the signal-to-noise ratio loss in the process of full spectrum combining of signals with a downconverted subcarrier under imperfect conditions. These imperfect conditions not only include the misalignment of the carrier, the subcarrier, and the symbols, but they also include the nonideal filtering in the subcarrier downconversion process, the cutoff of the data bandwidth, and the distortion in signal waveform.

  9. Random Number Simulations Reveal How Random Noise Affects the Measurements and Graphical Portrayals of Self-Assessed Competency

    Directory of Open Access Journals (Sweden)

    Edward Nuhfer

    2016-01-01

    Full Text Available Self-assessment measures of competency are blends of an authentic self-assessment signal that researchers seek to measure and random disorder or "noise" that accompanies that signal. In this study, we use random number simulations to explore how random noise affects critical aspects of self-assessment investigations: reliability, correlation, critical sample size, and the graphical representations of self-assessment data. We show that graphical conventions common in the self-assessment literature introduce artifacts that invite misinterpretation. Troublesome conventions include: (y minus x vs. (x scatterplots; (y minus x vs. (x column graphs aggregated as quantiles; line charts that display data aggregated as quantiles; and some histograms. Graphical conventions that generate minimal artifacts include scatterplots with a best-fit line that depict (y vs. (x measures (self-assessed competence vs. measured competence plotted by individual participant scores, and (y vs. (x scatterplots of collective average measures of all participants plotted item-by-item. This last graphic convention attenuates noise and improves the definition of the signal. To provide relevant comparisons across varied graphical conventions, we use a single dataset derived from paired measures of 1154 participants' self-assessed competence and demonstrated competence in science literacy. Our results show that different numerical approaches employed in investigating and describing self-assessment accuracy are not equally valid. By modeling this dataset with random numbers, we show how recognizing the varied expressions of randomness in self-assessment data can improve the validity of numeracy-based descriptions of self-assessment.

  10. The effect of signal noise on the remote sensing of Foliar biochemical concentration

    Science.gov (United States)

    Smith, Geoffrey M.; Curran, Paul J.

    1993-01-01

    Spectral measurements made using an imaging spectrometer contain systematic and random noise, while the former can be corrected the latter remains a source of error in the remotely sensed signal. A number of investigators have tried to determine the signal-to-noise-ratio (SNR) of the instrument, or the resultant imagery. However, the level of noise at which spectra are too noisy to be useful is not usually determined. The first attempt was by Goetz and Calvin, who suggested that the depth of the absorption feature should be at least an order of magnitude greater than the noise and more recently Dekker suggested a SNR of around 600:1 was required in visible/near infrared wavelengths to measure a 1/gl change in chlorophyll a concentration water. The wide range of applications of imaging spectroscopy make it difficult to set SNR specifications as they are dependent on a number of factors, one of the most important being reflectance of a particular target. For example, the SNR of imagery for vegetated targets is relatively low simply because vegetation has a relatively low level of reflectance. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) is being used to estimate the concentration of biochemicals within vegetation canopies. This paper reports a study undertaken to identify first, wavebands that were highly correlated with foliar biochemical concentration and second, to determine how sensitive these correlations were to sensor noise.

  11. Maximum likelihood estimation of signal-to-noise ratio and combiner weight

    Science.gov (United States)

    Kalson, S.; Dolinar, S. J.

    1986-01-01

    An algorithm for estimating signal to noise ratio and combiner weight parameters for a discrete time series is presented. The algorithm is based upon the joint maximum likelihood estimate of the signal and noise power. The discrete-time series are the sufficient statistics obtained after matched filtering of a biphase modulated signal in additive white Gaussian noise, before maximum likelihood decoding is performed.

  12. Motor noise is rich signal in autism research and pharmacological treatments.

    Science.gov (United States)

    Torres, E B; Denisova, K

    2016-11-21

    The human body is in constant motion, from every breath that we take, to every visibly purposeful action that we perform. Remaining completely still on command is a major achievement as involuntary fluctuations in our motions are difficult to keep under control. Here we examine the noise-to-signal ratio of micro-movements present in time-series of head motions extracted from resting-state functional magnetic resonance imaging scans in 1048 participants. These included individuals with autism spectrum disorders (ASD) and healthy-controls in shared data from the Autism Brain Imaging Data Exchange (ABIDE) and the Attention-Deficit Hyperactivity Disorder (ADHD-200) databases. We find excess noise and randomness in the ASD cases, suggesting an uncertain motor-feedback signal. A power-law emerged describing an orderly relation between the dispersion and shape of the probability distribution functions best describing the stochastic properties under consideration with respect to intelligence quotient (IQ-scores). In ASD, deleterious patterns of noise are consistently exacerbated with the presence of secondary (comorbid) neuropsychiatric diagnoses, lower verbal and performance intelligence, and autism severity. Importantly, such patterns in ASD are present whether or not the participant takes psychotropic medication. These data unambiguously establish specific noise-to-signal levels of head micro-movements as a biologically informed core feature of ASD.

  13. Gene expression noise and robustness of signaling in bacterial chemotaxis

    Science.gov (United States)

    Sourjik, Victor

    2006-03-01

    Stochastic variations in protein levels are one of the major sources of noise affecting biological networks. Since networks involved in gene regulation and signal transduction must have a defined input-output relation, they can be expected to have undergone evolution for inherent robustness against such perturbations. Chemotaxis of a model bacterium Escherichia coli -- a mechanism that allows motile cells to follow chemical gradients in the environment -- has one of the most thoroughly studied signaling networks in biology. Combining theoretical and experimental analysis, we investigated robustness of this network to intercellular variations in expression levels of chemotaxis proteins, or gene expression noise. The single-cell levels of different chemotaxis proteins showed strong co-variation, which implies that stochastic variations in transcriptional control are the main source of the noise. We demonstrated that the pathway is indeed robust to such kind of perturbations by testing the effect of concerted overexpression of all chemotaxis proteins on the pathway output. Using computer simulations and theoretical analysis, we determined the network design features responsible for robustness and showed that the experimentally established network in Escherichia coli has the smallest topology that is sufficiently robust to allow a majority of the individuals in a population to maintain a correct pathway output.

  14. Limiting characteristics of a superconducting quantum interferometer. I - Signal characteristic. II - Signal-to-noise ratio

    Science.gov (United States)

    Butikov, E. I.; Feofilov, S. P.

    1980-11-01

    An investigation is presented of a dc SQUID with two Josephson junctions in a system for measuring small changes of a magnetic field with low-frequency modulation of the magnetic flux. Idealized theoretical signal characteristics are obtained, and their dependence on the modes of operation and parameters of the SQUID are studied. These characteristics are used to determine the minimum detectable changes of magnetic flux characterizing the limiting sensitivity of the SQUID. The spectral density of thermal noise is obtained for the low-frequency range which constrains the limiting sensitivity; the signal/noise ratio is studied as a function of the operating modes and parameters of the SQUID.

  15. Defining Biological Networks for Noise Buffering and Signaling Sensitivity Using Approximate Bayesian Computation

    Directory of Open Access Journals (Sweden)

    Shuqiang Wang

    2014-01-01

    Full Text Available Reliable information processing in cells requires high sensitivity to changes in the input signal but low sensitivity to random fluctuations in the transmitted signal. There are often many alternative biological circuits qualifying for this biological function. Distinguishing theses biological models and finding the most suitable one are essential, as such model ranking, by experimental evidence, will help to judge the support of the working hypotheses forming each model. Here, we employ the approximate Bayesian computation (ABC method based on sequential Monte Carlo (SMC to search for biological circuits that can maintain signaling sensitivity while minimizing noise propagation, focusing on cases where the noise is characterized by rapid fluctuations. By systematically analyzing three-component circuits, we rank these biological circuits and identify three-basic-biological-motif buffering noise while maintaining sensitivity to long-term changes in input signals. We discuss in detail a particular implementation in control of nutrient homeostasis in yeast. The principal component analysis of the posterior provides insight into the nature of the reaction between nodes.

  16. Study of improving signal-noise ratio for fluorescence channel

    Science.gov (United States)

    Wang, Guoqing; Li, Xin; Lou, Yue; Chen, Dong; Zhao, Xin; Wang, Ran; Yan, Debao; Zhao, Qi

    2017-10-01

    Laser-induced fluorescence(LIFS), which is one of most effective discrimination methods to identify the material at the molecular level by inducing fluorescence spectrum, has been popularized for its fast and accurate probe's results. According to the research, violet laser or ultraviolet laser is always used as excitation light source. While, There is no atmospheric window for violet laser and ultraviolet laser, causing laser attenuation along its propagation path. What's worse, as the laser reaching sample, part of the light is reflected. That is, excitation laser really react on sample to produce fluorescence is very poor, leading to weak fluorescence mingled with the background light collected by LIFS' processing unit, when it used outdoor. In order to spread LIFS to remote probing under the complex background, study of improving signal-noise ratio for fluorescence channel is a meaningful work. Enhancing the fluorescence intensity and inhibiting background light both can improve fluorescence' signal-noise ratio. In this article, three different approaches of inhibiting background light are discussed to improve the signal-noise ratio of LIFS. The first method is increasing fluorescence excitation area in the proportion of LIFS' collecting field by expanding laser beam, if the collecting filed is fixed. The second one is changing field angle base to accommodate laser divergence angle. The third one is setting a very narrow gating circuit to control acquisition circuit, which is shortly open only when fluorescence arriving. At some level, these methods all can reduce the background light. But after discussion, the third one is best with adding gating acquisition circuit to acquisition circuit instead of changing light path, which is effective and economic.

  17. Enhanced signal-to-noise ratio estimation for tropospheric lidar channels

    Science.gov (United States)

    Saeed, Umar; Barragan, Rubén; Rocadenbosch, Francesc

    2016-04-01

    This works combines the fields of tropospheric lidar remote sensing and signal processing to come up with a robust signal-to-noise ratio (SNR) estimator apt for elastic and Raman channels. The estimator uses a combined low-pass / high-pass filtering scheme along with high-order statistics (kurtosis) to estimate the range-dependent signal and noise components with minimum distortion. While low-pass filtering is used to estimate the range-dependent signal level, high-pass filtering is used to estimate the noise component with minimum distortion. From this noise component estimate (a random realization) the noise level (e.g., variance) is computed as a function of range along with error bars. The minimum-distortion specification determines the optimal cut-off de-noising filter frequency and, in turn, the spatial resolution of the SNR estimation algorithm. The proposed SNR estimator has a much wider dynamic range of operation than well-known classic SNR estimation techniques, in which the SNR is directly computed from the mean and standard deviation of the measured noise-corrupted lidar signal along successive adjacent range intervals and where the spatial resolution is just a subjective input from the user's side. Aligned with ACTRIS (http://www.actris.net) WP on "optimization of the processing chain and Single-Calculus Chain (SCC)" the proposed topic is of application to assess lidar reception channel performance and confidence on the detected atmospheric morphology (e.g., cloud base and top, and location of aerosol layers). The SNR algorithm is tested against the classic SNR estimation approach using test-bed synthetic lidar data modelling the UPC multi-spectral lidar. Towards this end, the Nd:YAG UPC elastic-Raman lidar provides aerosol channels in the near-infrared (1064 nm), visible (532 nm), and ultra-violet (355 nm) as well as aerosol Raman and water-vapour channels with fairly varying SNR levels. The SNR estimator is also used to compare SNR levels between

  18. Signal-to-noise ratio of the MEG signal after preprocessing.

    Science.gov (United States)

    Gonzalez-Moreno, Alicia; Aurtenetxe, Sara; Lopez-Garcia, Maria-Eugenia; del Pozo, Francisco; Maestu, Fernando; Nevado, Angel

    2014-01-30

    Magnetoencephalography (MEG) provides a direct measure of brain activity with high combined spatiotemporal resolution. Preprocessing is necessary to reduce contributions from environmental interference and biological noise. The effect on the signal-to-noise ratio of different preprocessing techniques is evaluated. The signal-to-noise ratio (SNR) was defined as the ratio between the mean signal amplitude (evoked field) and the standard error of the mean over trials. Recordings from 26 subjects obtained during and event-related visual paradigm with an Elekta MEG scanner were employed. Two methods were considered as first-step noise reduction: Signal Space Separation and temporal Signal Space Separation, which decompose the signal into components with origin inside and outside the head. Both algorithm increased the SNR by approximately 100%. Epoch-based methods, aimed at identifying and rejecting epochs containing eye blinks, muscular artifacts and sensor jumps provided an SNR improvement of 5-10%. Decomposition methods evaluated were independent component analysis (ICA) and second-order blind identification (SOBI). The increase in SNR was of about 36% with ICA and 33% with SOBI. No previous systematic evaluation of the effect of the typical preprocessing steps in the SNR of the MEG signal has been performed. The application of either SSS or tSSS is mandatory in Elekta systems. No significant differences were found between the two. While epoch-based methods have been routinely applied the less often considered decomposition methods were clearly superior and therefore their use seems advisable. Copyright © 2013 Elsevier B.V. All rights reserved.

  19. The concept of signal-to-noise ratio in the modulation domain and speech intelligibility

    NARCIS (Netherlands)

    Dubbelboer, F.; Houtgast, T.

    2008-01-01

    A new concept is proposed that relates to intelligibility of speech in noise. The concept combines traditional estimations of signal-to-noise ratios (S/N) with elements from the modulation transfer function model, which results in the definition of the signal-to-noise ratio in the modulation domain:

  20. Digital Construction and Characterization of Noise-Like Spread Spectrum Signals

    Science.gov (United States)

    2016-11-01

    Digital Construction and Characterization of Noise -like Spread Spectrum Signals Donald C. Buzanowski II, Frederick J. Block, Thomas C. Royster MIT...Lincoln Laboratory Lexington, MA 02420 Abstract—A new method for generating digital noise -like spread spectrum signals is proposed. A standard binary...employing signals that are noise -like (e.g., [1]). Direct sequence spread spectrum (DSSS) signals provide benefits such as protection against jamming, low

  1. Seismic random noise removal by delay-compensation time-frequency peak filtering

    Science.gov (United States)

    Yu, Pengjun; Li, Yue; Lin, Hongbo; Wu, Ning

    2017-06-01

    Over the past decade, there has been an increasing awareness of time-frequency peak filtering (TFPF) due to its outstanding performance in suppressing non-stationary and strong seismic random noise. The traditional approach based on time-windowing achieves local linearity and meets the unbiased estimation. However, the traditional TFPF (including the improved algorithms with alterable window lengths) could hardly relieve the contradiction between removing noise and recovering the seismic signal, and this situation is more obvious in wave crests and troughs, even for alterable window lengths (WL). To improve the efficiency of the algorithm, the following TFPF in the time-space domain is applied, such as in the Radon domain and radial trace domain. The time-space transforms obtain a reduced-frequency input to reduce the TFPF error and stretch the desired signal along a certain direction, therefore the time-space development brings an improvement by both enhancing reflection events and attenuating noise. It still proves limited in application because the direction should be matched as a straight line or quadratic curve. As a result, waveform distortion and false seismic events may appear when processing the complex stratum record. The main emphasis in this article is placed on the time-space TFPF applicable expansion. The reconstructed signal in delay-compensation TFPF, which is generated according to the similarity among the reflection events, overcomes the limitation of the direction curve fitting. Moreover, the reconstructed signal just meets the TFPF linearity unbiased estimation and integrates signal reservation with noise attenuation. Experiments on both the synthetic model and field data indicate that delay-compensation TFPF has a better performance over the conventional filtering algorithms.

  2. DS/LPI autocorrelation detection in noise plus random-tone interference. [Direct Sequence Low-Probabilty of Intercept

    Science.gov (United States)

    Hinedi, S.; Polydoros, A.

    1988-01-01

    The authors present and analyze a frequency-noncoherent two-lag autocorrelation statistic for the wideband detection of random BPSK signals in noise-plus-random-multitone interference. It is shown that this detector is quite robust to the presence or absence of interference and its specific parameter values, contrary to the case of an energy detector. The rule assumes knowledge of the data rate and the active scenario under H0. It is concluded that the real-time autocorrelation domain and its samples (lags) are a viable approach for detecting random signals in dense environments.

  3. Noise and signal interference in optical fiber transmission systems an optimum design approach

    CERN Document Server

    Bottacchi, Stefano

    2008-01-01

    A comprehensive reference to noise and signal interference in optical fiber communications Noise and Signal Interference in Optical Fiber Transmission Systems is a compendium on specific topics within optical fiber transmission and the optimization process of the system design. It offers comprehensive treatment of noise and intersymbol interference (ISI) components affecting optical fiber communications systems, containing coverage on noise from the light source, the fiber and the receiver. The ISI is modeled with a statistical approach, leading to new useful computational m

  4. Clinical evaluation of signal-to-noise ratio-based noise reduction in Nucleus® cochlear implant recipients.

    Science.gov (United States)

    Dawson, Pam W; Mauger, Stefan J; Hersbach, Adam A

    2011-01-01

    The aim of this study was to investigate whether a real-time noise reduction algorithm provided speech perception benefit for Cochlear™ Nucleus® cochlear implant recipients in the laboratory. The noise reduction algorithm attenuated masker-dominated channels. It estimated the signal-to-noise ratio of each channel on a short-term basis from a single microphone input, using a recursive minimum statistics method. In this clinical evaluation, the algorithm was implemented in two programs (noise reduction programs 1 [NR1] and 2 [NR2]), which differed in their level of noise reduction. These programs used advanced combination encoder (ACE™) channel selection and were compared with ACE without noise reduction in 13 experienced cochlear implant subjects. An adaptive speech reception threshold (SRT) test provided the signal-to-noise ratio for 50% sentence intelligibility in three different types of noises: speech-weighted, cocktail party, and street-side city noise. In all three noise types, mean SRTs for both NR programs were significantly better than those for ACE. The greatest improvement occurred for speech-weighted noise; the SRT benefit over ACE was 1.77 dB for NR1 and 2.14 dB for NR2. There were no significant differences in speech perception scores between the two NR programs. Subjects reported no degradation in sound quality with the experimental programs. The noise reduction algorithm was successful in improving sentence perception in speech-weighted noise, as well as in more dynamic types of background noise. The algorithm is currently being trialed in a behind-the-ear processor for take-home use.

  5. Noise Reduction Effect of Multiple-Sampling-Based Signal-Readout Circuits for Ultra-Low Noise CMOS Image Sensors

    Science.gov (United States)

    Kawahito, Shoji; Seo, Min-Woong

    2016-01-01

    This paper discusses the noise reduction effect of multiple-sampling-based signal readout circuits for implementing ultra-low-noise image sensors. The correlated multiple sampling (CMS) technique has recently become an important technology for high-gain column readout circuits in low-noise CMOS image sensors (CISs). This paper reveals how the column CMS circuits, together with a pixel having a high-conversion-gain charge detector and low-noise transistor, realizes deep sub-electron read noise levels based on the analysis of noise components in the signal readout chain from a pixel to the column analog-to-digital converter (ADC). The noise measurement results of experimental CISs are compared with the noise analysis and the effect of noise reduction to the sampling number is discussed at the deep sub-electron level. Images taken with three CMS gains of two, 16, and 128 show distinct advantage of image contrast for the gain of 128 (noise(median): 0.29 e−rms) when compared with the CMS gain of two (2.4 e−rms), or 16 (1.1 e−rms). PMID:27827972

  6. Noise Reduction Effect of Multiple-Sampling-Based Signal-Readout Circuits for Ultra-Low Noise CMOS Image Sensors

    Directory of Open Access Journals (Sweden)

    Shoji Kawahito

    2016-11-01

    Full Text Available This paper discusses the noise reduction effect of multiple-sampling-based signal readout circuits for implementing ultra-low-noise image sensors. The correlated multiple sampling (CMS technique has recently become an important technology for high-gain column readout circuits in low-noise CMOS image sensors (CISs. This paper reveals how the column CMS circuits, together with a pixel having a high-conversion-gain charge detector and low-noise transistor, realizes deep sub-electron read noise levels based on the analysis of noise components in the signal readout chain from a pixel to the column analog-to-digital converter (ADC. The noise measurement results of experimental CISs are compared with the noise analysis and the effect of noise reduction to the sampling number is discussed at the deep sub-electron level. Images taken with three CMS gains of two, 16, and 128 show distinct advantage of image contrast for the gain of 128 (noise(median: 0.29 e−rms when compared with the CMS gain of two (2.4 e−rms, or 16 (1.1 e−rms.

  7. Quasi-Coherent Noise Jamming to LFM Radar Based on Pseudo-random Sequence Phase-modulation

    Directory of Open Access Journals (Sweden)

    N. Tai

    2015-12-01

    Full Text Available A novel quasi-coherent noise jamming method is proposed against linear frequency modulation (LFM signal and pulse compression radar. Based on the structure of digital radio frequency memory (DRFM, the jamming signal is acquired by the pseudo-random sequence phase-modulation of sampled radar signal. The characteristic of jamming signal in time domain and frequency domain is analyzed in detail. Results of ambiguity function indicate that the blanket jamming effect along the range direction will be formed when jamming signal passes through the matched filter. By flexible controlling the parameters of interrupted-sampling pulse and pseudo-random sequence, different covering distances and jamming effects will be achieved. When the jamming power is equivalent, this jamming obtains higher process gain compared with non-coherent jamming. The jamming signal enhances the detection threshold and the real target avoids being detected. Simulation results and circuit engineering implementation validate that the jamming signal covers real target effectively.

  8. Sensitivity of offset and onset cortical auditory evoked potentials to signals in noise.

    Science.gov (United States)

    Baltzell, Lucas S; Billings, Curtis J

    2014-02-01

    The purpose of this study was to determine the effects of SNR and signal level on the offset response of the cortical auditory evoked potential (CAEP). Successful listening often depends on how well the auditory system can extract target signals from competing background noise. Both signal onsets and offsets are encoded neurally and contribute to successful listening in noise. Neural onset responses to signals in noise demonstrate a strong sensitivity to signal-to-noise ratio (SNR) rather than signal level; however, the sensitivity of neural offset responses to these cues is not known. We analyzed the offset response from two previously published datasets for which only the onset response was reported. For both datasets, CAEPs were recorded from young normal-hearing adults in response to a 1000-Hz tone. For the first dataset, tones were presented at seven different signal levels without background noise, while the second dataset varied both signal level and SNR. Offset responses demonstrated sensitivity to absolute signal level in quiet, SNR, and to absolute signal level in noise. Offset sensitivity to signal level when presented in noise contrasts with previously published onset results. This sensitivity suggests a potential clinical measure of cortical encoding of signal level in noise.

  9. Signal-to-noise ratio of Singer product apertures

    Science.gov (United States)

    Shutler, Paul M. E.; Byard, Kevin

    2017-09-01

    Formulae for the signal-to-noise ratio (SNR) of Singer product apertures are derived, allowing optimal Singer product apertures to be identified, and the CPU time required to decode them is quantified. This allows a systematic comparison to be made of the performance of Singer product apertures against both conventionally wrapped Singer apertures, and also conventional product apertures such as square uniformly redundant arrays. For very large images, equivalently for images at very high resolution, the SNR of Singer product apertures is asymptotically as good as the best conventional apertures, but Singer product apertures decode faster than any conventional aperture by at least a factor of ten for image sizes up to several megapixels. These theoretical predictions are verified using numerical simulations, demonstrating that coded aperture video is for the first time a realistic possibility.

  10. A Dynamical System Exhibits High Signal-to-noise Ratio Gain by Stochastic Resonance

    Science.gov (United States)

    Makra, Peter; Gingl, Zoltan

    2003-05-01

    On the basis of mixed-signal simulations, we demonstrate that signal-to-noise ratio (SNR) gains much greater than unity can be obtained in the double-well potential through stochastic resonance (SR) with a symmetric periodic pulse train as deterministic and Gaussian white noise as random excitation. We also show that significant SNR improvement is possible in this system even for a sub-threshold sinusoid input if, instead of the commonly used narrow-band SNR, we apply an equally simple but much more realistic wide-band SNR definition. Using the latter result as an argument, we draw attention to the fact that the choice of the measure to reflect signal quality is critical with regard to the extent of signal improvement observed, and urge reconsideration of the practice prevalent in SR studies that most often the narrow-band SNR is used to characterise SR. Finally, we pose some questions concerning the possibilities of applying SNR improvement in practical set-ups.

  11. Practical signal-dependent noise parameter estimation from a single noisy image.

    Science.gov (United States)

    Liu, Xinhao; Tanaka, Masayuki; Okutomi, Masatoshi

    2014-10-01

    The additive white Gaussian noise is widely assumed in many image processing algorithms. However, in the real world, the noise from actual cameras is better modeled as signal-dependent noise (SDN). In this paper, we focus on the SDN model and propose an algorithm to automatically estimate its parameters from a single noisy image. The proposed algorithm identifies the noise level function of signal-dependent noise assuming the generalized signal-dependent noise model and is also applicable to the Poisson-Gaussian noise model. The accuracy is achieved by improved estimation of local mean and local noise variance from the selected low-rank patches. We evaluate the proposed algorithm with both synthetic and real noisy images. Experiments demonstrate that the proposed estimation algorithm outperforms the state-of-the-art methods.

  12. A genetically encoded, high-signal-to-noise maltose sensor

    Energy Technology Data Exchange (ETDEWEB)

    Marvin, Jonathan S.; Schreiter, Eric R.; Echevarría, Ileabett M.; Looger, Loren L. (Puerto Rico); (HHMI)

    2012-10-23

    We describe the generation of a family of high-signal-to-noise single-wavelength genetically encoded indicators for maltose. This was achieved by insertion of circularly permuted fluorescent proteins into a bacterial periplasmic binding protein (PBP), Escherichia coli maltodextrin-binding protein, resulting in a four-color family of maltose indicators. The sensors were iteratively optimized to have sufficient brightness and maltose-dependent fluorescence increases for imaging, under both one- and two-photon illumination. We demonstrate that maltose affinity of the sensors can be tuned in a fashion largely independent of the fluorescent readout mechanism. Using literature mutations, the binding specificity could be altered to moderate sucrose preference, but with a significant loss of affinity. We use the soluble sensors in individual E. coli bacteria to observe rapid maltose transport across the plasma membrane, and membrane fusion versions of the sensors on mammalian cells to visualize the addition of maltose to extracellular media. The PBP superfamily includes scaffolds specific for a number of analytes whose visualization would be critical to the reverse engineering of complex systems such as neural networks, biosynthetic pathways, and signal transduction cascades. We expect the methodology outlined here to be useful in the development of indicators for many such analytes.

  13. MOSFET LF noise under Large Signal Excitation: Measurement, Modelling and Application

    NARCIS (Netherlands)

    van der Wel, A.P.

    2005-01-01

    Regarding LF noise in MOSFETs, it is noted that the MOSFET is a surface channel device. Both n and p-channel devices exhibit similar low frequency (LF) noise behaviour that can be explained by a carrier number fluctuation model (section 3.5). LF noise in MOSFETs is predominantly caused by Random

  14. Estimation of signal and noise for a whole-body photon counting research CT system.

    Science.gov (United States)

    Li, Zhoubo; Leng, Shuai; Yu, Zhicong; Kappler, Stephen; McCollough, Cynthia H

    2016-02-01

    Photon-counting CT (PCCT) may yield potential value for many clinical applications due to its relative immunity to electronic noise, increased geometric efficiency relative to current scintillating detectors, and the ability to resolve energy information about the detected photons. However, there are a large number of parameters that require optimization, particularly the energy thresholds configurations. Fast and accurate estimation of signal and noise in PCCT can benefit the optimization of acquisition parameters for specific diagnostic tasks. Based on the acquisition parameters and detector response of our research PCCT system, we derived mathematical models for both signal and noise. The signal model took the tube spectrum, beam filtration, object attenuation, water beam hardening, and detector response into account. The noise model considered the relationship between noise and radiation dose, as well as the propagation of noise as threshold data are subtracted to yield energy bin data. To determine the absolute noise value, a noise look-up table (LUT) was acquired using a limited number of calibration scans. The noise estimation algorithm then used the noise LUT to estimate noise for scans with a variety of combination of energy thresholds, dose levels, and object attenuation. Validation of the estimation algorithms was performed on our whole-body research PCCT system using semi-anthropomorphic water phantoms and solutions of calcium and iodine. The algorithms achieved accurate estimation of signal and noise for a variety of scanning parameter combinations. The proposed method can be used to optimize energy thresholds configuration for many clinical applications of PCCT.

  15. Noise-benefit forbidden-interval theorems for threshold signal detectors based on cross correlations

    Science.gov (United States)

    Mitaim, Sanya; Kosko, Bart

    2014-11-01

    We show that the main forbidden interval theorems of stochastic resonance hold for a correlation performance measure. Earlier theorems held only for performance measures based on mutual information or the probability of error detection. Forbidden interval theorems ensure that a threshold signal detector benefits from deliberately added noise if the average noise does not lie in an interval that depends on the threshold value. We first show that this result holds for correlation for all finite-variance noise and for all forms of infinite-variance stable noise. A second forbidden-interval theorem gives necessary and sufficient conditions for a local noise benefit in a bipolar signal system when the noise comes from a location-scale family. A third theorem gives a general condition for a local noise benefit for arbitrary signals with finite second moments and for location-scale noise. This result also extends forbidden intervals to forbidden bands of parameters. A fourth theorem gives necessary and sufficient conditions for a local noise benefit when both the independent signal and noise are normal. A final theorem derives necessary and sufficient conditions for forbidden bands when using arrays of threshold detectors for arbitrary signals and location-scale noise.

  16. Spectral characterization of jitter, shimmer, and additive noise in synthetically generated voice signals.

    Science.gov (United States)

    Murphy, P J

    2000-02-01

    Alteration of the harmonic structure in voice source spectra, taken over at least two periods of the waveform, may occur due to the presence of fundamental frequency (f0) perturbation, amplitude perturbation, additive noise, or changes within the glottal source signal itself. In order to make accurate inferences regarding glottal-flow dynamics or perceptual evaluations based on spectral measurements taken from the acoustic speech waveform, investigation of the spectral features of each aperiodic component is required. Based on a heuristic development involving a consideration of the partial sum of the Fourier series taken for two periods of a jittered, shimmered, and (additive, random) noise-contaminated signal, the corresponding spectral characteristics are hypothesized. Subsequent to this, the Fourier series coefficients are calculated for the two periods in order to test the hypotheses. Definite spectral differences are found for each aperiodic component; based on these findings differential quantitative spectral measurements are suggested. Further supportive evidence is obtained through use of Fourier transform and periodogram-averaged calculations. The analysis is carried out on synthetically generated glottal-pulse waveforms and on radiated speech waveforms. A discussion of the results is given in terms of voice aperiodicity in general and in terms of their implication for future studies involving human voice signals.

  17. Orthogonal matching pursuit algorithm and power line noise suppression of magnetotelluric signal

    Science.gov (United States)

    Li, Guang; Tang, Jingtian

    2017-11-01

    Power-line noise is mainly comes from power systems and has become one of the most common noises during the acquisition of magnetotelluric (MT) signal, its components including a fundamental frequency signal and a lot of odd harmonics. There are trap circuits designed in most of the acquisition instruments to separate these noise, however, the fundamental frequency of the power line noise will fluctuate with the changing of load current, but the center frequency of the trap circuits are fixed, hence the MT data are still seriously disturbed by the power line noise. To mitigate the disturbance of power line noise, a novel denoising method was proposed based on orthogonal matching pursuit (OMP) algorithm. Semisynthetic experiments and real data obtained from Lu-Zong ore-concentration district illustrate that the proposed method can effectively suppress the power line noise while remain the useful MT signal, the apparent resistivity and phase curves are greatly improved over previous.

  18. Seismic random noise attenuation by time-frequency peak filtering based on joint time-frequency distribution

    Science.gov (United States)

    Zhang, Chao; Lin, Hong-bo; Li, Yue; Yang, Bao-jun

    2013-09-01

    Time-Frequency Peak Filtering (TFPF) is an effective method to eliminate pervasive random noise when seismic signals are analyzed. In conventional TFPF, the pseudo Wigner-Ville distribution (PWVD) is used for estimating instantaneous frequency (IF), but is sensitive to noise interferences that mask the borderline between signal and noise and detract the energy concentration on the IF curve. This leads to the deviation of the peaks of the pseudo Wigner-Ville distribution from the instantaneous frequency, which is the cause of undesirable lateral oscillations as well as of amplitude attenuation of the highly varying seismic signal, and ultimately of the biased seismic signal. With the purpose to overcome greatly these drawbacks and increase the signal-to-noise ratio, we propose in this paper a TFPF refinement that is based upon the joint time-frequency distribution (JTFD). The joint time-frequency distribution is obtained by the combination of the PWVD and smooth PWVD (SPWVD). First we use SPWVD to generate a broad time-frequency area of the signal. Then this area is filtered with a step function to remove some divergent time-frequency points. Finally, the joint time-frequency distribution JTFD is obtained from PWVD weighted by this filtered distribution. The objective pursued with all these operations is to reduce the effects of the interferences and enhance the energy concentration around the IF of the signal in the time-frequency domain. Experiments with synthetic and real seismic data demonstrate that TFPF based on the joint time-frequency distribution can effectively suppress strong random noise and preserve events of interest.

  19. Filtering and thresholding the analytic signal envelope in order to improve peak and spike noise reduction in EEG signals.

    Science.gov (United States)

    Melia, Umberto; Clariá, Francesc; Vallverdú, Montserrat; Caminal, Pere

    2014-04-01

    To remove peak and spike artifacts in biological time series has represented a hard challenge in the last decades. Several methods have been implemented mainly based on adaptive filtering in order to solve this problem. This work presents an algorithm for removing peak and spike artifacts based on a threshold built on the analytic signal envelope. The algorithm was tested on simulated and real EEG signals that contain peak and spike artifacts with random amplitude and frequency occurrence. The performance of the filter was compared with commonly used adaptive filters. Three indexes were used for testing the performance of the filters: Correlation coefficient (ρ), mean of coherence function (C), and rate of absolute error (RAE). All these indexes were calculated between filtered signal and original signal without noise. It was found that the new proposed filter was able to reduce the amplitude of peak and spike artifacts with ρ>0.85, C>0.8, and RAELMS adaptive filter (ρ1). Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

  20. Detecting impact signal in mechanical fault diagnosis under chaotic and Gaussian background noise

    Science.gov (United States)

    Hu, Jinfeng; Duan, Jie; Chen, Zhuo; Li, Huiyong; Xie, Julan; Chen, Hanwen

    2018-01-01

    In actual fault diagnosis, useful information is often submerged in heavy noise, and the feature information is difficult to extract. Traditional methods, such like stochastic resonance (SR), which using noise to enhance weak signals instead of suppressing noise, failed in chaotic background. Neural network, which use reference sequence to estimate and reconstruct the background noise, failed in white Gaussian noise. To solve these problems, a novel weak signal detection method aimed at the problem of detecting impact signal buried under heavy chaotic and Gaussian background noise is proposed. First, the proposed method obtains the virtual reference sequence by constructing the Hankel data matrix. Then an M-order optimal FIR filter is designed, which can minimize the output power of background noise and pass the weak periodic signal undistorted. Finally, detection and reconstruction of the weak periodic signal are achieved from the output SBNR (signal to background noise ratio). The simulation shows, compared with the stochastic resonance (SR) method, the proposed method can detect the weak periodic signal in chaotic noise background while stochastic resonance (SR) method cannot. Compared with the neural network method, (a) the proposed method does not need a reference sequence while neural network method needs one; (b) the proposed method can detect the weak periodic signal in white Gaussian noise background while the neural network method fails, in chaotic noise background, the proposed method can detect the weak periodic signal under a lower SBNR (about 8-17 dB lower) than the neural network method; (c) the proposed method can reconstruct the weak periodic signal precisely.

  1. Error Bounds Due to Random Noise in Cylindrical Near-Field Measurements

    OpenAIRE

    Romeu Robert, Jordi; Jofre Roca, Lluís

    1991-01-01

    The far field errors due to near field random noise are statistically bounded when performing cylindrical near to far field transform. In this communication, the far field noise variance it is expressed as a function of the measurement parameters and the near field noise variance. Peer Reviewed

  2. CORTICAL ENCODING OF SIGNALS IN NOISE: EFFECTS OF STIMULUS TYPE AND RECORDING PARADIGM

    Science.gov (United States)

    Billings, Curtis J.; Bennett, Keri O.; Molis, Michelle R.; Leek, Marjorie R.

    2010-01-01

    Objectives Perception-in-noise deficits have been demonstrated across many populations and listening conditions. Many factors contribute to successful perception of auditory stimuli in noise, including neural encoding in the central auditory system. Physiological measures such as cortical auditory evoked potentials can provide a view of neural encoding at the level of the cortex that may inform our understanding of listeners’ abilities to perceive signals in the presence of background noise. In order to understand signal-in-noise neural encoding better, we set out to determine the effect of signal type, noise type, and evoking paradigm on the P1-N1-P2 complex. Design Tones and speech stimuli were presented to nine individuals in quiet, and in three background noise types: continuous speech spectrum noise, interrupted speech spectrum noise, and four-talker babble at a signal-to-noise ratio of −3 dB. In separate sessions, cortical auditory evoked potentials were evoked by a passive homogenous paradigm (single repeating stimulus) and an active oddball paradigm. Results The results for the N1 component indicated significant effects of signal type, noise type, and evoking paradigm. While components P1 and P2 also had significant main effects of these variables, only P2 demonstrated significant interactions among these variables. Conclusions Signal type, noise type, and evoking paradigm all must be carefully considered when interpreting signal-in-noise evoked potentials. Furthermore, these data confirm the possible usefulness of CAEPs as an aid to understanding perception-in-noise deficits. PMID:20890206

  3. Visual signal detection in structured backgrounds. II. Effects of contrast gain control, background variations, and white noise

    Science.gov (United States)

    Eckstein, M. P.; Ahumada, A. J. Jr; Watson, A. B.

    1997-01-01

    Studies of visual detection of a signal superimposed on one of two identical backgrounds show performance degradation when the background has high contrast and is similar in spatial frequency and/or orientation to the signal. To account for this finding, models include a contrast gain control mechanism that pools activity across spatial frequency, orientation and space to inhibit (divisively) the response of the receptor sensitive to the signal. In tasks in which the observer has to detect a known signal added to one of M different backgrounds grounds due to added visual noise, the main sources of degradation are the stochastic noise in the image and the suboptimal visual processing. We investigate how these two sources of degradation (contrast gain control and variations in the background) interact in a task in which the signal is embedded in one of M locations in a complex spatially varying background (structured background). We use backgrounds extracted from patient digital medical images. To isolate effects of the fixed deterministic background (the contrast gain control) from the effects of the background variations, we conduct detection experiments with three different background conditions: (1) uniform background, (2) a repeated sample of structured background, and (3) different samples of structured background. Results show that human visual detection degrades from the uniform background condition to the repeated background condition and degrades even further in the different backgrounds condition. These results suggest that both the contrast gain control mechanism and the background random variations degrade human performance in detection of a signal in a complex, spatially varying background. A filter model and added white noise are used to generate estimates of sampling efficiencies, an equivalent internal noise, an equivalent contrast-gain-control-induced noise, and an equivalent noise due to the variations in the structured background.

  4. Signal to noise quantification of regional climate projections

    Science.gov (United States)

    Li, S.; Rupp, D. E.; Mote, P.

    2016-12-01

    One of the biggest challenges in interpreting climate model outputs for impacts studies and adaptation planning is understanding the sources of disagreement among models (which is often used imperfectly as a stand-in for system uncertainty). Internal variability is a primary source of uncertainty in climate projections, especially for precipitation, for which models disagree about even the sign of changes in large areas like the continental US. Taking advantage of a large initial-condition ensemble of regional climate simulations, this study quantifies the magnitude of changes forced by increasing greenhouse gas concentrations relative to internal variability. Results come from a large initial-condition ensemble of regional climate model simulations generated by weather@home, a citizen science computing platform, where the western United States climate was simulated for the recent past (1985-2014) and future (2030-2059) using a 25-km horizontal resolution regional climate model (HadRM3P) nested in global atmospheric model (HadAM3P). We quantify grid point level signal-to-noise not just in temperature and precipitation responses, but also the energy and moisture flux terms that are related to temperature and precipitation responses, to provide important insights regarding uncertainty in climate change projections at local and regional scales. These results will aid modelers in determining appropriate ensemble sizes for different climate variables and help users of climate model output with interpreting climate model projections.

  5. Modeling Signal-to-Noise Ratio of Otoacoustic Emissions in Workers Exposed to Different Industrial Noise Levels

    OpenAIRE

    Nassiri, Parvin; Zare, Sajad; Monazzam, Mohammad R.; Pourbakht, Akram; Azam, Kamal; Golmohammadi, Taghi

    2016-01-01

    Introduction: Noise is considered as the most common cause of harmful physical effects in the workplace. A sound that is generated from within the inner ear is known as an otoacoustic emission (OAE). Distortion-product otoacoustic emissions (DPOAEs) assess evoked emission and hearing capacity. The aim of this study was to assess the signal-to-noise ratio in different frequencies and at different times of the shift work in workers exposed to various levels of noise. It was also aimed to provid...

  6. Mittag-Leffler noise induced stochastic resonance in a generalized Langevin equation with random inherent frequency

    Science.gov (United States)

    He, Guitian; Guo, Dali; Tian, Yan; Li, Tiejun; Luo, Maokang

    2017-10-01

    The generalized stochastic resonance (GSR) and the bona fide stochastic resonance (SR) in a generalized Langevin equation driven by a periodic signal, multiplicative noise and Mittag-Leffler noise are extensively investigated. The expression of the frequency spectrum of the Mittag-Leffler noise is studied. Using the Shapiro-Loginov formula and Laplace transformation technique, the exact expressions of the output amplitude gain and the signal-to-noise ratio are obtained. The simulation results turn out that the output amplitude gain and the signal-to-noise ratio are non-monotonic functions of the characteristics of noise parameters and system parameters. Especially, the influence of the memory exponent and memory time of Mittag-Leffler noise could induce the GSR phenomenon. The influence of the driving frequency could induce the bona fide stochastic resonance. It is found that the system with fractional memory exponent could be more easily induced SR phenomenon than the system with integer memory exponent.

  7. Linking the sender to the receiver: vocal adjustments by bats to maintain signal detection in noise.

    Science.gov (United States)

    Luo, Jinhong; Goerlitz, Holger R; Brumm, Henrik; Wiegrebe, Lutz

    2015-12-22

    Short-term adjustments of signal characteristics allow animals to maintain reliable communication in noise. Noise-dependent vocal plasticity often involves simultaneous changes in multiple parameters. Here, we quantified for the first time the relative contributions of signal amplitude, duration, and redundancy for improving signal detectability in noise. To this end, we used a combination of behavioural experiments on pale spear-nosed bats (Phyllostomus discolor) and signal detection models. In response to increasing noise levels, all bats raised the amplitude of their echolocation calls by 1.8-7.9 dB (the Lombard effect). Bats also increased signal duration by 13%-85%, corresponding to an increase in detectability of 1.0-5.3 dB. Finally, in some noise conditions, bats increased signal redundancy by producing more call groups. Assuming optimal cognitive integration, this could result in a further detectability improvement by up to 4 dB. Our data show that while the main improvement in signal detectability was due to the Lombard effect, increasing signal duration and redundancy can also contribute markedly to improving signal detectability. Overall, our findings demonstrate that the observed adjustments of signal parameters in noise are matched to how these parameters are processed in the receiver's sensory system, thereby facilitating signal transmission in fluctuating environments.

  8. Mapping the signal-to-noise-ratios of cortical sources in magnetoencephalography and electroencephalography.

    Science.gov (United States)

    Goldenholz, Daniel M; Ahlfors, Seppo P; Hämäläinen, Matti S; Sharon, Dahlia; Ishitobi, Mamiko; Vaina, Lucia M; Stufflebeam, Steven M

    2009-04-01

    Although magnetoencephalography (MEG) and electroencephalography (EEG) have been available for decades, their relative merits are still debated. We examined regional differences in signal-to-noise-ratios (SNRs) of cortical sources in MEG and EEG. Data from four subjects were used to simulate focal and extended sources located on the cortical surface reconstructed from high-resolution magnetic resonance images. The SNR maps for MEG and EEG were found to be complementary. The SNR of deep sources was larger in EEG than in MEG, whereas the opposite was typically the case for superficial sources. Overall, the SNR maps were more uniform for EEG than for MEG. When using a noise model based on uniformly distributed random sources on the cortex, the SNR in MEG was found to be underestimated, compared with the maps obtained with noise estimated from actual recorded MEG and EEG data. With extended sources, the total area of cortex in which the SNR was higher in EEG than in MEG was larger than with focal sources. Clinically, SNR maps in a patient explained differential sensitivity of MEG and EEG in detecting epileptic activity. Our results emphasize the benefits of recording MEG and EEG simultaneously. 2008 Wiley-Liss, Inc.

  9. Cluster signal-to-noise analysis for evaluation of the information content in an image.

    Science.gov (United States)

    Weerawanich, Warangkana; Shimizu, Mayumi; Takeshita, Yohei; Okamura, Kazutoshi; Yoshida, Shoko; Yoshiura, Kazunori

    2018-01-01

    (1) To develop an observer-free method of analysing image quality related to the observer performance in the detection task and (2) to analyse observer behaviour patterns in the detection of small mass changes in cone-beam CT images. 13 observers detected holes in a Teflon phantom in cone-beam CT images. Using the same images, we developed a new method, cluster signal-to-noise analysis, to detect the holes by applying various cut-off values using ImageJ and reconstructing cluster signal-to-noise curves. We then evaluated the correlation between cluster signal-to-noise analysis and the observer performance test. We measured the background noise in each image to evaluate the relationship with false positive rates (FPRs) of the observers. Correlations between mean FPRs and intra- and interobserver variations were also evaluated. Moreover, we calculated true positive rates (TPRs) and accuracies from background noise and evaluated their correlations with TPRs from observers. Cluster signal-to-noise curves were derived in cluster signal-to-noise analysis. They yield the detection of signals (true holes) related to noise (false holes). This method correlated highly with the observer performance test (R2 = 0.9296). In noisy images, increasing background noise resulted in higher FPRs and larger intra- and interobserver variations. TPRs and accuracies calculated from background noise had high correlation with actual TPRs from observers; R2 was 0.9244 and 0.9338, respectively. Cluster signal-to-noise analysis can simulate the detection performance of observers and thus replace the observer performance test in the evaluation of image quality. Erroneous decision-making increased with increasing background noise.

  10. Noise affects the shape of female preference functions for acoustic signals.

    Science.gov (United States)

    Reichert, Michael S; Ronacher, Bernhard

    2015-02-01

    The shape of female mate preference functions influences the speed and direction of sexual signal evolution. However, the expression of female preferences is modulated by interactions between environmental conditions and the female's sensory processing system. Noise is an especially relevant environmental condition because it interferes directly with the neural processing of signals. Although noise is therefore likely a significant force in the evolution of communication systems, little is known about its effects on preference function shape. In the grasshopper Chorthippus biguttulus, female preferences for male calling song characteristics are likely to be affected by noise because its auditory system is sensitive to fine temporal details of songs. We measured female preference functions for variation in male song characteristics in several levels of masking noise and found strong effects of noise on preference function shape. The overall responsiveness to signals in noise generally decreased. Preference strength increased for some signal characteristics and decreased for others, largely corresponding to expectations based on neurophysiological studies of acoustic signal processing. These results suggest that different signal characteristics will be favored under different noise conditions, and thus that signal evolution may proceed differently depending on the extent and temporal patterning of environmental noise. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

  11. An analysis of noise reduction in variable reluctance motors using pulse position randomization

    Science.gov (United States)

    Smoot, Melissa C.

    1994-05-01

    The design and implementation of a control system to introduce randomization into the control of a variable reluctance motor (VRM) is presented. The goal is to reduce noise generated by radial vibrations of the stator. Motor phase commutation angles are dithered by 1 or 2 mechanical degrees to investigate the effect of randomization on acoustic noise. VRM commutation points are varied using a uniform probability density function and a 4 state Markov chain among other methods. The theory of VRM and inverter operation and a derivation of the major source of acoustic noise are developed. The experimental results show the effects of randomization. Uniform dithering and Markov chain dithering both tend to spread the noise spectrum, reducing peak noise components. No clear evidence is found to determine which is the optimum randomization scheme. The benefit of commutation angle randomization in reducing VRM loudness as perceived by humans is found to be questionable.

  12. Noise in Load Cell Signal in an Automatic Weighing System Based on a Belt Conveyor

    Directory of Open Access Journals (Sweden)

    Kyoo Nam Choi

    2017-01-01

    Full Text Available Noise in load cell signal in an automatic weighing system based on a belt conveyor has been examined experimentally in time and frequency domains to enhance signal quality. The noise frequency spectrum showed nonlinearly increasing multiple resonance peaks as speed increased. The noise reduction process using noise reduction algorithm, by sharply rejecting peak noise frequency component and afterward forming optimum pulse width ratio through filter slope control using selective switching of 6 LPF stages, was used for enhanced accuracy. The effectiveness of proposed method, controlling both cutoff frequency and slope of LPF, was evaluated by feeding 50 g test mass, and this noise reduction process showed better noise filtering with enhanced accuracy than fixed cutoff frequency control method. The ratio of top to bottom pulse width showed that LPF cutoff frequency above 5 Hz had the ratio above 50% up to 80 m/min speed range.

  13. Elevated cAMP improves signal-to-noise ratio in amphibian rod photoreceptors.

    Science.gov (United States)

    Astakhova, Luba A; Nikolaeva, Darya A; Fedotkina, Tamara V; Govardovskii, Victor I; Firsov, Michael L

    2017-07-03

    The absolute sensitivity of vertebrate retinas is set by a background noise, called dark noise, which originates from several different cell types and is generated by different molecular mechanisms. The major share of dark noise is produced by photoreceptors and consists of two components, discrete and continuous. Discrete noise is generated by spontaneous thermal activations of visual pigment. These events are undistinguishable from real single-photon responses (SPRs) and might be considered an equivalent of the signal. Continuous noise is produced by spontaneous fluctuations of the catalytic activity of the cGMP phosphodiesterase. This masks both SPR and spontaneous SPR-like responses. Circadian rhythms affect photoreceptors, among other systems by periodically increasing intracellular cAMP levels ([cAMP]in), which increases the size and changes the shape of SPRs. Here, we show that forskolin, a tool that increases [cAMP]in, affects the magnitude and frequency spectrum of the continuous and discrete components of dark noise in photoreceptors. By changing both components of rod signaling, the signal and the noise, cAMP is able to increase the photoreceptor signal-to-noise ratio by twofold. We propose that this results in a substantial improvement of signal detection, without compromising noise rejection, at the rod bipolar cell synapse. © 2017 Astakhova et al.

  14. De-noising methods for NMR logging echo signals based on wavelet transform

    Science.gov (United States)

    Xie, Ranhong; Wu, Youbin; Liu, Kang; Liu, Mi; Xiao, Lizhi

    2014-06-01

    The signal-to-noise ratio (SNR) of the echo signals in nuclear magnetic resonance (NMR) is one of the most important factors that affect the effective application of NMR logging. Wavelet transform can be used to remove the noise and improve the SNR of echo signals in NMR logging. This paper uses three de-noising methods to treat the NMR echo signals: modulus maxima, spatial correlation and wavelet threshold based on wavelet transform. The effects of the three methods in the noise reduction of NMR echo signals were compared by numerical simulation, core experiment and NMR logging data. The results show that while these three methods can all effectively improve the SNR of NMR echo signals and the NMR T2 inversion results, the most effective among them is the wavelet threshold method, which can obtain a higher SNR and provides more accurate formation porosity.

  15. Noise Correlation Effect on Detection: Signals in Equicorrelated or Autoregressive(1) Gaussian.

    Science.gov (United States)

    Kasasbeh, Hadi; Viswanathan, Ramanarayanan; Cao, Lei

    2017-07-01

    In this letter, we consider the effect of noise correlation on the error performance of binary hypothesis signal detection, when one of two deterministic signals is received in correlated Gaussian noise. For the likelihood ratio detection scheme, analytical performance results are derived for equicorrelated and autoregressive order one models. Although it is known previously that the best signal lies in the direction of eigenvector corresponding to the minimum eigenvalue of the noise covariance matrix, our investigation of the variation of mean signal-to-noise power ratio as a function of correlation parameter (i) shows how correlation leads to increased probability of error up to a point, beyond which monotonic decrease in error probability with increasing correlation is possible and (ii) provides a max-min signal design solution for the unknown correlation parameter case. Numerical results are also included for some specific signals.

  16. Improving detection range, signal-to-noise ratio, and measurement time through hyperentanglement

    Science.gov (United States)

    Smith, James F.

    2017-07-01

    An atmospheric imaging system based on quantum hyperentanglement has been developed. Hyper-entanglement can increase the maximum detection range of the system by more than a factor of 10, improve the signal-to-noise ratio (SNR) by more than a factor of 10,000, and decrease measurement time. Hyperentanglement refers to entanglement in more than one degree of freedom. A design for creating states hyperentangled in the degrees of freedom polarization, energy-time, orbital angular momentum (OAM), and the radial quantum number is examined. The design helps reduce propagation loss. Figures of merit related to generation and detection efficiencies, the SNR, signal to interference ratio, the measurement time, and phase estimation are provided in closed form. A formula describing how hyperentanglement greatly improves the maximum detection range of the system is derived. Hermite-Gaussian modes, Laguerre-Gaussian (LG) modes, OAM dependence of the LG modes, and mode conversion are discussed. Bell state generation and Bell state measurement, i.e., the ability to distinguish the various Bell states, is discussed. Mathematical and circuit representations of Bell state generation and the Bell state analyzer are provided. Signatures for unique detection of the various Bell states are developed. The formalism permits random noise and entangled or nonentangled sources of interference to be modeled.

  17. Reprint of 'Noise contributions to the fMRI signal: An Overview'.

    Science.gov (United States)

    Liu, Thomas T

    2017-07-01

    The ability to discriminate signal from noise plays a key role in the analysis and interpretation of functional magnetic resonance imaging (fMRI) measures of brain activity. Over the past two decades, a number of major sources of noise have been identified, including system-related instabilities, subject motion, and physiological fluctuations. This article reviews the characteristics of the various noise sources as well as the mechanisms through which they affect the fMRI signal. Approaches for distinguishing signal from noise and the associated challenges are also reviewed. These challenges reflect the fact that some noise sources, such as respiratory activity, are generated by the same underlying brain networks that give rise to functional signals that are of interest. Copyright © 2016 Elsevier Inc. All rights reserved.

  18. Signal-to-noise ratios in IUE low-dispersion spectra. II - Photometrically corrected images

    Science.gov (United States)

    Ayres, Thomas R.

    1993-01-01

    Photometrically corrected images from the IUE's two intensified vidicon cameras are used to explore the character of detector noise, and a protocol for the derivation of realistic noise models is proposed on the basis of available collections of UV-Flood calibration images. The incomplete removal of the pixel-to-pixel sensitivity pattern can lead to a factor-of-2 enhancement in apparent noise; even with good suppression of pixel granularity, the remaining random noise can exhibit saturation behavior which causes S/N to cease improving with increasing exposure. When all relevant effects are considered, underlying, 'pristine' noise models show virtually no dependence on spatial position.

  19. Alleviation of additional phase noise in fiber optical parametric amplifier based signal regenerator.

    Science.gov (United States)

    Jin, Lei; Xu, Bo; Yamashita, Shinji

    2012-11-19

    We theoretically and numerically explain the power saturation and the additional phase noise brought by the fiber optical parametric amplifier (FOPA). An equation to calculate an approximation to the saturated signal output power is presented. We also propose a scheme for alleviating the phase noise brought by the FOPA at the saturated state. In simulation, by controlling the decisive factor dispersion difference term Δk of the FOPA, amplitude-noise and additional phase noise reduction of quadrature phase shift keying (QPSK) based on the saturated FOPA is studied, which can provide promising performance to deal with PSK signals.

  20. Acceptance noise level: effects of the speech signal, babble, and listener language.

    Science.gov (United States)

    Shi, Lu-Feng; Azcona, Gabrielly; Buten, Lupe

    2015-04-01

    The acceptable noise level (ANL) measure has gained much research/clinical interest in recent years. The present study examined how the characteristics of the speech signal and the babble used in the measure may affect the ANL in listeners with different native languages. Fifteen English monolingual, 16 Russian-English bilingual, and 24 Spanish-English bilingual listeners participated. The ANL was obtained in eight conditions varying in the language of the signal (English and Spanish), language of the babble (English and Spanish), and number of talkers in the babble (4 and 12). Test conditions were randomized across listeners. The ANL for each condition was based on a minimum of two trials. Russian-English bilinguals yielded higher ANLs than other listeners; the intergroup difference of 4-5 dB was statistically and clinically significant. Spanish signals yielded significantly higher ANLs than English signals, but this difference of 0.5 dB was clinically negligible. The language and composition of the babble had a significant effect on Russian-English bilinguals, who yielded higher ANLs with the Spanish than English 12-talker babble. The above findings do not fully support the notion that the ANL is language- and population-independent. Clinicians should be aware of possible effects on ANL measures due to listeners' linguistic/cultural background.

  1. Estimation of signal and noise for a whole-body research photon-counting CT system.

    Science.gov (United States)

    Li, Zhoubo; Leng, Shuai; Yu, Zhicong; Kappler, Steffen; McCollough, Cynthia H

    2017-04-01

    Photon-counting detector CT has a large number of acquisition parameters that require optimization, particularly the energy threshold configurations. Fast and accurate estimation of both signal and noise in photon-counting CT (PCCT) images can facilitate such optimization. Using the detector response function of a research PCCT system, we derived mathematical models for both signal and noise estimation, taking into account beam spectrum and filtration, object attenuation, water beam hardening, detector response, radiation dose, energy thresholds, and the propagation of noise. To determine the absolute noise value, a noise lookup table (LUT) for all available energy thresholds was acquired using a number of calibration scans. The noise estimation algorithm then used the noise LUT to estimate noise for scans with a variety of combination of energy thresholds, dose levels, and object attenuations. Validation of the estimation algorithms was performed on a whole-body research PCCT system using semianthropomorphic water phantoms and solutions of calcium and iodine. Clinical feasibility of noise estimation was assessed with scans of a cadaver head and a living swine. The algorithms achieved accurate estimation of both signal and noise for a variety of scanning parameter combinations. Maximum discrepancies were below 15%, while most errors were below 5%.

  2. Compressed Sensing with Linear Correlation Between Signal and Measurement Noise

    DEFF Research Database (Denmark)

    Arildsen, Thomas; Larsen, Torben

    2014-01-01

    reconstruction algorithms, but is not known in existing literature. The proposed technique reduces reconstruction error considerably in the case of linearly correlated measurements and noise. Numerical experiments confirm the efficacy of the technique. The technique is demonstrated with application to low......-rate quantization of compressed measurements, which is known to introduce correlated noise, and improvements in reconstruction error compared to ordinary Basis Pursuit De-Noising of up to approximately 7 dB are observed for 1 bit/sample quantization. Furthermore, the proposed method is compared to Binary Iterative...

  3. MMSE-based algorithm for joint signal detection, channel and noise variance estimation for OFDM systems

    CERN Document Server

    Savaux, Vincent

    2014-01-01

    This book presents an algorithm for the detection of an orthogonal frequency division multiplexing (OFDM) signal in a cognitive radio context by means of a joint and iterative channel and noise estimation technique. Based on the minimum mean square criterion, it performs an accurate detection of a user in a frequency band, by achieving a quasi-optimal channel and noise variance estimation if the signal is present, and by estimating the noise level in the band if the signal is absent. Organized into three chapters, the first chapter provides the background against which the system model is pr

  4. Signal recognition by green treefrogs (Hyla cinerea) and Cope's gray treefrogs (Hyla chrysoscelis) in naturally fluctuating noise.

    Science.gov (United States)

    Vélez, Alejandro; Bee, Mark A

    2013-05-01

    This study tested three hypotheses about the ability of female frogs to exploit temporal fluctuations in the level of background noise to overcome the problem of recognizing male advertisement calls in noisy breeding choruses. Phonotaxis tests with green treefrogs (Hyla cinerea) and Cope's gray treefrogs (Hyla chrysoscelis) were used to measure thresholds for recognizing calls in the presence of noise maskers with (a) no level fluctuations, (b) random fluctuations, or level fluctuations characteristic of (c) conspecific choruses and (d) heterospecific choruses. The dip-listening hypothesis predicted lower signal recognition thresholds in the presence of fluctuating maskers compared with nonfluctuating maskers. Support for the dip-listening hypothesis was weak; only Cope's gray treefrogs experienced dip listening and only in the presence of randomly fluctuating maskers. The natural soundscapes advantage hypothesis predicted lower recognition thresholds when level fluctuations resembled those of natural soundscapes compared with artificial fluctuations. This hypothesis was rejected. In noise backgrounds with natural fluctuations, the species-specific advantage hypothesis predicted lower recognition thresholds when fluctuations resembled species-specific patterns of conspecific soundscapes. No evidence was found to support this hypothesis. These results corroborate previous findings showing that Cope's gray treefrogs, but not green treefrogs, experience dip listening under some noise conditions. Together, the results suggest level fluctuations in the soundscape of natural breeding choruses may present few dip-listening opportunities. The findings of this study provide little support for the hypothesis that receivers are adapted to exploit level fluctuations of natural soundscapes in recognizing communication signals.

  5. Unipolar pulse and bipolar noise testing of wideband signal noise conditioner (MC476-0132-0034)

    Science.gov (United States)

    Harris, J. E.

    1977-01-01

    Information is presented on performance characteristics of the shuttle orbiter wideband signal conditioner when subjected to special types of input signals. Design analysis of the signal flow path through the signal conditioning amplifier was performed followed by acutal testing of the amplifier with various signal inputs. Results indicate that the signal conditioner should perform acceptably if the shuttle orbiter flight vibration signal levels are in accord with preflight predictions.

  6. Cramer-Rao Bound for Gaussian Random Processes and Applications to Radar Processing of Atmospheric Signals

    Science.gov (United States)

    Frehlich, Rod

    1993-01-01

    Calculations of the exact Cramer-Rao Bound (CRB) for unbiased estimates of the mean frequency, signal power, and spectral width of Doppler radar/lidar signals (a Gaussian random process) are presented. Approximate CRB's are derived using the Discrete Fourier Transform (DFT). These approximate results are equal to the exact CRB when the DFT coefficients are mutually uncorrelated. Previous high SNR limits for CRB's are shown to be inaccurate because the discrete summations cannot be approximated with integration. The performance of an approximate maximum likelihood estimator for mean frequency approaches the exact CRB for moderate signal to noise ratio and moderate spectral width.

  7. Correlated and uncorrelated invisible temporal white noise alters mesopic rod signaling.

    Science.gov (United States)

    Hathibelagal, Amithavikram R; Feigl, Beatrix; Kremers, Jan; Zele, Andrew J

    2016-03-01

    We determined how rod signaling at mesopic light levels is altered by extrinsic temporal white noise that is correlated or uncorrelated with the activity of one (magnocellular, parvocellular, or koniocellular) postreceptoral pathway. Rod and cone photoreceptor excitations were independently controlled using a four-primary photostimulator. Psychometric (Weibull) functions were measured for incremental rod pulses (50 to 250 ms) in the presence (or absence; control) of perceptually invisible subthreshold extrinsic noise. Uncorrelated (rod) noise facilitates rod detection. Correlated postreceptoral pathway noise produces differential changes in rod detection thresholds and decreases the slope of the psychometric functions. We demonstrate that invisible extrinsic noise changes rod-signaling characteristics within the three retinogeniculate pathways at mesopic illumination depending on the temporal profile of the rod stimulus and the extrinsic noise type.

  8. IIR digital filter design for powerline noise cancellation of ECG signal using arduino platform

    Science.gov (United States)

    Rahmatillah, Akif; Ataulkarim

    2017-05-01

    Powerline noise has been one of significant noises of Electrocardiogram (ECG) signal measurement. This noise is characterized by a sinusoidal signal which has 50 Hz of noise and 0.3 mV of maximum amplitude. This paper describes the design of IIR Notch filter design to reject a 50 Hz power line noise. IIR filter coefficients were calculated using pole placement method with three variations of band stop cut off frequencies of (49-51)Hz, (48 - 52)Hz, and (47 - 53)Hz. The algorithm and coefficients of filter were embedded to Arduino DUE (ARM 32 bit microcontroller). IIR notch filter designed has been able to reject power line noise with average square of error value of 0.225 on (49-51) Hz filter design and 0.2831 on (48 - 52)Hz filter design.

  9. Optical Correlation of Images With Signal-Dependent Noise Using Constrained-Modulation Filter Devices

    Science.gov (United States)

    Downie, John D.

    1995-01-01

    Images with signal-dependent noise present challenges beyond those of images with additive white or colored signal-independent noise in terms of designing the optimal 4-f correlation filter that maximizes correlation-peak signal-to-noise ratio, or combinations of correlation-peak metrics. Determining the proper design becomes more difficult when the filter is to be implemented on a constrained-modulation spatial light modulator device. The design issues involved for updatable optical filters for images with signal-dependent film-grain noise and speckle noise are examined. It is shown that although design of the optimal linear filter in the Fourier domain is impossible for images with signal-dependent noise, proper nonlinear preprocessing of the images allows the application of previously developed design rules for optimal filters to be implemented on constrained-modulation devices. Thus the nonlinear preprocessing becomes necessary for correlation in optical systems with current spatial light modulator technology. These results are illustrated with computer simulations of images with signal-dependent noise correlated with binary-phase-only filters and ternary-phase-amplitude filters.

  10. Noise and Signal for Spectra of Intermittent Noiselike Emission

    Science.gov (United States)

    Gwinn, C. R.; Johnson, M. D.

    2011-05-01

    We show that intermittency of noiselike emission, after propagation through a scattering medium, affects the distribution of noise in the observed correlation function. Intermittency also affects correlation of noise among channels of the spectrum, but leaves the average spectrum, average correlation function, and distribution of noise among channels of the spectrum unchanged. Pulsars are examples of such sources: intermittent and affected by interstellar propagation. We assume that the source emits Gaussian white noise, modulated by a time envelope. Propagation convolves the resulting time series with an impulse-response function that represents effects of dispersion, scattering, and absorption. We assume that this propagation kernel is shorter than the time for an observer to accumulate a single spectrum. We show that rapidly varying intermittent emission tends to concentrate noise near the central lag of the correlation function. We derive mathematical expressions for this effect, in terms of the time envelope and the propagation kernel. We present examples, discuss effects of background noise, and compare our results with observations.

  11. Equalization-enhanced phase noise for coherent-detection systems using electronic digital signal processing.

    Science.gov (United States)

    Shieh, William; Ho, Keang-Po

    2008-09-29

    In coherent optical systems employing electronic digital signal processing, the fiber chromatic dispersion can be gracefully compensated in electronic domain without resorting to optical techniques. Unlike optical dispersion compensator, the electronic equalizer enhances the impairments from the laser phase noise. This equalization-enhanced phase noise (EEPN) imposes a tighter constraint on the receive laser phase noise for transmission systems with high symbol rate and large electronically-compensated chromatic dispersion.

  12. A low-noise low-power amplifier for implantable device for neural signal acquisition.

    Science.gov (United States)

    Li, Ming-Ze; Tang, Kea-Tiong

    2009-01-01

    This paper presents a low-noise low-power amplifier for implantable device for neural signal acquisition. By operating MOS transistors in the subthreshold region, smaller low-frequency noise and lower power consumption can be achieved. A low power, low-noise common-drain buffer and a low-noise, high-linearity, low pass filter are used for high frequency noise filtering. Post-layout simulation shows the input referred noise of the system is 2.19microVrms from 10Hz to 10 KHz, power consumption is 55.8microW, and the NEF is 2.53. The amplifier was fabricated using a TSMC 0.18microm 1P6M CMOS process. Simulation results show that this low-noise, low-power amplifier is suitable for implantable device applications.

  13. Spectral models of additive and modulation noise in speech and phonatory excitation signals

    Science.gov (United States)

    Schoentgen, Jean

    2003-01-01

    The article presents spectral models of additive and modulation noise in speech. The purpose is to learn about the causes of noise in the spectra of normal and disordered voices and to gauge whether the spectral properties of the perturbations of the phonatory excitation signal can be inferred from the spectral properties of the speech signal. The approach to modeling consists of deducing the Fourier series of the perturbed speech, assuming that the Fourier series of the noise and of the clean monocycle-periodic excitation are known. The models explain published data, take into account the effects of supraglottal tremor, demonstrate the modulation distortion owing to vocal tract filtering, establish conditions under which noise cues of different speech signals may be compared, and predict the impossibility of inferring the spectral properties of the frequency modulating noise from the spectral properties of the frequency modulation noise (e.g., phonatory jitter and frequency tremor). The general conclusion is that only phonatory frequency modulation noise is spectrally relevant. Other types of noise in speech are either epiphenomenal, or their spectral effects are masked by the spectral effects of frequency modulation noise.

  14. Measurement of the Low Frequency Noise of MOSFETs under Large Signal RF Excitation

    NARCIS (Netherlands)

    van der Wel, A.P.; Klumperink, Eric A.M.; Nauta, Bram

    A measurement technique [1] is presented that allows measurement of MOSFET low frequency (LF) noise under large signal RF (Radio Frequency) excitation. Measurements indicate that MOSFETS exhibit a reduction in LF noise when they are cycled from inversion to accummulation and that this reduction does

  15. Signal Processing of Vortex Flow with Noise Based on Wavelet Analysis

    Directory of Open Access Journals (Sweden)

    Xiaohong Zeng

    2014-07-01

    Full Text Available The vortex of low speed flows is difficult to measure resulted in that the output signal of vortex flowmeter appears the spectral line splitting and frequency offset in the low SNR and causes the frequency resolution to be decreased. In the paper, it first conducted the multi-scale wavelet decomposition to the vortex signal with noise, then removed the noise spectrum and carried on power spectrum analysis and frequency correction for the actual signal of stress type vortex flowmeter, and finally determined the vortex signal frequency to be as the basis for designing band-pass filter. By means of Matlab software, it took a signal with noise as an example, and reconstructed an effective sine signal by wavelet denoising algorithm. The simulation experiment shows that the presented method is effective.

  16. Fitting Noise Management Signal Processing Applying the American Academy of Audiology Pediatric Amplification Guideline: Verification Protocols.

    Science.gov (United States)

    Scollie, Susan; Levy, Charla; Pourmand, Nazanin; Abbasalipour, Parvaneh; Bagatto, Marlene; Richert, Frances; Moodie, Shane; Crukley, Jeff; Parsa, Vijay

    2016-03-01

    Although guidelines for fitting hearing aids for children are well developed and have strong basis in evidence, specific protocols for fitting and verifying some technologies are not always available. One such technology is noise management in children's hearing aids. Children are frequently in high-level and/or noisy environments, and many options for noise management exist in modern hearing aids. Verification protocols are needed to define specific test signals and levels for use in clinical practice. This work aims to (1) describe the variation in different brands of noise reduction processors in hearing aids and the verification of these processors and (2) determine whether these differences are perceived by 13 children who have hearing loss. Finally, we aimed to develop a verification protocol for use in pediatric clinical practice. A set of hearing aids was tested using both clinically available test systems and a reference system, so that the impacts of noise reduction signal processing in hearing aids could be characterized for speech in a variety of background noises. A second set of hearing aids was tested across a range of audiograms and across two clinical verification systems to characterize the variance in clinical verification measurements. Finally, a set of hearing aid recordings that varied by type of noise reduction was rated for sound quality by children with hearing loss. Significant variation across makes and models of hearing aids was observed in both the speed of noise reduction activation and the magnitude of noise reduction. Reference measures indicate that noise-only testing may overestimate noise reduction magnitude compared to speech-in-noise testing. Variation across clinical test signals was also observed, indicating that some test signals may be more successful than others for characterization of hearing aid noise reduction. Children provided different sound quality ratings across hearing aids, and for one hearing aid rated the sound

  17. Noise Spectrum of a Semiconductor Optical Amplifier Excited by a Modulated Signal

    DEFF Research Database (Denmark)

    Blaaberg, Søren; Mørk, Jesper

    2014-01-01

    A detailed analysis of the noise spectrum of a semiconductor optical amplifier excited by an amplitude-modulated input signal is presented. This extends the well-established theory for the case of continuous-wave input signals and is relevant for various applications within optical signal......, and modulation frequency, is investigated and explained. We find several interesting modifications to the spectra compared with the continuous-wave case. In particular, the side-bands present in the input-signal lead via four-wave mixing effects to additional structure in the spectra as well as additional noise...... processing. One important example is the analysis of noise in microwave photonic elements based on slow-light propagation in semiconductor optical amplifiers. Expressions for the noise spectra are derived and the dependence on important operation parameters, such as input power, modulation depth...

  18. Signal to Noise Ratios of Pulsed and Sinewave Modulated Direct Detection Lidar for IPDA Measurements

    Science.gov (United States)

    Sun, Xiaoli; Abshire, James B.

    2011-01-01

    The signal-to-noise ratios have been derived for IPDA lidar using a direct detection receiver for both pulsed and sinewave laser modulation techniques, and the results and laboratory measurements are presented

  19. Daily Snow Depth and SWE from GPS Signal-to-Noise Ratios, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set consists of daily snow depths and snow-water equivalents (SWEs) estimated from GPS signal-to-noise ratios (SNRs). Snow depth is determined by...

  20. Ship Radiated Noise Recognition Using Resonance-Based Sparse Signal Decomposition

    Directory of Open Access Journals (Sweden)

    Jiaquan Yan

    2017-01-01

    Full Text Available Under the complex oceanic environment, robust and effective feature extraction is the key issue of ship radiated noise recognition. Since traditional feature extraction methods are susceptible to the inevitable environmental noise, the type of vessels, and the speed of ships, the recognition accuracy will degrade significantly. Hence, we propose a robust time-frequency analysis method which combines resonance-based sparse signal decomposition (RSSD and Hilbert marginal spectrum (HMS analysis. First, the observed signals are decomposed into high resonance component, low resonance component, and residual component by RSSD, which is a nonlinear signal analysis method based not on frequency or scale but on resonance. High resonance component is multiple simultaneous sustained oscillations, low resonance component is nonoscillatory transients, and residual component is white Gaussian noises. According to the low-frequency periodic oscillatory characteristic of ship radiated noise, high resonance component is the purified ship radiated noise. RSSD is suited to noise suppression for low-frequency oscillation signals. Second, HMS of high resonance component is extracted by Hilbert-Huang transform (HHT as the feature vector. Finally, support vector machine (SVM is adopted as a classifier. Real audio recordings are employed in the experiments under different signal-to-noise ratios (SNRs. The experimental results indicate that the proposed method has a better recognition performance than the traditional method under different SNRs.

  1. Quantum detection of coherent-state signals in the presence of noise

    Science.gov (United States)

    Vilnrotter, V. A.; Lau, C. W.

    2003-01-01

    A general method for solving an important class of quantum detection problems will be presented and evaluated. The quantum theory for detecting pure states for communications purposes has been developed over two decades ago, however the mixed state problem representing signal plus noise states has received little attention due to its great complexity. Here we develop a practical model for solving the mixed-state problem using a discrete approximation to the coherent-state representation of signal plus noise density operators.

  2. Signal-Noise Ratio Control Subsystem of Digital Equipment for Transmission of "Strela" Relay Protection Commands

    Directory of Open Access Journals (Sweden)

    I. Zabenkov

    2012-01-01

    Full Text Available Continuous measurement function of relative noise and interference level in the information transmission channel is considered as an important one for controlling parameters of high-frequency signal. The present paper simulates an algorithm for measuring signal-noise ratio in the transmission channel of high-voltage lines which is used in the digital equipment for transmission of relay protection and emergency automation commands of "Strela" complex.

  3. Post-embedding tem signal-to-noise ratio of S-100

    Science.gov (United States)

    Fermin, C. D.; Lee, D. H.; Martin, D.

    1994-01-01

    We assessed the reactivity of purified S-100 antiserum in immuno-electron microscopy by counting the number of gold particles per microns 2 over inner ear tissues embedded in different media. Sections containing predominantly Schwann's cell cytoplasm and nucleus, afferent fiber axoplasm and myelin sheath of chick cochleae were reacted with anti-S-100 IgG, an antibody to a calcium binding protein of neuronal tissues, then labeled with anti-IgG-gold conjugate. This investigation was conducted because previously published procedures, unmodified, did not yield acceptable results. Preparation of all specimens was identical. Only the medium (PolyBed 812, Araldite or Spurr epoxies; and LR White, LR Gold or Lowicryl plastics) was changed. The medium was made the changing variable because antigens available in post-embedding immuno-electron microscopy are decreased by heat, either used and/or released during polymerization of the embedding medium. The results indicate that: (a) none of the embedding media above provided optimal signal-to-noise ratio for all parts of the nerve stained in the same section; (b) aggregation of gold particles over cells was highest in embedding media with high background labeling over areas devoid of tissue (noise); (c) aggregation occurred randomly throughout both cellular and acellular regions; and (d) particles aggregated less and were distributed more evenly in tissues from media yielding good ultrastructural integrity.

  4. Diffusion MRI noise mapping using random matrix theory

    National Research Council Canada - National Science Library

    Veraart, Jelle; Fieremans, Els; Novikov, Dmitry S

    2016-01-01

    .... Methods We exploit redundancy in non-Gaussian distributed multidirectional diffusion MRI data by identifying its noise-only principal components, based on the theory of noisy covariance matrices...

  5. Random-Resistor-Random-Temperature Kirchhoff-Law-Johnson-Noise (RRRT-KLJN Key Exchange

    Directory of Open Access Journals (Sweden)

    Kish Laszlo B.

    2016-03-01

    Full Text Available We introduce two new Kirchhoff-law-Johnson-noise (KLJN secure key distribution schemes which are generalizations of the original KLJN scheme. The first of these, the Random-Resistor (RR- KLJN scheme, uses random resistors with values chosen from a quasi-continuum set. It is well-known since the creation of the KLJN concept that such a system could work in cryptography, because Alice and Bob can calculate the unknown resistance value from measurements, but the RR-KLJN system has not been addressed in prior publications since it was considered impractical. The reason for discussing it now is the second scheme, the Random Resistor Random Temperature (RRRT- KLJN key exchange, inspired by a recent paper of Vadai, Mingesz and Gingl, wherein security was shown to be maintained at non-zero power flow. In the RRRT-KLJN secure key exchange scheme, both the resistances and their temperatures are continuum random variables. We prove that the security of the RRRT-KLJN scheme can prevail at a non-zero power flow, and thus the physical law guaranteeing security is not the Second Law of Thermodynamics but the Fluctuation-Dissipation Theorem. Alice and Bob know their own resistances and temperatures and can calculate the resistance and temperature values at the other end of the communication channel from measured voltage, current and power-flow data in the wire. However, Eve cannot determine these values because, for her, there are four unknown quantities while she can set up only three equations. The RRRT-KLJN scheme has several advantages and makes all former attacks on the KLJN scheme invalid or incomplete.

  6. [Effect of noise in submarine compartment on signal discrimination and arithmetic performance].

    Science.gov (United States)

    Hu, Z; Liang, Z; Shi, X; Tang, Z

    1997-06-01

    To study the effects of noise level in submarine compartment on signal discrimination and arithmetic performance, experiments were carried out on 13 subjects. The results showed that as noise level raised from moderate (73 dBA) to higher levels (85-92 dBA), work efficiency showed a progressive decrease, but when noise level reached 96 dBA the decrease in efficiency reached a steady state. The results indicated that impairment of efficiency apparently occurred at a level of 85 dBA and that the interference effect of noise was more pronounced on task performance with mental strain.

  7. Characterization of Transient Noise in Advanced LIGO Relevant to Gravitational Wave Signal GW150914

    Science.gov (United States)

    Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adamo, M.; Adams, C.; Adams, T.; Camp, Jordan B.

    2016-01-01

    On 14 September 2015, a gravitational wave signal from a coalescing black hole binary system was observed by the Advanced LIGO detectors. This paper describes the transient noise backgrounds used to determine the significance of the event (designated GW150914) and presents the results of investigations into potential correlated or uncorrelated sources of transient noise in the detectors around the time of the event. The detectors were operating nominally at the time of GW150914. We have ruled out environmental influences and non-Gaussian instrument noise at either LIGO detector as the cause of the observed gravitational wave signal.

  8. Effects of reverberation, background talker number, and compression release time on signal-to-noise ratioa)

    Science.gov (United States)

    Reinhart, Paul; Zahorik, Pavel; Souza, Pamela E.

    2017-01-01

    Wide dynamic range compression (WDRC) processing in hearing aids alters the signal-to-noise ratio (SNR) of a speech-in-noise signal. This effect depends on the modulations of the speech and noise, input SNR, and WDRC speed. The purpose of the present experiment was to examine the change in output SNR caused by the interaction between modulation characteristics and WDRC speed. Two modulation manipulations were examined: (1) reverberation and (2) variation in background talker number. Results indicated that fast-acting WDRC altered SNR more than slow-acting WDRC; however, reverberation reduced this difference. Additionally, less modulated maskers led to poorer output SNRs than modulated maskers. PMID:28764441

  9. The concept of signal-to-noise ratio in the modulation domain and speech intelligibility.

    Science.gov (United States)

    Dubbelboer, Finn; Houtgast, Tammo

    2008-12-01

    A new concept is proposed that relates to intelligibility of speech in noise. The concept combines traditional estimations of signal-to-noise ratios (S/N) with elements from the modulation transfer function model, which results in the definition of the signal-to-noise ratio in the modulation domain: the (SN)(mod). It is argued that this (SN)(mod), quantifying the strength of speech modulations relative to a floor of spurious modulations arising from the speech-noise interaction, is the key factor in relation to speech intelligibility. It is shown that, by using a specific test signal, the strength of these spurious modulations can be measured, allowing an estimation of the (SN)(mod) for various conditions of additive noise, noise suppression, and amplitude compression. By relating these results to intelligibility data for these same conditions, the relevance of the (SN)(mod) as the key factor underlying speech intelligibility is clearly illustrated. For instance, it is shown that the commonly observed limited effect of noise suppression on speech intelligibility is correctly "predicted" by the (SN)(mod), whereas traditional measures such as the speech transmission index, considering only the changes in the speech modulations, fall short in this respect. It is argued that (SN)(mod) may provide a relevant tool in the design of successful noise-suppression systems.

  10. Time-domain noise reduction based on an orthogonal decomposition for desired signal extraction.

    Science.gov (United States)

    Benesty, Jacob; Chen, Jingdong; Arden Huang, Yiteng; Gaensler, Tomas

    2012-07-01

    This paper addresses the problem of noise reduction in the time domain where the clean speech sample at every time instant is estimated by filtering a vector of the noisy speech signal. Such a clean speech estimate consists of both the filtered speech and residual noise (filtered noise) as the noisy vector is the sum of the clean speech and noise vectors. Traditionally, the filtered speech is treated as the desired signal after noise reduction. This paper proposes to decompose the clean speech vector into two orthogonal components: one is correlated and the other is uncorrelated with the current clean speech sample. While the correlated component helps estimate the clean speech, it is shown that the uncorrelated component interferes with the estimation, just as the additive noise. Based on this orthogonal decomposition, the paper presents a way to define the error signal and cost functions and addresses the issue of how to design different optimal noise reduction filters by optimizing these cost functions. Specifically, it discusses how to design the maximum SNR filter, the Wiener filter, the minimum variance distortionless response (MVDR) filter, the tradeoff filter, and the linearly constrained minimum variance (LCMV) filter. It demonstrates that the maximum SNR, Wiener, MVDR, and tradeoff filters are identical up to a scaling factor. It also shows from the orthogonal decomposition that many performance measures can be defined, which seem to be more appropriate than the traditional ones for the evaluation of the noise reduction filters.

  11. Cortical Dipole Imaging for Multiple Signal Sources Considering Time-Varying Non-Uniform Noise

    Science.gov (United States)

    Hori, Junichi; Watanabe, Yoshiki

    Cortical dipole imaging is one of the spatial enhancement techniques from the scalp electroencephalogram. We investigated the dipole imaging for multiple signal sources under time-varying non-uniform noise conditions. The effects of incorporating statistical information of noise into the spatiotemporal inverse filter were examined by computer simulations and experimental studies in three sphere volume conductor model. The parametric projection filter that incorporated with noise covariance was applied to the inverse problem of EEG measurements. The noise covariance matrix was estimated by applying independent component analysis to the scalp potentials. The spatial filter was expanded to apply to the time-varying non-uniform noise conditions such as eye blink artifact. Moreover, multiple dipole distributions were introduced to extract and to visualize individual signal sources. The proposed imaging technique was applied to human experimental data of visual evoked potentials. We obtained reasonable results that coincide to physiological knowledge.

  12. Effects of signal analysis parameters and noise removal on measured aircraft spectra

    Science.gov (United States)

    Kelly, Jeffrey J.; Wilson, Mark R.

    1993-01-01

    Special techniques must be applied when analyzing acoustic noise data from nonstationary sources such as aircraft flyover measurements. Since the Fourier transform is time dependent, the noise signal is divided into short time segments by introducing a window function so that the spectral characteristics remain reasonably stationary. Reducing the window width reduces the frequency resolution while increasing the window duration can lead to spectral smearing. A trade-off must be made between time resolution and frequency resolution. The effects of varying the window duration on narrow-band acoustic spectra and thus the frequency bin width are addressed in this study. The influence of window functions (rectangular, Hamming, etc.) are also investigated. Both a tonal noise source, XV-15 aircraft in the airplane mode, and a broadband noise source, a F-18 aircraft, are considered. When dealing with flight test data, not only is the signal nonstationary, often it is contaminated by both ambient background noise and internal noise generated by the data acquisition system and power generators. Since generator noise is highly tonal, this can be particularly troublesome when computing tone-corrected perceived noise level (PNLT). A scheme is presented in this paper to eliminate unwanted background and internal noise.

  13. Comparative analysis of chosen transforms in the context of de-noising harmonic signals

    Directory of Open Access Journals (Sweden)

    Artur Zacniewski

    2015-09-01

    Full Text Available In the article, comparison of popular transforms used i.a. in denoising harmonical signals was presented. The division of signals submitted to mathematical analysis was shown and chosen transforms such as Short Time Fourier Transform, Wigner-Ville Distribution, Wavelet Transform and Discrete Cosine Transform were presented. Harmonic signal with white noise added was submitted for research. During research, the parameters of noise were changed to analyze the effects of using particular transform on noised signal. The importance of right choice for transform and its parameters (different for particular kind of transform was shown. Small changes in parameters or different functions used in transform can lead to considerably different results.[b]Keywords[/b]: denoising of harmonical signals, wavelet transform, discrete cosine transform, DCT

  14. Electromagnetic Signals and Earthquakes 2.0: Increasing Signals and Reducing Noise

    Science.gov (United States)

    Dunson, J. C.; Bleier, T.; Heraud, J. A.; Muller, S.; Lindholm, C.; Christman, L.; King, R.; Lemon, J.

    2013-12-01

    QuakeFinder has an international network of 150+ Magnetometers and air conductivity instruments located in California, Peru, Chile, Taiwan, and Greece. Since 2000, QuakeFinder has been collecting electromagnetic data and applying simple algorithms to identify and characterize electromagnetic signals that occur in the few weeks prior to earthquakes greater than M4.5. In this presentation, we show refinements to several aspects of our signal identification techniques that enhance detection of pre-earthquake patterns. Our magnetometers have been improved to show longer pulses, and we are now using second generation algorithms that have been refined to detect the proper shape of the earthquake-generated pulses and to allow individual site adjustments. Independent lightning strike data has also now been included to mask out lightning based on amplitude and distance from a given instrument site. Direction of arrival (Azimuth) algorithms have been added to identify patterns of pulse clustering that occur prior to nearby earthquakes. Likewise, positive and negative air ion concentration detection has been improved by building better enclosures, using stainless screens to eliminate insects and some dirt sources, conformal coating PC boards to reduce moisture contamination, and filtering out contaminated data segments based on relative humidity measurements at each site. Infra Red data from the western GOES satellite has been time-filtered, cloud-filtered, and compared to 3 year averages of each pixel's output (by seasonal month) to arrive at a relevant comparison baseline for each night's temperature/cooling slope. All these efforts have helped improve the detection of multiple, nearly simultaneous, electromagnetic signals due to earthquake preparation processes, while reducing false positive indications due to environmental noise sources.

  15. Analogies between colored Lévy noise and random channel approach to disordered kinetics

    Science.gov (United States)

    Vlad, Marcel O.; Velarde, Manuel G.; Ross, John

    2004-02-01

    We point out some interesting analogies between colored Lévy noise and the random channel approach to disordered kinetics. These analogies are due to the fact that the probability density of the Lévy noise source plays a similar role as the probability density of rate coefficients in disordered kinetics. Although the equations for the two approaches are not identical, the analogies can be used for deriving new, useful results for both problems. The random channel approach makes it possible to generalize the fractional Uhlenbeck-Ornstein processes (FUO) for space- and time-dependent colored noise. We describe the properties of colored noise in terms of characteristic functionals, which are evaluated by using a generalization of Huber's approach to complex relaxation [Phys. Rev. B 31, 6070 (1985)]. We start out by investigating the properties of symmetrical white noise and then define the Lévy colored noise in terms of a Langevin equation with a Lévy white noise source. We derive exact analytical expressions for the various characteristic functionals, which characterize the noise, and a functional fractional Fokker-Planck equation for the probability density functional of the noise at a given moment in time. Second, by making an analogy between the theory of colored noise and the random channel approach to disordered kinetics, we derive fractional equations for the evolution of the probability densities of the random rate coefficients in disordered kinetics. These equations serve as a basis for developing methods for the evaluation of the statistical properties of the random rate coefficients from experimental data. Special attention is paid to the analysis of systems for which the observed kinetic curves can be described by linear or nonlinear stretched exponential kinetics.

  16. Noise exposure immediately activates cochlear mitogen-activated protein kinase signaling

    Directory of Open Access Journals (Sweden)

    Kumar N Alagramam

    2014-01-01

    Full Text Available Noise-induced hearing loss (NIHL is a major public health issue worldwide. Uncovering the early molecular events associated with NIHL would reveal mechanisms leading to the hearing loss. Our aim is to investigate the immediate molecular responses after different levels of noise exposure and identify the common and distinct pathways that mediate NIHL. Previous work showed mice exposed to 116 decibels sound pressure level (dB SPL broadband noise for 1 h had greater threshold shifts than the mice exposed to 110 dB SPL broadband noise, hence we used these two noise levels in this study. Groups of 4-8-week-old CBA/CaJ mice were exposed to no noise (control or to broadband noise for 1 h, followed by transcriptome analysis of total cochlear RNA isolated immediately after noise exposure. Previously identified and novel genes were found in all data sets. Following exposure to noise at 116 dB SPL, the earliest responses included up-regulation of 243 genes and down-regulation of 61 genes, while a similar exposure at 110 dB SPL up-regulated 155 genes and down-regulated 221 genes. Bioinformatics analysis indicated that mitogen-activated protein kinase (MAPK signaling was the major pathway in both levels of noise exposure. Nevertheless, both qualitative and quantitative differences were noticed in some MAPK signaling genes, after exposure to different noise levels. Cacna1b , Cacna1g , and Pla2g6 , related to calcium signaling were down-regulated after 110 dB SPL exposure, while the fold increase in the expression of Fos was relatively lower than what was observed after 116 dB SPL exposure. These subtle variations provide insight on the factors that may contribute to the differences in NIHL despite the activation of a common pathway.

  17. Noise exposure immediately activates cochlear mitogen-activated protein kinase signaling.

    Science.gov (United States)

    Alagramam, Kumar N; Stepanyan, Ruben; Jamesdaniel, Samson; Chen, Daniel H-C; Davis, Rickie R

    2014-01-01

    Noise-induced hearing loss (NIHL) is a major public health issue worldwide. Uncovering the early molecular events associated with NIHL would reveal mechanisms leading to the hearing loss. Our aim is to investigate the immediate molecular responses after different levels of noise exposure and identify the common and distinct pathways that mediate NIHL. Previous work showed mice exposed to 116 decibels sound pressure level (dB SPL) broadband noise for 1 h had greater threshold shifts than the mice exposed to 110 dB SPL broadband noise, hence we used these two noise levels in this study. Groups of 4-8-week-old CBA/CaJ mice were exposed to no noise (control) or to broadband noise for 1 h, followed by transcriptome analysis of total cochlear RNA isolated immediately after noise exposure. Previously identified and novel genes were found in all data sets. Following exposure to noise at 116 dB SPL, the earliest responses included up-regulation of 243 genes and down-regulation of 61 genes, while a similar exposure at 110 dB SPL up-regulated 155 genes and down-regulated 221 genes. Bioinformatics analysis indicated that mitogen-activated protein kinase (MAPK) signaling was the major pathway in both levels of noise exposure. Nevertheless, both qualitative and quantitative differences were noticed in some MAPK signaling genes, after exposure to different noise levels. Cacna1b , Cacna1g , and Pla2g6 , related to calcium signaling were down-regulated after 110 dB SPL exposure, while the fold increase in the expression of Fos was relatively lower than what was observed after 116 dB SPL exposure. These subtle variations provide insight on the factors that may contribute to the differences in NIHL despite the activation of a common pathway.

  18. Hardware Design and Implementation of a Wavelet De-Noising Procedure for Medical Signal Preprocessing

    Directory of Open Access Journals (Sweden)

    Szi-Wen Chen

    2015-10-01

    Full Text Available In this paper, a discrete wavelet transform (DWT based de-noising with its applications into the noise reduction for medical signal preprocessing is introduced. This work focuses on the hardware realization of a real-time wavelet de-noising procedure. The proposed de-noising circuit mainly consists of three modules: a DWT, a thresholding, and an inverse DWT (IDWT modular circuits. We also proposed a novel adaptive thresholding scheme and incorporated it into our wavelet de-noising procedure. Performance was then evaluated on both the architectural designs of the software and. In addition, the de-noising circuit was also implemented by downloading the Verilog codes to a field programmable gate array (FPGA based platform so that its ability in noise reduction may be further validated in actual practice. Simulation experiment results produced by applying a set of simulated noise-contaminated electrocardiogram (ECG signals into the de-noising circuit showed that the circuit could not only desirably meet the requirement of real-time processing, but also achieve satisfactory performance for noise reduction, while the sharp features of the ECG signals can be well preserved. The proposed de-noising circuit was further synthesized using the Synopsys Design Compiler with an Artisan Taiwan Semiconductor Manufacturing Company (TSMC, Hsinchu, Taiwan 40 nm standard cell library. The integrated circuit (IC synthesis simulation results showed that the proposed design can achieve a clock frequency of 200 MHz and the power consumption was only 17.4 mW, when operated at 200 MHz.

  19. Hardware design and implementation of a wavelet de-noising procedure for medical signal preprocessing.

    Science.gov (United States)

    Chen, Szi-Wen; Chen, Yuan-Ho

    2015-10-16

    In this paper, a discrete wavelet transform (DWT) based de-noising with its applications into the noise reduction for medical signal preprocessing is introduced. This work focuses on the hardware realization of a real-time wavelet de-noising procedure. The proposed de-noising circuit mainly consists of three modules: a DWT, a thresholding, and an inverse DWT (IDWT) modular circuits. We also proposed a novel adaptive thresholding scheme and incorporated it into our wavelet de-noising procedure. Performance was then evaluated on both the architectural designs of the software and. In addition, the de-noising circuit was also implemented by downloading the Verilog codes to a field programmable gate array (FPGA) based platform so that its ability in noise reduction may be further validated in actual practice. Simulation experiment results produced by applying a set of simulated noise-contaminated electrocardiogram (ECG) signals into the de-noising circuit showed that the circuit could not only desirably meet the requirement of real-time processing, but also achieve satisfactory performance for noise reduction, while the sharp features of the ECG signals can be well preserved. The proposed de-noising circuit was further synthesized using the Synopsys Design Compiler with an Artisan Taiwan Semiconductor Manufacturing Company (TSMC, Hsinchu, Taiwan) 40 nm standard cell library. The integrated circuit (IC) synthesis simulation results showed that the proposed design can achieve a clock frequency of 200 MHz and the power consumption was only 17.4 mW, when operated at 200 MHz.

  20. Hardware Design and Implementation of a Wavelet De-Noising Procedure for Medical Signal Preprocessing

    Science.gov (United States)

    Chen, Szi-Wen; Chen, Yuan-Ho

    2015-01-01

    In this paper, a discrete wavelet transform (DWT) based de-noising with its applications into the noise reduction for medical signal preprocessing is introduced. This work focuses on the hardware realization of a real-time wavelet de-noising procedure. The proposed de-noising circuit mainly consists of three modules: a DWT, a thresholding, and an inverse DWT (IDWT) modular circuits. We also proposed a novel adaptive thresholding scheme and incorporated it into our wavelet de-noising procedure. Performance was then evaluated on both the architectural designs of the software and. In addition, the de-noising circuit was also implemented by downloading the Verilog codes to a field programmable gate array (FPGA) based platform so that its ability in noise reduction may be further validated in actual practice. Simulation experiment results produced by applying a set of simulated noise-contaminated electrocardiogram (ECG) signals into the de-noising circuit showed that the circuit could not only desirably meet the requirement of real-time processing, but also achieve satisfactory performance for noise reduction, while the sharp features of the ECG signals can be well preserved. The proposed de-noising circuit was further synthesized using the Synopsys Design Compiler with an Artisan Taiwan Semiconductor Manufacturing Company (TSMC, Hsinchu, Taiwan) 40 nm standard cell library. The integrated circuit (IC) synthesis simulation results showed that the proposed design can achieve a clock frequency of 200 MHz and the power consumption was only 17.4 mW, when operated at 200 MHz. PMID:26501290

  1. Friction Signal Denoising Using Complete Ensemble EMD with Adaptive Noise and Mutual Information

    Directory of Open Access Journals (Sweden)

    Chengwei Li

    2015-08-01

    Full Text Available During the measurement of friction force, the measured signal generally contains noise. To remove the noise and preserve the important features of the signal, a hybrid filtering method is introduced that uses the mutual information and a new waveform. This new waveform is the difference between the original signal and the sum of intrinsic mode functions (IMFs, which are obtained by empirical mode decomposition (EMD or its improved versions. To evaluate the filter performance for the friction signal, ensemble EMD (EEMD, complementary ensemble EMD (CEEMD, and complete ensemble EMD with adaptive noise (CEEMDAN are employed in combination with the proposed filtering method. The combination is used to filter the synthesizing signals at first. For the filtering of the simulation signal, the filtering effect is compared under conditions of different ensemble number, sampling frequency, and the input signal-noise ratio, respectively. Results show that CEEMDAN outperforms other signal filtering methods. In particular, this method is successful in filtering the friction signal as evaluated by the de-trended fluctuation analysis (DFA algorithm.

  2. [Effect of JNK signal transduction pathway in intense noise-induced apoptosis of vestibular hair cells in guinea pigs].

    Science.gov (United States)

    Wei, Ming; Wang, Wei-tao; Zhang, Tao; Tu, Ling; Liang, Ying-hong; Liu, Jia; Zhang, Jun-hua; Gong, Yan-jie

    2012-10-01

    To investigate the mechanism of intense noise-induced apoptosis of vestibular hair cells in guinea pigs and the effect of phosphorylated c-Jun N-terminal kinase (JNK) signal transduction pathway in intense noise-induced apoptosis of vestibular hair cells. Thirty-two guinea pigs were randomly and equally divided into 1, 5, and 15 d experimental groups and control group. The guinea pigs in the experimental groups were exposed to 4 kHz narrow-band noise at 120 dB SPL for 4 h and then subjected to measurement of auditory brainstem response at 1, 5, or 15 d after noise exposure. In each group, four guinea pigs were used to prepare paraffin sections of vestibular hair cells, and the rest for extraction of total protein from vestibular hair cells. The apoptosis of vestibular hair cells was detected by terminal deoxynucleotidyl transferase (TdT)-mediated d-UTP nick-end labeling (TUNEL). The expression levels of p-JNK and pc-Jun were measured by immunohistochemistry and Western blot. TUNEL-positive cells were found in the vestibular hair cells in the experimental groups, most in the 1 d experimental group and least in the 15 d experimental group, but no positive cells were found in the control group. The immunohistochemical results showed that p-JNK and pc-Jun were detected in the cell nuclei in the experimental groups, but no p-JNK- and pc-Jun-positive cells were found in the control group. The Western blot showed that p-JNK and pc-Jun were increased and activated quickly at 1d after noise exposure, reached the peak levels at 5 d after noise exposure, and were then decreased gradually, but they were still at relatively high levels at 15 d after noise exposure. Intense noise can cause injury to vestibular hair cells by inducing cell apoptosis, and p-JNK marks the activation of JNK signal transduction pathway, suggesting that JNK signal transduction pathway plays an important role in intense noise-induced apoptosis of vestibular hair cells in guinea pigs.

  3. Improved conductivity reconstruction from multi-echo MREIT utilizing weighted voxel-specific signal-to-noise ratios.

    Science.gov (United States)

    Kim, Myoung Nyoun; Ha, Tae Young; Woo, Eung Je; Kwon, Oh In

    2012-06-07

    Magnetic resonance electrical impedance tomography (MREIT) is a non-invasive method to visualize cross-sectional electrical conductivity and/or current density by measuring a magnetic flux density signal when an electrical current is injected into a subject. In the MREIT system, it is crucial to reduce the scan duration while maintaining spatial resolution and contrast for practical in vivo implementation. The purpose of the study is to optimize the measured magnetic flux density using an interleaved multiple-echo pulse sequence (injected current nonlinear encoding) that acquires each spatial position multiple times, although these pixels vary between echoes in their signal-to-noise ratio due to (a) T*2 decay and (b) the current density passing through the pixel. Using the acquired multiple measured magnetic flux densities, the noise level for the measured magnetic flux density B(z) at each pixel is estimated using the relationship between the intensity of the magnitude and the width of the injected current. We determine an optimal combination of the multiply acquired magnetic flux densities, which optimally reduces the random noise artifacts. We develop a new denoising technique and apply it to a recovered conductivity distribution with a known noise level of the recovered magnetic flux density, which is designed to provide a stable internal conductivity distribution, while sustaining resolution. The proposed method uses three key steps: the first step is optimizing the magnetic flux density by using the multiple-echo magnetic flux densities at each pixel, the second step is estimating the noise level of this optimized magnetic flux density and the third step is applying a denoising technique using the pixel-specific estimated noise level. Numerical simulation experiments using a three-dimensional cylindrical phantom model validated the proposed method. Multiple-echo B(z) data were generated, including in short T*2 or low spin-density regions, as a function of T*2

  4. A study on discrete wavelet-based noise removal from EEG signals.

    Science.gov (United States)

    Asaduzzaman, K; Reaz, M B I; Mohd-Yasin, F; Sim, K S; Hussain, M S

    2010-01-01

    Electroencephalogram (EEG) serves as an extremely valuable tool for clinicians and researchers to study the activity of the brain in a non-invasive manner. It has long been used for the diagnosis of various central nervous system disorders like seizures, epilepsy, and brain damage and for categorizing sleep stages in patients. The artifacts caused by various factors such as Electrooculogram (EOG), eye blink, and Electromyogram (EMG) in EEG signal increases the difficulty in analyzing them. Discrete wavelet transform has been applied in this research for removing noise from the EEG signal. The effectiveness of the noise removal is quantitatively measured using Root Mean Square (RMS) Difference. This paper reports on the effectiveness of wavelet transform applied to the EEG signal as a means of removing noise to retrieve important information related to both healthy and epileptic patients. Wavelet-based noise removal on the EEG signal of both healthy and epileptic subjects was performed using four discrete wavelet functions. With the appropriate choice of the wavelet function (WF), it is possible to remove noise effectively to analyze EEG significantly. Result of this study shows that WF Daubechies 8 (db8) provides the best noise removal from the raw EEG signal of healthy patients, while WF orthogonal Meyer does the same for epileptic patients. This algorithm is intended for FPGA implementation of portable biomedical equipments to detect different brain state in different circumstances.

  5. Signal detection in industrial noise: effects of noise exposure history, hearing loss, and the use of ear protection.

    Science.gov (United States)

    Abel, S M; Kunov, H; Pichora-Fuller, M K; Alberti, P W

    1985-01-01

    The detection of one-third octave signals superimposed on backgrounds of steady-state and intermittent industrial noise of 84 dBA was investigated for observers with normal hearing or moderate to severe noise-induced hearing loss (NIHL). Variables included age, noise exposure history, configuration of the audiogram and the wearing of insert hearing protectors. Detection thresholds were obtained binaurally over headphones using a two- interval forced-choice procedure. For unprotected listening all observers showed a masked threshold of about 80 dBA for a one-third octave band cented at 3.15 kHz. Neither variation in noise exposure history nor configuration of the audiogram were significant factors. Using insert protectors in noise, observers with normal hearing showed an advantage on average of 3 dB. Those with NIHL gave masked detection thresholds greater than 100 dBA. Detection of a one-third octave band centred at 1 kHz by hearing-impaired observers with mild to moderate loss at 1 kHz was similar to that for normal observers. A model of the detection process was developed and evaluated.

  6. Probabilistic Signal Recovery and Random Matrices

    Science.gov (United States)

    2016-12-08

    is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing   data sources , gathering and...a collection of information   if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ORGANIZATION...proved a sharp invertibility result for sparse random matrices, showed how to improve the norm of a general random matrix by removing a small submatrix

  7. Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal.

    Science.gov (United States)

    Satija, Udit; Ramkumar, Barathram; Sabarimalai Manikandan, M

    2017-02-01

    Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal.

  8. The Effects of Noise on Speech and Warning Signals

    Science.gov (United States)

    1989-06-01

    reverberation on speech recognition, Nabelek and Pickett (1974) found that a change in reverberation time of 0.3 second produced a substantial decrease...between a reverberation time of 0.25 to 0.5 second, and concluded that the adverse effects of reverberation are greater in small than they are in...from 0% to 34.8%, depending on reverberation time , presence or absence of noise, and monaural or binaural listening (Nabelek and Robinette, 1978, p. 246

  9. Discrete random signal processing and filtering primer with Matlab

    CERN Document Server

    Poularikas, Alexander D

    2013-01-01

    Engineers in all fields will appreciate a practical guide that combines several new effective MATLAB® problem-solving approaches and the very latest in discrete random signal processing and filtering.Numerous Useful Examples, Problems, and Solutions - An Extensive and Powerful ReviewWritten for practicing engineers seeking to strengthen their practical grasp of random signal processing, Discrete Random Signal Processing and Filtering Primer with MATLAB provides the opportunity to doubly enhance their skills. The author, a leading expert in the field of electrical and computer engineering, offe

  10. [Study of the effect of JNK signal transduction pathway in intense noise-induced apoptosis in cochlea of guinea pig].

    Science.gov (United States)

    Xue, Qiuhong; Chen, Jia; Gong, Shusheng; Xie, Jing; He, Jian; Chen, Xiaolin

    2009-12-01

    To investigate the mechanism of intense noise-induced cochlea cells death in guinea pig, and the effect of JNK signal transduction pathway in the procedure of cochlea cells apoptosis by intense noise-induced. Thirty-two guinea pigs were randomly divided into 4 groups. The guinea pigs in the experiment groups were exposed to 4 kHz narrow band noise at 120 dB SPL for 4 h. After the noise expose for 1, 4, 14 days of the experiment guinea pigs, ABR of the guinea pigs on experiment and control groups were tested before put them to death. Four guinea pig's cochleas of every group were taken to paraffin section, and the rest was extracted the total cochlear's protein. Apoptosis was tested by terminal deoxynucleotidyl Transferase (TdT)-mediated deoxyuridine triphosphate (d-UTP) nick and labeling method (TUNEL). The phosphorylation of JNK and c-Jun were tested by immunohistochemistry and western blot methods. Tunel-Positive cells in the Corti's, SGC and SV of experiment groups, and there have significant differences compared with the control group (Pnoise exposed, but no positive cells were found in the control. Protein levels of P-JNK and P-c-Jun were risen up and activated quickly after noise exposed, and achieved peak in 1 d, 4 d and then fallen-offs, but still maintained higher levels within 14 d. Intense noise causes cochlea cell lesion by inducing apoptosis to result in and JNK signal transduction pathway plays an important role in the procedure of apoptosis.

  11. Effect of signal noise on the learning capability of an artificial neural network

    Science.gov (United States)

    Vega, J. J.; Reynoso, R.; Calvet, H. Carrillo

    2009-07-01

    Digital Pulse Shape Analysis (DPSA) by artificial neural networks (ANN) is becoming an important tool to extract relevant information from digitized signals in different areas. In this paper, we present a systematic evidence of how the concomitant noise that distorts the signals or patterns to be identified by an ANN set limits to its learning capability. Also, we present evidence that explains overtraining as a competition between the relevant pattern features, on the one side, against the signal noise, on the other side, as the main cause defining the shape of the error surface in weight space and, consequently, determining the steepest descent path that controls the ANN adaptation process.

  12. Effect of signal noise on the learning capability of an artificial neural network

    Energy Technology Data Exchange (ETDEWEB)

    Vega, J.J. [Departamento del Acelerador, Gerencia de Ciencias Ambientales, Instituto Nacional de Investigaciones Nucleares, Apartado Postal 18-1027, Mexico D.F. 11801 (Mexico)], E-mail: jjvc@nuclear.inin.mx; Reynoso, R. [Departamento del Acelerador, Gerencia de Ciencias Ambientales, Instituto Nacional de Investigaciones Nucleares, Apartado Postal 18-1027, Mexico D.F. 11801 (Mexico); Calvet, H. Carrillo [Laboratorio de Dinamica no Lineal, Facultad de Ciencias, Universidad Nacional Autonoma de Mexico, Mexico D.F. 04510 (Mexico)

    2009-07-21

    Digital Pulse Shape Analysis (DPSA) by artificial neural networks (ANN) is becoming an important tool to extract relevant information from digitized signals in different areas. In this paper, we present a systematic evidence of how the concomitant noise that distorts the signals or patterns to be identified by an ANN set limits to its learning capability. Also, we present evidence that explains overtraining as a competition between the relevant pattern features, on the one side, against the signal noise, on the other side, as the main cause defining the shape of the error surface in weight space and, consequently, determining the steepest descent path that controls the ANN adaptation process.

  13. Full-Scale Turbofan Engine Noise-Source Separation Using a Four-Signal Method

    Science.gov (United States)

    Hultgren, Lennart S.; Arechiga, Rene O.

    2016-01-01

    Contributions from the combustor to the overall propulsion noise of civilian transport aircraft are starting to become important due to turbofan design trends and expected advances in mitigation of other noise sources. During on-ground, static-engine acoustic tests, combustor noise is generally sub-dominant to other engine noise sources because of the absence of in-flight effects. Consequently, noise-source separation techniques are needed to extract combustor-noise information from the total noise signature in order to further progress. A novel four-signal source-separation method is applied to data from a static, full-scale engine test and compared to previous methods. The new method is, in a sense, a combination of two- and three-signal techniques and represents an attempt to alleviate some of the weaknesses of each of those approaches. This work is supported by the NASA Advanced Air Vehicles Program, Advanced Air Transport Technology Project, Aircraft Noise Reduction Subproject and the NASA Glenn Faculty Fellowship Program.

  14. A New Method for Reduction of Photomultiplier Signal-Induced Noise

    Science.gov (United States)

    Koble, Andrea; DeYoung, Russell

    2000-01-01

    For lidar measurements of ozone, photomultiplier tube (PMT) detector signal-induced noise represents a fundamental problem that complicates the extraction of information from lidar data. A new method is developed to significantly reduce signal-induced noise in lidar receiver PMT detectors. The electron optics of the lidar photomultiplier detector is modified to filter the source of signal-induced noise. A mesh electrode external to the PMT is utilized to control photoemission and disorient electron trajectories from the photocathode to the first dynode. Experiments were taken both with simulated and actual lidar return signals at Langley Research Center. Results show at least 40 percent more accurate ozone number density values with a mesh voltage of 60 V applied than with no voltage applied.

  15. Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices

    Science.gov (United States)

    Ji, Lei; Zhang, Li; Rover, Jennifer R.; Wylie, Bruce K.; Chen, Xuexia

    2014-01-01

    In the past 40 years, many spectral vegetation indices have been developed to quantify vegetation biophysical parameters. An ideal vegetation index should contain the maximum level of signal related to specific biophysical characteristics and the minimum level of noise such as background soil influences and atmospheric effects. However, accurate quantification of signal and noise in a vegetation index remains a challenge, because it requires a large number of field measurements or laboratory experiments. In this study, we applied a geostatistical method to estimate signal-to-noise ratio (S/N) for spectral vegetation indices. Based on the sample semivariogram of vegetation index images, we used the standardized noise to quantify the noise component of vegetation indices. In a case study in the grasslands and shrublands of the western United States, we demonstrated the geostatistical method for evaluating S/N for a series of soil-adjusted vegetation indices derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The soil-adjusted vegetation indices were found to have higher S/N values than the traditional normalized difference vegetation index (NDVI) and simple ratio (SR) in the sparsely vegetated areas. This study shows that the proposed geostatistical analysis can constitute an efficient technique for estimating signal and noise components in vegetation indices.

  16. A data-driven processing scheme for the GPR signal analysis and noise patterns removal

    Science.gov (United States)

    Jeng, Yih; Chen, Chih-Sung

    2015-04-01

    GPR signal events are inevitably interfered by a variety of noises. Noise waves degrade the quality of subsurface reflections, mask the reflections from targets, and may appear like true reflections. Some investigators have proposed ways to minimize the interference of specific noise events; however, a generalized noise removal methodology is still an interesting issue. In this study, we demonstrate an effective methodology for analyzing GPR data and suppressing noise events. The processing scheme is framed by the modified multidimensional ensemble empirical mode decomposition (MDEEMD), a multidimensional extension of the EMD algorithm. The MDEEMD is a data-driven time-frequency approach that has the advantages of dealing with nonlinear and non-stationary multichannel signals, and outperforms other univariate EMD algorithms with better uniformity, closer scale alignment, and more reliable intrinsic mode functions (IMFs). The procedure is implemented by performing the EEMD (ensemble empirical mode decomposition) in both directions of the B-scan GPR data set consecutively to obtain a 2D image matrix in which the elements are images representing fragmentary features of the B-scan GPR data. The final 2D EEMD filter bank is achieved by applying the comparable minimal scale combination technique to the 2D image matrix. With the velocity analysis and pattern recognition, the noise components can be distinguished from the signal components in the 2D EEMD filter bank. By subtracting the noise components from the filter bank and combining the rest components or directly picking the signal components for final image reconstruction, the noise events in the B-scan are suppressed effectively while most of the true reflections remain. The developed approach provides an alternative efficient method for GPR signal enhancement and can be applied to extract information from other noisy multidimensional geophysical data with limited modifications.

  17. Power Spectrum Estimation of Randomly Sampled Signals

    DEFF Research Database (Denmark)

    Velte, Clara M.; Buchhave, Preben; K. George, William

    2014-01-01

    with high data rate and low inherent bias, respectively, while residence time weighting provides non-biased estimates regardless of setting. The free-running processor was also tested and compared to residence time weighting using actual LDA measurements in a turbulent round jet. Power spectra from...... of alternative methods attempting to produce correct power spectra have been invented andtested. The objective of the current study is to create a simple computer generated signal for baseline testing of residence time weighting and some of the most commonly proposed algorithms (or algorithms which most...... modernalgorithms ultimately are based on), sample-and-hold and the direct spectral estimator without residence time weighting, and compare how they perform in relation to power spectra based on the equidistantly sampled reference signal. The computer generated signal is a Poisson process with a sample rate...

  18. Improved stochastic resonance algorithm for enhancement of signal-to-noise ratio of high-performance liquid chromatographic signal

    Energy Technology Data Exchange (ETDEWEB)

    Xie Shaofei [Center for Instrumental Analysis, China Pharmaceutical University, Key Laboratory of Drug Quality Control and Pharmacovigilance, Ministry of Education, Nanjing 210009 (China); Xiang Bingren [Center for Instrumental Analysis, China Pharmaceutical University, Key Laboratory of Drug Quality Control and Pharmacovigilance, Ministry of Education, Nanjing 210009 (China)]. E-mail: cpuxsf@hotmail.com; Deng Haishan [Center for Instrumental Analysis, China Pharmaceutical University, Key Laboratory of Drug Quality Control and Pharmacovigilance, Ministry of Education, Nanjing 210009 (China); Xiang Suyun [Center for Instrumental Analysis, China Pharmaceutical University, Key Laboratory of Drug Quality Control and Pharmacovigilance, Ministry of Education, Nanjing 210009 (China); Lu Jun [Center for Instrumental Analysis, China Pharmaceutical University, Key Laboratory of Drug Quality Control and Pharmacovigilance, Ministry of Education, Nanjing 210009 (China)

    2007-02-28

    Based on the theory of stochastic resonance, an improved stochastic resonance algorithm with a new criterion for optimizing system parameters to enhance signal-to-noise ratio (SNR) of HPLC/UV chromatographic signal for trace analysis was presented in this study. Compared with the conventional criterion in stochastic resonance, the proposed one can ensure satisfactory SNR as well as good peak shape of chromatographic peak in output signal. Application of the criterion to experimental weak signals of HPLC/UV was investigated and the results showed an excellent quantitative relationship between different concentrations and responses.

  19. Noise figure of microwave photonic links operating under large-signal modulation and its application to optoelectronic oscillators.

    Science.gov (United States)

    Hosseini, Seyyed Esmail; Banai, Ali

    2014-10-01

    The noise performance of intensity-modulation direct-detection microwave photonic links (MWPL) operating under large-signal conditions has been studied in this paper. A sinusoidal signal plus narrowband white Gaussian noise is applied at the radio frequency input of the link, and the output spectrum is derived using a nonlinear analytical approach. We show that the output SNR can be severely affected by the interaction of signal and noise due to the nonlinearity of the MWPL combined with the large input modulating signal. It is shown that the large-signal noise figure (NF) of an MWPL depends on the input power, a dependence that is not readily apparent under small-signal conditions, due to two unavoidable issues appearing in the large-signal conditions: (1) the link power gain is a function of its input power, and (2) the link power gain is not the same for the signal and noise due to the capture effect. We also have observed that if shot noise or laser relative intensity noise (RIN) is the dominant source of noise, link large-signal NF increases as the input signal power increases. We have shown that, when the MWPL is operating in the linear regime, our theoretical predictions approach the already published results on small-signal NF, which are verified by experimental data. We have shown that large-signal NF affects the noise performance of optoelectronic oscillators because they contain MWPLs at saturation.

  20. Hybrid computer technique yields random signal probability distributions

    Science.gov (United States)

    Cameron, W. D.

    1965-01-01

    Hybrid computer determines the probability distributions of instantaneous and peak amplitudes of random signals. This combined digital and analog computer system reduces the errors and delays of manual data analysis.

  1. Signal-to-noise analysis of time-dependent greenhouse warming experiments

    Science.gov (United States)

    Santer, Benjamin D.; Brüggemann, Wolfgang; Cubasch, Ulrich; Hasselmann, Klaus; Höck, Heinke; Maier-Reimer, Ernst; Mikolajewica, Uwe

    1994-03-01

    Results from a control integration and time-dependent greenhouse warming experiments performed with a coupled ocean-atmosphere model are analysed in terms of their signal-to-noise properties. The aim is to illustrate techniques for efficient description of the space-time evolution of signals and noise and to identify potentially useful components of a multivariate greenhouse-gas “fingerprint”. The three 100-year experiments analysed here simulate the response of the climate system to a step-function doubling of CO2 and to the time-dependent greenhouse-gas increases specified in Scenarios A (“Business as Usual”) and D (“Draconian Measures”) of the Intergovernmental Panel on Climate Change (IPCC). If signal and noise patterns are highly similar, the separation of the signal from the natural variability noise is difficult. We use the pattern correlation between the dominant Empirical Orthogonal Functions (EOFs) of the control run and the Scenario A experiment as a measure of the similarity of signal and noise patterns. The EOF 1 patterns of signal and noise are least similar for near-surface temperature and the vertical structure of zonal winds, and are most similar for sea level pressure (SLP). The dominant signal and noise modes of precipitable water and stratospheric/tropospheric temperature contrasts show considerable pattern similarity. Despite the differences in forcing history, a highly similar EOF 1 surface temperature response pattern is found in all three greenhouse warming experiments. A large part of this similarity is due to a common land-sea contrast component of the signal. To determine the degree to which the signal is contaminated by the natural variability (and/or drift) of the control run, we project the Scenario A data onto EOFs 1 and 2 of the control. Signal contamination by the EOF 1 and 2 modes of the noise is lowest for near-surface temperature, a situation favorable for detection. The signals for precipitable water, SLP, and the

  2. Probability, random variables, and random processes theory and signal processing applications

    CERN Document Server

    Shynk, John J

    2012-01-01

    Probability, Random Variables, and Random Processes is a comprehensive textbook on probability theory for engineers that provides a more rigorous mathematical framework than is usually encountered in undergraduate courses. It is intended for first-year graduate students who have some familiarity with probability and random variables, though not necessarily of random processes and systems that operate on random signals. It is also appropriate for advanced undergraduate students who have a strong mathematical background. The book has the following features: Several app

  3. Effects of traffic noise on tree frog stress levels, immunity, and color signaling.

    Science.gov (United States)

    Troïanowski, Mathieu; Mondy, Nathalie; Dumet, Adeline; Arcanjo, Caroline; Lengagne, Thierry

    2017-10-01

    During the last decade, many studies have focused on the detrimental effects of noise pollution on acoustic communication. Surprisingly, although it is known that noise exposure strongly influences health in humans, studies on wildlife remain scarce. In order to gain insight into the consequences of traffic noise exposure, we experimentally manipulated traffic noise exposure as well as the endocrine status of animals to investigate physiological and phenotypic consequences of noise pollution in an anuran species. We showed that noise exposure increased stress hormone level and induced an immunosuppressive effect. In addition, both traffic noise exposure and stress hormone application negatively impacted H. arborea vocal sac coloration. Moreover, our results suggest profound changes in sexual selection processes because the best quality males with initial attractive vocal sac coloration were the most impacted by noise. Hence, our study suggests that the recent increases in anthropogenic noise worldwide might affect a broader range of animal species than previously thought, because of alteration of visual signals and immunity. Generalizing these results to other taxa is crucial for the conservation of biodiversity in an increasingly noisy world. © 2017 Society for Conservation Biology.

  4. Reduction of randomness in seismic noise as a short-term precursor to a volcanic eruption.

    Science.gov (United States)

    Glynn, C C; Konstantinou, K I

    2016-11-24

    Ambient seismic noise is characterized by randomness incurred by the random position and strength of the noise sources as well as the heterogeneous properties of the medium through which it propagates. Here we use ambient noise data recorded prior to the 1996 Gjálp eruption in Iceland in order to show that a reduction of noise randomness can be a clear short-term precursor to volcanic activity. The eruption was preceded on 29 September 1996 by a Mw ~5.6 earthquake that occurred in the caldera rim of the Bárdarbunga volcano. A significant reduction of randomness started occurring 8 days before the earthquake and 10 days before the onset of the eruption. This reduction was observed even at stations more than 100 km away from the eruption site. Randomness increased to its previous levels 160 minutes after the Bárdarbunga earthquake, during which time aftershocks migrated from the Bárdarbunga caldera to a site near the Gjálp eruption fissure. We attribute this precursory reduction of randomness to the lack of higher frequencies (>1 Hz) in the noise wavefield caused by high absorption losses as hot magma ascended in the upper crust.

  5. Measurement and analysis of signal to noise ratio for image intensifier tube, 18mm microchannel plate

    Science.gov (United States)

    Bai, Xiaofeng; Shi, Feng; Feng, Hanliang; Liu, Rong; Yin, Lei; He, Yingping

    2011-08-01

    Output signal to noise ratio is an important technical index for evaluating detectability of microchannel plate image intensifier tube, and the characteristic for detecting of microchannel plate image intensifier tube restricts the detectability of the night vision system. It has been proved in theory and in practice that the value of output signal to noise ratio of image intensifier tube equipped for night vision system decides the farthest distance and imaging definition of system which used under low light level in square root way. In this article, method and device for measuring the output signal to noise ratio of 18mm microchannel plate image intensifier tube has been introduced in detail. Output signal to noise ratio values of several 18mm microchannel plate image intensifier tube selected have been measured. Contacting to work condition of image intensifier tube, relationship between voltage of cathode, microchannel plate, screen and output signal to noise ratio of 18mm microchannel plate image intensifier tube bas been studied, which is available for other image intensifier tube.

  6. Modeling signal-to-noise ratio of otoacoustic emissions in workers exposed to different industrial noise levels

    Directory of Open Access Journals (Sweden)

    Parvin Nassiri

    2016-01-01

    Full Text Available Introduction: Noise is considered as the most common cause of harmful physical effects in the workplace. A sound that is generated from within the inner ear is known as an otoacoustic emission (OAE. Distortion-product otoacoustic emissions (DPOAEs assess evoked emission and hearing capacity. The aim of this study was to assess the signal-to-noise ratio in different frequencies and at different times of the shift work in workers exposed to various levels of noise. It was also aimed to provide a statistical model for signal-to-noise ratio (SNR of OAEs in different frequencies based on the two variables of sound pressure level (SPL and exposure time. Materials and Methods: This case–control study was conducted on 45 workers during autumn 2014. The workers were divided into three groups based on the level of noise exposure. The SNR was measured in frequencies of 1000, 2000, 3000, 4000, and 6000 Hz in both ears, and in three different time intervals during the shift work. According to the inclusion criterion, SNR of 6 dB or greater was included in the study. The analysis was performed using repeated measurements of analysis of variance, spearman correlation coefficient, and paired samples t-test. Results: The results showed that there was no statistically significant difference between the three exposed groups in terms of the mean values of SNR (P > 0.05. Only in signal pressure levels of 88 dBA with an interval time of 10:30–11:00 AM, there was a statistically significant difference between the right and left ears with the mean SNR values of 3000 frequency (P = 0.038. The SPL had a significant effect on the SNR in both the right and left ears (P = 0.023, P = 0.041. The effect of the duration of measurement on the SNR was statistically significant in both the right and left ears (P = 0.027, P < 0.001. Conclusion: The findings of this study demonstrated that after noise exposure during the shift, SNR of OAEs reduced from the

  7. Modeling signal-to-noise ratio of otoacoustic emissions in workers exposed to different industrial noise levels.

    Science.gov (United States)

    Nassiri, Parvin; Zare, Sajad; Monazzam, Mohammad R; Pourbakht, Akram; Azam, Kamal; Golmohammadi, Taghi

    2016-01-01

    Noise is considered as the most common cause of harmful physical effects in the workplace. A sound that is generated from within the inner ear is known as an otoacoustic emission (OAE). Distortion-product otoacoustic emissions (DPOAEs) assess evoked emission and hearing capacity. The aim of this study was to assess the signal-to-noise ratio in different frequencies and at different times of the shift work in workers exposed to various levels of noise. It was also aimed to provide a statistical model for signal-to-noise ratio (SNR) of OAEs in different frequencies based on the two variables of sound pressure level (SPL) and exposure time. This case-control study was conducted on 45 workers during autumn 2014. The workers were divided into three groups based on the level of noise exposure. The SNR was measured in frequencies of 1000, 2000, 3000, 4000, and 6000 Hz in both ears, and in three different time intervals during the shift work. According to the inclusion criterion, SNR of 6 dB or greater was included in the study. The analysis was performed using repeated measurements of analysis of variance, spearman correlation coefficient, and paired samples t-test. The results showed that there was no statistically significant difference between the three exposed groups in terms of the mean values of SNR (P > 0.05). Only in signal pressure levels of 88 dBA with an interval time of 10:30-11:00 AM, there was a statistically significant difference between the right and left ears with the mean SNR values of 3000 frequency (P = 0.038). The SPL had a significant effect on the SNR in both the right and left ears (P = 0.023, P = 0.041). The effect of the duration of measurement on the SNR was statistically significant in both the right and left ears (P = 0.027, P noise exposure during the shift, SNR of OAEs reduced from the beginning to the end of the shift.

  8. Real time eye blink noise removal from EEG signals using morphological component analysis

    OpenAIRE

    Matiko, Joseph W.; Beeby, Stephen; Tudor, John

    2013-01-01

    This paper presents a method of removing the noise caused by eye blinks from an electroencephalogram (EEG) signal in real time based on morphological component analysis (MCA). This method sparsely represents both the eye blink and the EEG signal basis matrices using a Short Time Fourier Transform (STFT). This approach has two main advantages: 1) fast computation of the estimation of the signal coefficients using the basis pursuit algorithm 2) less memory requirement. The obtained result shows...

  9. Information Encoding on a Pseudo Random Noise Radar Waveform

    Science.gov (United States)

    2013-03-01

    antenna under test AWG arbitrary waveform generator AWGN additive white Gaussian noise BPSK binary phase shift keying CDMA code division multiple...focused on the orthogonal frequency-division multiplexing (OFDM) and code division multiple access ( CDMA ) waveforms. The Ohio State University has...components into a single unit allows for a more mobile compact platform. The plan is diagrammed in Figure 3.5. Figure 3.5: Planned modifications to

  10. About Cognitive Outcome Measures at Ecological Signal-to-Noise Ratios and Cognitive-Driven Hearing Aid Signal Processing.

    Science.gov (United States)

    Lunner, Thomas

    2015-06-01

    The purpose of this article is to discuss 2 questions concerning how hearing aids interact with hearing and cognition: Can signal processing in hearing aids improve memory? Can attention be used for top-down control of hearing aids? Memory recall of sentences, presented at 95% correct speech recognition, was assessed with and without binary mask noise reduction. A short literature review was performed on recent findings on new brain-imaging techniques showing potential for hearing aid control. Two experiments indicate that it is possible to show improved memory with an experimental noise reduction algorithm at ecological signal-to-noise ratios and that it is possible to replicate these findings in a new language. The literature indicates that attention-controlled hearing aids may be developed in the future.

  11. Development of an ultra low noise, miniature signal conditioning device for vestibular evoked response recordings.

    Science.gov (United States)

    Kumaragamage, Chathura L; Lithgow, Brian J; Moussavi, Zahra

    2014-01-27

    Inner ear evoked potentials are small amplitude (signals that require a low noise signal acquisition protocol for successful extraction; an existing such technique is Electrocochleography (ECOG). A novel variant of ECOG called Electrovestibulography (EVestG) is currently investigated by our group, which captures vestibular responses to a whole body tilt. The objective is to design and implement a bio-signal amplifier optimized for ECOG and EVestG, which will be superior in noise performance compared to low noise, general purpose devices available commercially. A high gain configuration is required (>85 dB) for such small signal recordings; thus, background power line interference (PLI) can have adverse effects. Active electrode shielding and driven-right-leg circuitry optimized for EVestG/ECOG recordings were investigated for PLI suppression. A parallel pre-amplifier design approach was investigated to realize low voltage, and current noise figures for the bio-signal amplifier. In comparison to the currently used device, PLI is significantly suppressed by the designed prototype (by >20 dB in specific test scenarios), and the prototype amplifier generated noise was measured to be 4.8 nV/Hz @ 1 kHz (0.45 μVRMS with bandwidth 10 Hz-10 kHz), which is lower than the currently used device generated noise of 7.8 nV/Hz @ 1 kHz (0.76 μVRMS). A low noise (noise contribution from the pre-amplifier, while maintaining the required bandwidth in high impedance measurements. Validation of the prototype device was conducted for actual ECOG recordings on humans that showed an increase (p Signal-to-Noise ratio (SNR), and for EVestG recordings using a synthetic ear model that showed a ~4% improvement (p noise and miniaturized bio-signal amplifier tailored for EVestG and ECOG. The increase in SNR for the implemented amplifier will reduce variability associated with bio-features extracted from such recordings; hence sensitivity and specificity measures associated with disease

  12. A Few Photons Among Many: Unmixing Signal and Noise for Photon-Efficient Active Imaging

    CERN Document Server

    Rapp, Joshua

    2016-01-01

    Conventional LIDAR systems require hundreds or thousands of photon detections to form accurate depth and reflectivity images. Recent photon-efficient computational imaging methods are remarkably effective with only 1.0 to 3.0 detected photons per pixel, but they are not demonstrated at signal-to-background ratio (SBR) below 1.0 because their imaging accuracies degrade significantly in the presence of high background noise. We introduce a new approach to depth and reflectivity estimation that focuses on unmixing contributions from signal and noise sources. At each pixel in an image, short-duration range gates are adaptively determined and applied to remove detections likely to be due to noise. For pixels with too few detections to perform this censoring accurately, we borrow data from neighboring pixels to improve depth estimates, where the neighborhood formation is also adaptive to scene content. Algorithm performance is demonstrated on experimental data at varying levels of noise. Results show improved perfo...

  13. Limiting characteristics of a superconducting quantum interferometer. II. Signal-to-noise ratio

    Energy Technology Data Exchange (ETDEWEB)

    Butikov, E.I.; Feofilov, S.P.

    1980-11-01

    In the approximation of small fluctuations, the spectral density of intrinsic thermal noise limiting the maximal sensitivity of a constant-current SQUID is found in the low-frequency region. The dependence of the signal-to-noise ratio on the SQUID parameters and operating conditions of an interferometer with low-frequency magnetic flux modulation is studied. Estimates are given for the smallest detectable magnetic flux corresponding to optimal operating conditions of a SQUID.

  14. Wavelet transform as a new approach to the enhancement of signal-to-noise ratio in anodic stripping voltammetry.

    Science.gov (United States)

    Prikler, Simon; Einax, Jürgen W

    2009-11-01

    De-noising signals is a frequent aim achieved by signal processing in analytical chemistry. The purpose is to enable the detection of trace concentrations of analytes. The limit of detection is defined as the lowest amount of analyte that still causes signals greater than the background noise. Appropriate de-noising decreases only the noise and maintains the measurement signal, so that signal-to-noise ratios are enhanced. One adequate mean of signal processing for this purpose is wavelet transform, which still is not a common tool in analytical chemistry. In this paper, the ability of de-noising by wavelet transform is shown for measurements in anodic stripping voltammetry using a hanging mercury drop electrode. The calculation of limits of detection and signal-to-noise ratios on the basis of peak-to-peak noise is exercised to quantify the performance of de-noising. Furthermore, signal shape with regard of easing the application of base lines is discussed. Different wavelet functions are used, and the results are compared also to Fourier transform. Coiflet2 was found out to reduce noise by the factor of 330 and is proposed as the adequate wavelet function for voltammetric and similar signals.

  15. Coil-to-coil physiological noise correlations and their impact on functional MRI time-series signal-to-noise ratio.

    Science.gov (United States)

    Triantafyllou, Christina; Polimeni, Jonathan R; Keil, Boris; Wald, Lawrence L

    2016-12-01

    Physiological nuisance fluctuations ("physiological noise") are a major contribution to the time-series signal-to-noise ratio (tSNR) of functional imaging. While thermal noise correlations between array coil elements have a well-characterized effect on the image Signal to Noise Ratio (SNR0 ), the element-to-element covariance matrix of the time-series fluctuations has not yet been analyzed. We examine this effect with a goal of ultimately improving the combination of multichannel array data. We extend the theoretical relationship between tSNR and SNR0 to include a time-series noise covariance matrix Ψt , distinct from the thermal noise covariance matrix Ψ0 , and compare its structure to Ψ0 and the signal coupling matrix SSH formed from the signal intensity vectors S. Inclusion of the measured time-series noise covariance matrix into the model relating tSNR and SNR0 improves the fit of experimental multichannel data and is shown to be distinct from Ψ0 or SSH . Time-series noise covariances in array coils are found to differ from Ψ0 and more surprisingly, from the signal coupling matrix SSH . Correct characterization of the time-series noise has implications for the analysis of time-series data and for improving the coil element combination process. Magn Reson Med 76:1708-1719, 2016. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

  16. Speech Denoising in White Noise Based on Signal Subspace Low-rank Plus Sparse Decomposition

    Directory of Open Access Journals (Sweden)

    yuan Shuai

    2017-01-01

    Full Text Available In this paper, a new subspace speech enhancement method using low-rank and sparse decomposition is presented. In the proposed method, we firstly structure the corrupted data as a Toeplitz matrix and estimate its effective rank for the underlying human speech signal. Then the low-rank and sparse decomposition is performed with the guidance of speech rank value to remove the noise. Extensive experiments have been carried out in white Gaussian noise condition, and experimental results show the proposed method performs better than conventional speech enhancement methods, in terms of yielding less residual noise and lower speech distortion.

  17. Effects of Signal-to-Noise Ratio on Auditory Cortical Frequency Processing.

    Science.gov (United States)

    Teschner, Magnus J; Seybold, Bryan A; Malone, Brian J; Hüning, Jana; Schreiner, Christoph E

    2016-03-02

    The neural mechanisms that support the robust processing of acoustic signals in the presence of background noise in the auditory system remain largely unresolved. Psychophysical experiments have shown that signal detection is influenced by the signal-to-noise ratio (SNR) and the overall stimulus level, but this relationship has not been fully characterized. We evaluated the neural representation of frequency in rat primary auditory cortex by constructing tonal frequency response areas (FRAs) in primary auditory cortex for different SNRs, tone levels, and noise levels. We show that response strength and selectivity for frequency and sound level depend on interactions between SNRs and tone levels. At low SNRs, jointly increasing the tone and noise levels reduced firing rates and narrowed FRA bandwidths; at higher SNRs, however, increasing the tone and noise levels increased firing rates and expanded bandwidths, as is usually seen for FRAs obtained without background noise. These changes in frequency and intensity tuning decreased tone level and tone frequency discriminability at low SNRs. By contrast, neither response onset latencies nor noise-driven steady-state firing rates meaningfully interacted with SNRs or overall sound levels. Speech detection performance in humans was also shown to depend on the interaction between overall sound level and SNR. Together, these results indicate that signal processing difficulties imposed by high noise levels are quite general and suggest that the neurophysiological changes we see for simple sounds generalize to more complex stimuli. Effective processing of sounds in background noise is an important feature of the mammalian auditory system and a necessary feature for successful hearing in many listening conditions. Even mild hearing loss strongly affects this ability in humans, seriously degrading the ability to communicate. The mechanisms involved in achieving high performance in background noise are not well understood. We

  18. Subfrequency noise signal extraction in fiber-optic strain sensors using postprocessing.

    Science.gov (United States)

    Lam, Timothy T-Y; Gray, Malcolm B; Shaddock, Daniel A; McClelland, David E; Chow, Jong H

    2012-06-01

    Laser frequency fluctuations typically limit the performance of high-resolution interferometric fiber strain sensors. Using time delay interferometry, we demonstrate a frequency noise immune fiber sensing system, where strain signals were extracted well below the noise floor normally imposed by the frequency fluctuations of the laser. Initial measurements show a reduction in the noise floor by a factor of 30, with strain sensitivities of a nanostrain/Hz at 100 mHz and reaching 100 ps/Hz at 1 Hz. Further characterization of the system indicates the potential for at least 4.5 orders of magnitude frequency fluctuation rejection.

  19. MEMS microphone innovations towards high signal to noise ratios (Conference Presentation) (Plenary Presentation)

    Science.gov (United States)

    Dehé, Alfons

    2017-06-01

    After decades of research and more than ten years of successful production in very high volumes Silicon MEMS microphones are mature and unbeatable in form factor and robustness. Audio applications such as video, noise cancellation and speech recognition are key differentiators in smart phones. Microphones with low self-noise enable those functions. Backplate-free microphones enter the signal to noise ratios above 70dB(A). This talk will describe state of the art MEMS technology of Infineon Technologies. An outlook on future technologies such as the comb sensor microphone will be given.

  20. Experimental Comparison of Signal Subspace Based Noise Reduction Methods

    DEFF Research Database (Denmark)

    Hansen, Peter Søren Kirk; Hansen, Per Christian; Hansen, Steffen Duus

    1999-01-01

    The signal subspace approach for non-parametric speech enhancement is considered. Several algorithms have been proposed in the literature but only partly analyzed. Here, the different algorithms are compared, and the emphasis is put onto the limiting factors and practical behavior of the estimato...

  1. Agatha: disentangling periodic signals from correlated noise in a periodogram framework

    Science.gov (United States)

    Feng, F.; Tuomi, M.; Jones, H. R. A.

    2017-10-01

    Periodograms are used as a key significance assessment and visualization tool to display the significant periodicities in unevenly sampled time series. We introduce a framework of periodograms, called `Agatha', to disentangle periodic signals from correlated noise and to solve the two-dimensional model selection problem: signal dimension and noise model dimension. These periodograms are calculated by applying likelihood maximization and marginalization and combined in a self-consistent way. We compare Agatha with other periodograms for the detection of Keplerian signals in synthetic radial velocity data produced for the radial velocity challenge as well as in radial velocity data sets of several Sun-like stars. In our tests, we find Agatha is able to recover signals to the adopted detection limit of the radial velocity challenge. Applied to real radial velocity, we use Agatha to confirm previous analysis of CoRoT-7 and to find two new planet candidates with minimum masses of 15.1 and 7.08 M⊕ orbiting HD177565 and HD41248, with periods of 44.5 and 13.4 d, respectively. We find that Agatha outperforms other periodograms in terms of removing correlated noise and assessing the significances of signals with more robust metrics. Moreover, it can be used to select the optimal noise model and to test the consistency of signals in time. Agatha is intended to be flexible enough to be applied to time series analyses in other astronomical and scientific disciplines. Agatha is available at agatha.herts.ac.uk.

  2. Noise

    Science.gov (United States)

    Noise is all around you, from televisions and radios to lawn mowers and washing machines. Normally, you ... sensitive structures of the inner ear and cause noise-induced hearing loss. More than 30 million Americans ...

  3. Real time eye blink noise removal from EEG signals using morphological component analysis.

    Science.gov (United States)

    Matiko, Joseph W; Beeby, Stephen; Tudor, John

    2013-01-01

    This paper presents a method of removing the noise caused by eye blinks from an electroencephalogram (EEG) signal in real time based on morphological component analysis (MCA). This method sparsely represents both the eye blink and the EEG signal basis matrices using a Short Time Fourier Transform (STFT). This approach has two main advantages: 1) fast computation of the estimation of the signal coefficients using the basis pursuit algorithm 2) less memory requirement. The obtained result shows that the correlation coefficient between the raw EEG and the cleaned EEG is between 0.72 and 0.94 which implies that it is possible to remove eye blink noise from the EEG signal in real time without affecting an underlying brain signal.

  4. The Miniaturization of the AFIT Random Noise Radar

    Science.gov (United States)

    2013-03-01

    Gaussian , RI = σ2n. If k is chosen to be 1/σ2, the result is simply [30] H = X∗. (2.35) In other words, the ideal filter in the presence of white noise...Virtex-5. The HDL code for the correlation algorithm consists of a combination of Verilog , schematic- based coding , and Xilinx IP Cores. Verilog is an HDL...synthesizable. In addition to Verilog coding , the Xilinx ISE includes a graphical method for representing the register-transfer level circuits needed for

  5. Application of empirical mode decomposition method for characterization of random vibration signals

    Directory of Open Access Journals (Sweden)

    Setyamartana Parman

    2016-07-01

    Full Text Available Characterization of finite measured signals is a great of importance in dynamical modeling and system identification. This paper addresses an approach for characterization of measured random vibration signals where the approach rests on a method called empirical mode decomposition (EMD. The applicability of proposed approach is tested in one numerical and experimental data from a structural system, namely spar platform. The results are three main signal components, comprising: noise embedded in the measured signal as the first component, first intrinsic mode function (IMF called as the wave frequency response (WFR as the second component and second IMF called as the low frequency response (LFR as the third component while the residue is the trend. Band-pass filter (BPF method is taken as benchmark for the results obtained from EMD method.

  6. Auto Regressive Moving Average (ARMA) Modeling Method for Gyro Random Noise Using a Robust Kalman Filter.

    Science.gov (United States)

    Huang, Lei

    2015-09-30

    To solve the problem in which the conventional ARMA modeling methods for gyro random noise require a large number of samples and converge slowly, an ARMA modeling method using a robust Kalman filtering is developed. The ARMA model parameters are employed as state arguments. Unknown time-varying estimators of observation noise are used to achieve the estimated mean and variance of the observation noise. Using the robust Kalman filtering, the ARMA model parameters are estimated accurately. The developed ARMA modeling method has the advantages of a rapid convergence and high accuracy. Thus, the required sample size is reduced. It can be applied to modeling applications for gyro random noise in which a fast and accurate ARMA modeling method is required.

  7. Signal-to-noise performance analysis of streak tube imaging lidar systems. I. Cascaded model.

    Science.gov (United States)

    Yang, Hongru; Wu, Lei; Wang, Xiaopeng; Chen, Chao; Yu, Bing; Yang, Bin; Yuan, Liang; Wu, Lipeng; Xue, Zhanli; Li, Gaoping; Wu, Baoning

    2012-12-20

    Streak tube imaging lidar (STIL) is an active imaging system using a pulsed laser transmitter and a streak tube receiver to produce 3D range and intensity imagery. The STIL has recently attracted a great deal of interest and attention due to its advantages of wide azimuth field-of-view, high range and angle resolution, and high frame rate. This work investigates the signal-to-noise performance of STIL systems. A theoretical model for characterizing the signal-to-noise performance of the STIL system with an internal or external intensified streak tube receiver is presented, based on the linear cascaded systems theory of signal and noise propagation. The STIL system is decomposed into a series of cascaded imaging chains whose signal and noise transfer properties are described by the general (or the spatial-frequency dependent) noise factors (NFs). Expressions for the general NFs of the cascaded chains (or the main components) in the STIL system are derived. The work presented here is useful for the design and evaluation of STIL systems.

  8. Analytical estimation of laser phase noise induced BER floor in coherent receiver with digital signal processing.

    Science.gov (United States)

    Vanin, Evgeny; Jacobsen, Gunnar

    2010-03-01

    The Bit-Error-Ratio (BER) floor caused by the laser phase noise in the optical fiber communication system with differential quadrature phase shift keying (DQPSK) and coherent detection followed by digital signal processing (DSP) is analytically evaluated. An in-phase and quadrature (I&Q) receiver with a carrier phase recovery using DSP is considered. The carrier phase recovery is based on a phase estimation of a finite sum (block) of the signal samples raised to the power of four and the phase unwrapping at transitions between blocks. It is demonstrated that errors generated at block transitions cause the dominating contribution to the system BER floor when the impact of the additive noise is negligibly small in comparison with the effect of the laser phase noise. Even the BER floor in the case when the phase unwrapping is omitted is analytically derived and applied to emphasize the crucial importance of this signal processing operation. The analytical results are verified by full Monte Carlo simulations. The BER for another type of DQPSK receiver operation, which is based on differential phase detection, is also obtained in the analytical form using the principle of conditional probability. The principle of conditional probability is justified in the case of differential phase detection due to statistical independency of the laser phase noise induced signal phase error and the additive noise contributions. Based on the achieved analytical results the laser linewidth tolerance is calculated for different system cases.

  9. Signal-to-noise ratio adaptive post-filtering method for intelligibility enhancement of telephone speech.

    Science.gov (United States)

    Jokinen, Emma; Yrttiaho, Santeri; Pulakka, Hannu; Vainio, Martti; Alku, Paavo

    2012-12-01

    Post-filtering can be utilized to improve the quality and intelligibility of telephone speech. Previous studies have shown that energy reallocation with a high-pass type filter works effectively in improving the intelligibility of speech in difficult noise conditions. The present study introduces a signal-to-noise ratio adaptive post-filtering method that utilizes energy reallocation to transfer energy from the first formant to higher frequencies. The proposed method adapts to the level of the background noise so that, in favorable noise conditions, the post-filter has a flat frequency response and the effect of the post-filtering is increased as the level of the ambient noise increases. The performance of the proposed method is compared with a similar post-filtering algorithm and unprocessed speech in subjective listening tests which evaluate both intelligibility and listener preference. The results indicate that both of the post-filtering methods maintain the quality of speech in negligible noise conditions and are able to provide intelligibility improvement over unprocessed speech in adverse noise conditions. Furthermore, the proposed post-filtering algorithm performs better than the other post-filtering method under evaluation in moderate to difficult noise conditions, where intelligibility improvement is mostly required.

  10. Noise estimation in voice signals using short-term cepstral analysis.

    Science.gov (United States)

    Murphy, Peter J; Akande, Olatunji O

    2007-03-01

    Cepstral-based estimation is used to provide a baseline estimate of the noise level in the logarithmic spectrum for voiced speech. A theoretical description of cepstral processing of voiced speech containing aspiration noise, together with supporting empirical data, is provided in order to illustrate the nature of the noise baseline estimation process. Taking the Fourier transform of the liftered (filtered in the cepstral domain) cepstrum produces a noise baseline estimate. It is shown that Fourier transforming the low-pass liftered cepstrum is comparable to applying a moving average (MA) filter to the logarithmic spectrum and hence the baseline receives contributions from the glottal source excited vocal tract and the noise excited vocal tract. Because the estimation process resembles the action of a MA filter, the resulting noise baseline is determined by the harmonic resolution (as determined by the temporal analysis window length) and the glottal source spectral tilt. On selecting an appropriate temporal analysis window length the estimated baseline is shown to lie halfway between the glottal excited vocal tract and the noise excited vocal tract. This information is employed in a new harmonics-to-noise (HNR) estimation technique, which is shown to provide accurate HNR estimates when tested on synthetically generated voice signals.

  11. Random Deep Belief Networks for Recognizing Emotions from Speech Signals.

    Science.gov (United States)

    Wen, Guihua; Li, Huihui; Huang, Jubing; Li, Danyang; Xun, Eryang

    2017-01-01

    Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN) can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN) method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition.

  12. Ramanujan sums for signal processing of low-frequency noise.

    Science.gov (United States)

    Planat, Michel; Rosu, Haret; Perrine, Serge

    2002-11-01

    An aperiodic (low-frequency) spectrum may originate from the error term in the mean value of an arithmetical function such as Möbius function or Mangoldt function, which are coding sequences for prime numbers. In the discrete Fourier transform the analyzing wave is periodic and not well suited to represent the low-frequency regime. In place we introduce a different signal processing tool based on the Ramanujan sums c(q)(n), well adapted to the analysis of arithmetical sequences with many resonances p/q. The sums are quasiperiodic versus the time n and aperiodic versus the order q of the resonance. Different results arise from the use of this Ramanujan-Fourier transform in the context of arithmetical and experimental signals.

  13. A microwave photonic generator of chaotic and noise signals

    Science.gov (United States)

    Ustinov, A. B.; Kondrashov, A. V.; Kalinikos, B. A.

    2016-04-01

    The transition to chaos in a microwave photonic generator has been experimentally studied for the first time, and the generated broadband chaotic microwave signal has been analyzed. The generator represented a ring circuit with the microwave tract containing a low-pass filter and a microwave amplifier. The optical tract comprised a fiber delay line. The possibility of generating chaotic oscillations with uniform spectral power density in a 3-8 GHz range is demonstrated.

  14. Training sensory signal-to-noise resolution in children with ADHD in a global mental health setting.

    Science.gov (United States)

    Mishra, J; Sagar, R; Joseph, A A; Gazzaley, A; Merzenich, M M

    2016-04-12

    Children with attention deficit/hyperactivity disorder (ADHD) have impaired focus on goal-relevant signals and fail to suppress goal-irrelevant distractions. To address both these issues, we developed a novel neuroplasticity-based training program that adaptively trains the resolution of challenging sensory signals and the suppression of progressively more challenging distractions. We evaluated this sensory signal-to-noise resolution training in a small sample, global mental health study in Indian children with ADHD. The children trained for 30 h over 6 months in a double-blind, randomized controlled trial. Training completers showed steady and significant improvements in ADHD-associated behaviors from baseline to post training relative to controls, and benefits sustained in a 6-month follow-up. Post-training cognitive assessments showed significant positive results for response inhibition and Stroop interference tests in training completers vs controls, while measures of sustained attention and short-term memory showed nonsignificant improvement trends. Further, training-driven improvements in distractor suppression correlated with the improved ADHD symptoms. This initial study suggests utility of signal-to-noise resolution training for children with ADHD; it emphasizes the need for further research on this intervention and substantially informs the design of a larger trial.

  15. Solid-state Raman quantum memory in whispering gallery mode resonators: signal-to-noise ratio

    Science.gov (United States)

    Berezhnoi, Alexander; Kalachev, Alexey

    2017-10-01

    The possibility of implementation of optical quantum memory via off-resonant Raman absorption and emission of single-photon pulses in rare-earth-ion-doped crystals is theoretically analysed taking into account signal-to-noise ratio at the output of the memory device. The crystal 143Nd3+:Y7LiF4 is considered as an example. It is shown that the signal-to-noise ratio can exceed unity for single-photon input pulses provided that storage and retrieval of them is performed in the doped crystals forming a microcavity such as whispering gallery mode resonator.

  16. Solid-state Raman quantum memory in whispering gallery mode resonators: signal-to-noise ratio

    Directory of Open Access Journals (Sweden)

    Berezhnoi Alexander

    2017-01-01

    Full Text Available The possibility of implementation of optical quantum memory via off-resonant Raman absorption and emission of single-photon pulses in rare-earth-ion-doped crystals is theoretically analysed taking into account signal-to-noise ratio at the output of the memory device. The crystal 143Nd3+:Y7LiF4 is considered as an example. It is shown that the signal-to-noise ratio can exceed unity for single-photon input pulses provided that storage and retrieval of them is performed in the doped crystals forming a microcavity such as whispering gallery mode resonator.

  17. Power Spectrum Estimation of Randomly Sampled Signals

    DEFF Research Database (Denmark)

    Velte, C. M.; Buchhave, P.; K. George, W.

    . Residence time weighting provides non-biased estimates regardless of setting. The free-running processor was also tested and compared to residence time weighting using actual LDA measurements in a turbulent round jet. Power spectra from measurements on the jet centerline and the outer part of the jet...... sine waves. The primary signal and the corresponding power spectrum are shown in Figure 1. The conventional spectrum shows multiple erroneous mixing frequencies and the peak values are too low. The residence time weighted spectrum is correct. The sample-and-hold spectrum has lower power than...... the correct spectrum, and the f -2-filtering effect appearing for low data densities is evident (Adrian and Yao 1987). The remaining tests also show that sample-and-hold and the free-running processor perform well only under very particular circumstances with high data rate and low inherent bias, respectively...

  18. Noise estimation for remote sensing image data analysis

    Science.gov (United States)

    Du, Qian

    2004-01-01

    Noise estimation does not receive much attention in remote sensing society. It may be because normally noise is not large enough to impair image analysis result. Noise estimation is also very challenging due to the randomness nature of the noise (for random noise) and the difficulty of separating the noise component from the signal in each specific location. We review and propose seven different types of methods to estimate noise variance and noise covariance matrix in a remotely sensed image. In the experiment, it is demonstrated that a good noise estimate can improve the performance of an algorithm via noise whitening if this algorithm assumes white noise.

  19. Emergence of deterministic Green's functions from noise generated by finite random sources.

    Science.gov (United States)

    Godin, Oleg A

    2009-12-01

    Two-point correlation functions of sufficiently diffuse wave fields generated by uncorrelated random sources are known to approximate deterministic Green's functions between the two points. This property is utilized increasingly for passive imaging and remote sensing of the environment. Here we show that the relation between the Green's functions and the noise cross-correlation function holds under much less restrictive conditions than previously thought. It can even hold when ambient noise sources have correlation ranges large compared to the wavelength. Admissible correlation ranges are limited from above by the size of the Fresnel zone at wave propagation between the points where noise cross correlation is evaluated.

  20. Distributed Fusion Filtering in Networked Systems with Random Measurement Matrices and Correlated Noises

    Directory of Open Access Journals (Sweden)

    Raquel Caballero-Águila

    2015-01-01

    Full Text Available The distributed fusion state estimation problem is addressed for sensor network systems with random state transition matrix and random measurement matrices, which provide a unified framework to consider some network-induced random phenomena. The process noise and all the sensor measurement noises are assumed to be one-step autocorrelated and different sensor noises are one-step cross-correlated; also, the process noise and each sensor measurement noise are two-step cross-correlated. These correlation assumptions cover many practical situations, where the classical independence hypothesis is not realistic. Using an innovation methodology, local least-squares linear filtering estimators are recursively obtained at each sensor. The distributed fusion method is then used to form the optimal matrix-weighted sum of these local filters according to the mean squared error criterion. A numerical simulation example shows the accuracy of the proposed distributed fusion filtering algorithm and illustrates some of the network-induced stochastic uncertainties that can be dealt with in the current system model, such as sensor gain degradation, missing measurements, and multiplicative noise.

  1. A method for discrimination of noise and EMG signal regions recorded during rhythmic behaviors.

    Science.gov (United States)

    Ying, Rex; Wall, Christine E

    2016-12-08

    Analyses of muscular activity during rhythmic behaviors provide critical data for biomechanical studies. Electrical potentials measured from muscles using electromyography (EMG) require discrimination of noise regions as the first step in analysis. An experienced analyst can accurately identify the onset and offset of EMG but this process takes hours to analyze a short (10-15s) record of rhythmic EMG bursts. Existing computational techniques reduce this time but have limitations. These include a universal threshold for delimiting noise regions (i.e., a single signal value for identifying the EMG signal onset and offset), pre-processing using wide time intervals that dampen sensitivity for EMG signal characteristics, poor performance when a low frequency component (e.g., DC offset) is present, and high computational complexity leading to lack of time efficiency. We present a new statistical method and MATLAB script (EMG-Extractor) that includes an adaptive algorithm to discriminate noise regions from EMG that avoids these limitations and allows for multi-channel datasets to be processed. We evaluate the EMG-Extractor with EMG data on mammalian jaw-adductor muscles during mastication, a rhythmic behavior typified by low amplitude onsets/offsets and complex signal pattern. The EMG-Extractor consistently and accurately distinguishes noise from EMG in a manner similar to that of an experienced analyst. It outputs the raw EMG signal region in a form ready for further analysis. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Method for leveling the signal-to-noise ratio in multichannel functional near-infrared spectroscopy

    Science.gov (United States)

    Yamada, Toru; Umeyama, Shinji; Kamoshida, Atsushi

    2017-02-01

    The difference in signal-to-noise ratio (SNR) within functional near-infrared spectroscopic (fNIRS)-measurement channels makes it difficult to compare the significance of the signal amplitude in an individual channel against the baseline or against signals in other channels. The difference in SNR mainly originates from the difference in light loss due to the hair coverage or the optode-scalp contact. During the initial calibration of most commercial fNIRS equipment, the detected signals in different channels are differently amplified such that the system effectively utilizes a dynamic range for measurement. While different amplification rates among the channels realize almost equal signal intensities, they also differently amplify the detection noises. This results in different apparent noises in the fNIRS signals between channels. In order to level the SNRs in all the measurement channels, the system needs to equalize the light intensities received by the detectors instead of changing the signal amplification rates. To realize this novel procedure for leveling the SNR among the channels, we developed an fNIRS system equipped with an optical attenuator at each source and detector. A systematic procedure for modulating the attenuators to level SNR over all channels was mathematically formulated, and the procedure was examined using an optical phantom with a surface covered with air.

  3. Transcranial Random Noise Stimulation (tRNS Shapes the Processing of Rapidly Changing Auditory Information

    Directory of Open Access Journals (Sweden)

    Katharina S. Rufener

    2017-06-01

    Full Text Available Neural oscillations in the gamma range are the dominant rhythmic activation pattern in the human auditory cortex. These gamma oscillations are functionally relevant for the processing of rapidly changing acoustic information in both speech and non-speech sounds. Accordingly, there is a tight link between the temporal resolution ability of the auditory system and inherent neural gamma oscillations. Transcranial random noise stimulation (tRNS has been demonstrated to specifically increase gamma oscillation in the human auditory cortex. However, neither the physiological mechanisms of tRNS nor the behavioral consequences of this intervention are completely understood. In the present study we stimulated the human auditory cortex bilaterally with tRNS while EEG was continuously measured. Modulations in the participants’ temporal and spectral resolution ability were investigated by means of a gap detection task and a pitch discrimination task. Compared to sham, auditory tRNS increased the detection rate for near-threshold stimuli in the temporal domain only, while no such effect was present for the discrimination of spectral features. Behavioral findings were paralleled by reduced peak latencies of the P50 and N1 component of the auditory event-related potentials (ERP indicating an impact on early sensory processing. The facilitating effect of tRNS was limited to the processing of near-threshold stimuli while stimuli clearly below and above the individual perception threshold were not affected by tRNS. This non-linear relationship between the signal-to-noise level of the presented stimuli and the effect of stimulation further qualifies stochastic resonance (SR as the underlying mechanism of tRNS on auditory processing. Our results demonstrate a tRNS related improvement in acoustic perception of time critical auditory information and, thus, provide further indices that auditory tRNS can amplify the resonance frequency of the auditory system.

  4. Signal-to-noise enhancement in ground-based intensity observations of solar p modes

    Science.gov (United States)

    Germain, Marvin E.

    1995-01-01

    Intensity observations of solar p modes are needed to form a complete picture of wave propagation in the photosphere. Ground-based intensity observations are severely hampered by terrestrial atmospheric noise. Partial cancellation of the noise power can be achieved if two spectra having disparate signal-to- noise ratios, and based on time series acquired simultaneously at the same site, are combined. A method of combining the spectra is suggested in which one amplitude is scaled and subtracted from the other. The result is squared yielding a positive-definite power density. To test the method, the intensity of light scattered by the Earth's atmnosphere was recorded at fifteen- second intervals in two narrow bands centered on 0.5 microns and 1.6 microns. When the two resulting spectra were combined, the noise power was attenuated by a factor of 2.7. The scale factor was varied about its optimum value, revealing that noise peaks have a different siganture than signal peaks, and opening up the possibility of a new tool in discrimination against noise peaks. Maxima at symmetry-allowed frequencies and minima at symmetry- forbidden frequencies indicate that the possibility that these results are obtained by chance is only 6.1 x 10(exp -4). The positions of these maxima and minima also support the solar-cycle dependent frequency shifts found by Palle, Regulo, and Roca Cortes.

  5. Signal to Noise Ratio Characterization of Coherent Doppler Lidar Backscattered Signals

    Directory of Open Access Journals (Sweden)

    Abdelazim Sameh

    2016-01-01

    Full Text Available An eye-safe coherent Doppler Lidar (CDL system for wind measurement was developed and tested at the Remote Sensing Laboratory of the City College of New York (CCNY. The system employs a 1542 nm fiber laser to leverage components’ availability and affordability of the telecommunication industry. A balanced detector with a bandwidth extending from dc to 125 MHz is used to eliminate the common mode relative intensity noise (RIN. The system is shot noise limited i.e., the dominant component of received signals’ noise is the shot noise. Wind velocity can be measured under nominal aerosol loading and atmospheric turbulence conditions for ranges up to 3 km while pointing vertically with 0.08 m/s precision.

  6. Signal Amplification Technique (SAT): an approach for improving resolution and reducing image noise in computed tomography

    Energy Technology Data Exchange (ETDEWEB)

    Phelps, M.E.; Huang, S.C.; Hoffman, E.J.; Plummer, D.; Carson, R.

    1981-01-01

    Spatial resolution improvements in computed tomography (CT) have been limited by the large and unique error propagation properties of this technique. The desire to provide maximum image resolution has resulted in the use of reconstruction filter functions designed to produce tomographic images with resolution as close as possible to the intrinsic detector resolution. Thus, many CT systems produce images with excessive noise with the system resolution determined by the detector resolution rather than the reconstruction algorithm. CT is a rigorous mathematical technique which applies an increasing amplification to increasing spatial frequencies in the measured data. This mathematical approach to spatial frequency amplification cannot distinguish between signal and noise and therefore both are amplified equally. We report here a method in which tomographic resolution is improved by using very small detectors to selectively amplify the signal and not noise. Thus, this approach is referred to as the signal amplification technique (SAT). SAT can provide dramatic improvements in image resolution without increases in statistical noise or dose because increases in the cutoff frequency of the reconstruction algorithm are not required to improve image resolution. Alternatively, in cases where image counts are low, such as in rapid dynamic or receptor studies, statistical noise can be reduced by lowering the cutoff frequency while still maintaining the best possible image resolution. A possible system design for a positron CT system with SAT is described.

  7. Real Time Phase Noise Meter Based on a Digital Signal Processor

    Science.gov (United States)

    Angrisani, Leopoldo; D'Arco, Mauro; Greenhall, Charles A.; Schiano Lo Morille, Rosario

    2006-01-01

    A digital signal-processing meter for phase noise measurement on sinusoidal signals is dealt with. It enlists a special hardware architecture, made up of a core digital signal processor connected to a data acquisition board, and takes advantage of a quadrature demodulation-based measurement scheme, already proposed by the authors. Thanks to an efficient measurement process and an optimized implementation of its fundamental stages, the proposed meter succeeds in exploiting all hardware resources in such an effective way as to gain high performance and real-time operation. For input frequencies up to some hundreds of kilohertz, the meter is capable both of updating phase noise power spectrum while seamlessly capturing the analyzed signal into its memory, and granting as good frequency resolution as few units of hertz.

  8. On the measurement of criterion noise in signal detection theory: the case of recognition memory.

    Science.gov (United States)

    Kellen, David; Klauer, Karl Christoph; Singmann, Henrik

    2012-07-01

    Traditional approaches within the framework of signal detection theory (SDT; Green & Swets, 1966), especially in the field of recognition memory, assume that the positioning of response criteria is not a noisy process. Recent work (Benjamin, Diaz, & Wee, 2009; Mueller & Weidemann, 2008) has challenged this assumption, arguing not only for the existence of criterion noise but also for its large magnitude and substantive contribution to individuals' performance. A review of these recent approaches for the measurement of criterion noise in SDT identifies several shortcomings and confoundings. A reanalysis of Benjamin et al.'s (2009) data sets as well as the results from a new experimental method indicate that the different forms of criterion noise proposed in the recognition memory literature are of very low magnitudes, and they do not provide a significant improvement over the account already given by traditional SDT without criterion noise. Copyright 2012 APA, all rights reserved.

  9. Signal Processing for MoC brake rattle noise of moving vehicles using prony analysis

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jae Cheol; Kwak, Yun Sang; Park, Jun Hong [Dept. of Mechanical Convergence Engineering, Hanyang University, Seoul (Korea, Republic of)

    2015-08-15

    To verify the possibility of generating rattling noise from a motor on caliper brake system, a test was conducted using a caliper excited with vibrations similar to that in a vehicle running on actual roads; this test was conducted using a quiet shaker installed in an anechoic room. After several hours of external excitation, the test assembly was loosened, and the frequency of rattling noise generation increased. A microphone was used to record the generated noise. The measured signals were analyzed by conventional spectrum analysis. Since the noise is generated as an impact response, the advantages of employing Prony analysis was discussed, and the results were compared to those obtained using conventional fast Fourier transforms. The accuracy of Prony analysis was through endurance tests on different brake systems.

  10. Internal curvature signal and noise in low- and high-level vision

    Science.gov (United States)

    Grabowecky, Marcia; Kim, Yee Joon; Suzuki, Satoru

    2011-01-01

    How does internal processing contribute to visual pattern perception? By modeling visual search performance, we estimated internal signal and noise relevant to perception of curvature, a basic feature important for encoding of three-dimensional surfaces and objects. We used isolated, sparse, crowded, and face contexts to determine how internal curvature signal and noise depended on image crowding, lateral feature interactions, and level of pattern processing. Observers reported the curvature of a briefly flashed segment, which was presented alone (without lateral interaction) or among multiple straight segments (with lateral interaction). Each segment was presented with no context (engaging low-to-intermediate-level curvature processing), embedded within a face context as the mouth (engaging high-level face processing), or embedded within an inverted-scrambled-face context as a control for crowding. Using a simple, biologically plausible model of curvature perception, we estimated internal curvature signal and noise as the mean and standard deviation, respectively, of the Gaussian-distributed population activity of local curvature-tuned channels that best simulated behavioral curvature responses. Internal noise was increased by crowding but not by face context (irrespective of lateral interactions), suggesting prevention of noise accumulation in high-level pattern processing. In contrast, internal curvature signal was unaffected by crowding but modulated by lateral interactions. Lateral interactions (with straight segments) increased curvature signal when no contextual elements were added, but equivalent interactions reduced curvature signal when each segment was presented within a face. These opposing effects of lateral interactions are consistent with the phenomena of local-feature contrast in low-level processing and global-feature averaging in high-level processing. PMID:21209356

  11. Looking for the Signal: A guide to iterative noise and artefact removal in X-ray tomographic reconstructions of porous geomaterials

    Science.gov (United States)

    Bruns, S.; Stipp, S. L. S.; Sørensen, H. O.

    2017-07-01

    X-ray micro- and nanotomography has evolved into a quantitative analysis tool rather than a mere qualitative visualization technique for the study of porous natural materials. Tomographic reconstructions are subject to noise that has to be handled by image filters prior to quantitative analysis. Typically, denoising filters are designed to handle random noise, such as Gaussian or Poisson noise. In tomographic reconstructions, noise has been projected from Radon space to Euclidean space, i.e. post reconstruction noise cannot be expected to be random but to be correlated. Reconstruction artefacts, such as streak or ring artefacts, aggravate the filtering process so algorithms performing well with random noise are not guaranteed to provide satisfactory results for X-ray tomography reconstructions. With sufficient image resolution, the crystalline origin of most geomaterials results in tomography images of objects that are untextured. We developed a denoising framework for these kinds of samples that combines a noise level estimate with iterative nonlocal means denoising. This allows splitting the denoising task into several weak denoising subtasks where the later filtering steps provide a controlled level of texture removal. We describe a hands-on explanation for the use of this iterative denoising approach and the validity and quality of the image enhancement filter was evaluated in a benchmarking experiment with noise footprints of a varying level of correlation and residual artefacts. They were extracted from real tomography reconstructions. We found that our denoising solutions were superior to other denoising algorithms, over a broad range of contrast-to-noise ratios on artificial piecewise constant signals.

  12. Analysis of biomedical signals by flicker-noise spectroscopy : identification of photosensitive epilepsy using magnetoencephalograms

    OpenAIRE

    Timashev, S. F.; Polyakov, Yu. S.; Yulmetyev, R. M.; Demin, S. A.; Panischev, O. Yu.; Shimojo, S.; Bhattacharya, J

    2009-01-01

    The flicker-noise spectroscopy (FNS) approach is used to determine the dynamic characteristics of neuromagnetic responses by analyzing the magnetoencephalographic (MEG) signals recorded as the response of a group of control human subjects and a patient with photosensitive epilepsy (PSE) to equiluminant flickering stimuli of different color combinations. Parameters characterizing the analyzed stochastic biomedical signals for different frequency bands are identified. It is shown that the class...

  13. Cramer-Rao bounds for signal-to-noise ratio and combiner weight estimation

    Science.gov (United States)

    Dolinar, S. J.

    1986-01-01

    Cramer-Rao lower bounds on estimator variance are calculated for arbitrary unbiased estimates of signal-to-noise ratio and combiner weight parameters. Estimates are assumed to be based on a discrete set of observables obtained by matched filtering of a biphase modulated signal. The bounds are developed first for a problem model based on one observable per channel symbol period, and then extended to a more general problem in which subperiod observables are also available.

  14. Relationship Among Signal Fidelity, Hearing Loss, and Working Memory for Digital Noise Suppression.

    Science.gov (United States)

    Arehart, Kathryn; Souza, Pamela; Kates, James; Lunner, Thomas; Pedersen, Michael Syskind

    2015-01-01

    This study considered speech modified by additive babble combined with noise-suppression processing. The purpose was to determine the relative importance of the signal modifications, individual peripheral hearing loss, and individual cognitive capacity on speech intelligibility and speech quality. The participant group consisted of 31 individuals with moderate high-frequency hearing loss ranging in age from 51 to 89 years (mean = 69.6 years). Speech intelligibility and speech quality were measured using low-context sentences presented in babble at several signal-to-noise ratios. Speech stimuli were processed with a binary mask noise-suppression strategy with systematic manipulations of two parameters (error rate and attenuation values). The cumulative effects of signal modification produced by babble and signal processing were quantified using an envelope-distortion metric. Working memory capacity was assessed with a reading span test. Analysis of variance was used to determine the effects of signal processing parameters on perceptual scores. Hierarchical linear modeling was used to determine the role of degree of hearing loss and working memory capacity in individual listener response to the processed noisy speech. The model also considered improvements in envelope fidelity caused by the binary mask and the degradations to envelope caused by error and noise. The participants showed significant benefits in terms of intelligibility scores and quality ratings for noisy speech processed by the ideal binary mask noise-suppression strategy. This benefit was observed across a range of signal-to-noise ratios and persisted when up to a 30% error rate was introduced into the processing. Average intelligibility scores and average quality ratings were well predicted by an objective metric of envelope fidelity. Degree of hearing loss and working memory capacity were significant factors in explaining individual listener's intelligibility scores for binary mask processing

  15. Optimized Signal-To Ratio with Shot Noise Limited Detection in Stimulated Raman Scattering Microscopy

    Science.gov (United States)

    Moester, M. J. B.; Ariese, F.; de Boer, J. F.

    2015-04-01

    We describe our set-up for Stimulated Raman Scattering (SRS) microscopy with shot noise limited detection for a broad window of biologically relevant laser powers. This set-up is used to demonstrate that the highest signal-to-noise ratio (SNR) in SRS with shot noise limited detection is achieved with a time-averaged laser power ratio of 1:2 of the unmodulated and modulated beam. In SRS, two different coloured laser beams are incident on a sample. If the energy difference between them matches a molecular vibration of a molecule, energy can be transferred from one beam to the other. By applying amplitude modulation to one of the beams, the modulation transfer to the other beam can be measured. The efficiency of this process is a direct measure for the number of molecules of interest in the focal volume. Combined with laser scanning microscopy, this technique allows for fast and sensitive imaging with sub-micrometre resolution. Recent technological advances have resulted in an improvement of the sensitivity of SRS applications, but few show shot noise limited detection. The dominant noise source in this SRS microscope is the shot noise of the unmodulated, detected beam. Under the assumption that photodamage is linear with the total laser power, the optimal SNR shifts away from equal beam powers, where the most signal is generated, to a 1:2 power ratio. Under these conditions the SNR is maximized and the total laser power that could induce photodamage is minimized. Compared to using a 1:1 laser power ratio, we show improved image quality and a signal-to-noise ratio improvement of 8 % in polystyrene beads and C. Elegans worms. Including a non-linear damage mechanism in the analysis, we find that the optimal power ratio converges to a 1:1 ratio with increasing order of the non-linear damage mechanism.

  16. Analysis of Signal-to-Noise Ratio of the Laser Doppler Velocimeter

    DEFF Research Database (Denmark)

    Lading, Lars

    1973-01-01

    The signal-to-shot-noise ratio of the photocurrent of a laser Doppler anemometer is calculated as a function of the parameters which describe the system. It is found that the S/N is generally a growing function of receiver area, that few large particles are better than many small ones, and that g...

  17. Signal-to-Noise ratio and design complexity based on Unified Loss ...

    African Journals Online (AJOL)

    Taguchi's quality loss function for larger-the-better performance characteristics uses a reciprocal transformation to compute quality loss. This paper suggests that reciprocal transformation unnecessarily complicates and may distort results. Examples of this distortion include the signal-to-noise ratio based on mean squared ...

  18. Visual Motherese? Signal-to-Noise Ratios in Toddler-Directed Television

    Science.gov (United States)

    Wass, Sam V.; Smith, Tim J.

    2015-01-01

    Younger brains are noisier information processing systems; this means that information for younger individuals has to allow clearer differentiation between those aspects that are required for the processing task in hand (the "signal") and those that are not (the "noise"). We compared toddler-directed and adult-directed TV…

  19. Separating the signal from the noise: Expanding flow cytometry into the sub-micron range.

    Science.gov (United States)

    Cytometry Part A Special Section: Separating the signal from the noise: Expanding flow cytometry into the sub-micron range. The current Cytometry Part A Special Section presents three studies that utilize cytometers to study sub-micron particles. The three studies involve the 1...

  20. Trade-offs and noise tolerance in signal detection by genetic circuits.

    Directory of Open Access Journals (Sweden)

    Raúl Guantes

    Full Text Available Genetic circuits can implement elaborated tasks of amplitude or frequency signal detection. What type of constraints could circuits experience in the performance of these tasks, and how are they affected by molecular noise? Here, we consider a simple detection process-a signal acting on a two-component module-to analyze these issues. We show that the presence of a feedback interaction in the detection module imposes a trade-off on amplitude and frequency detection, whose intensity depends on feedback strength. A direct interaction between the signal and the output species, in a type of feed-forward loop architecture, greatly modifies these trade-offs. Indeed, we observe that coherent feed-forward loops can act simultaneously as good frequency and amplitude noise-tolerant detectors. Alternatively, incoherent feed-forward loop structures can work as high-pass filters improving high frequency detection, and reaching noise tolerance by means of noise filtering. Analysis of experimental data from several specific coherent and incoherent feed-forward loops shows that these properties can be realized in a natural context. Overall, our results emphasize the limits imposed by circuit structure on its characteristic stimulus response, the functional plasticity of coherent feed-forward loops, and the seemingly paradoxical advantage of improving signal detection with noisy circuit components.

  1. Trade-offs and noise tolerance in signal detection by genetic circuits.

    Science.gov (United States)

    Guantes, Raúl; Estrada, Javier; Poyatos, Juan F

    2010-08-26

    Genetic circuits can implement elaborated tasks of amplitude or frequency signal detection. What type of constraints could circuits experience in the performance of these tasks, and how are they affected by molecular noise? Here, we consider a simple detection process-a signal acting on a two-component module-to analyze these issues. We show that the presence of a feedback interaction in the detection module imposes a trade-off on amplitude and frequency detection, whose intensity depends on feedback strength. A direct interaction between the signal and the output species, in a type of feed-forward loop architecture, greatly modifies these trade-offs. Indeed, we observe that coherent feed-forward loops can act simultaneously as good frequency and amplitude noise-tolerant detectors. Alternatively, incoherent feed-forward loop structures can work as high-pass filters improving high frequency detection, and reaching noise tolerance by means of noise filtering. Analysis of experimental data from several specific coherent and incoherent feed-forward loops shows that these properties can be realized in a natural context. Overall, our results emphasize the limits imposed by circuit structure on its characteristic stimulus response, the functional plasticity of coherent feed-forward loops, and the seemingly paradoxical advantage of improving signal detection with noisy circuit components.

  2. Signal-to-noise ratio of FT-IR CO gas spectra

    DEFF Research Database (Denmark)

    Bak, J.; Clausen, Sønnik

    1999-01-01

    The minimum amount of a gaseous compound which can be detected and quantified with Fourier transform infrared (FT-IR) spectrometers depends on the signal-to-noise ratio (SNR) of the measured gas spectra. In order to use low-resolution FT-IR spectrometers to measure combustion gases like CO and CO2...

  3. Numerical modelling of the pump-to-signal relative intensity noise ...

    Indian Academy of Sciences (India)

    An accurate numerical model to investigate the pump-to-signal relative intensity noise (RIN) transfer in two-pump fibre optical parametric amplifiers (2-P FOPAs) for low ... Department of Physics, College of Sciences, Shiraz University, Shiraz 71454, Iran; Department of Physics, College of Sciences, Shiraz University of ...

  4. Characterization of transient noise in Advanced LIGO relevant to gravitational wave signal GW150914

    NARCIS (Netherlands)

    Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adamo, M.; Adams, C.; Phythian-Adams, A.T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Aggarwal, N.T.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Allen, B.; Allocca, A.; Altin, P. A.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Araya, M. C.; Arceneaux, C. C.; Areeda, J. S.; Arnaud, N.; Arun, K. G.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Babak, S.; Bacon, P.; Bader, M. K. M.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, R.D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Baune, C.; Bavigadda, V.; Bazzan, M.; Behnke, B.; Bejger, M.; Bell, A. S.; Bell, C. J.; Berger, B. K.; Bergman, J.; Bergmann, G.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Birch, M.J.; Birney, R.; Biscans, S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blackburn, L.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, A.L.S.; Bock, O.; Bodiya, T. P.; Boer, M.; Bogaert, J.G.; Bogan, C.; Bohe, A.; Bojtos, P.; Bond, T.C; Bondu, F.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; Brooks, A. F.; Brown, A.D.; Brown, D.; Brown, N. M.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Calderon Bustillo, J.; Callister, T. A.; Calloni, E.; Camp, J. B.; Cannon, K. C.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Diaz, J. Casanueva; Casentini, C.; Caudill, S.; Cavaglia, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Baiardi, L. Cerboni; Cerretani, G.; Cesarini, E.; Chakraborty, R.; Chalermsongsak, T.; Chamberlin, S. J.; Chan, M.; Chao, D. S.; Charlton, P.; Charlton, P.; Chassande-Mottin, E.; Chatterji, S.; Chen, H. Y.; Chen, Y; Cheng, C.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Qian; Chua, S. E.; Chung, E.S.; Ciani, G.; Clara, F.; Clark, J. A.; Cleva, F.; Coccia, E.; Cohadon, P. -F.; Colla, A.; Collette, C. G.; Cominsky, L.; Conte, A.; Conti, L.; Cook, D.; Corbitt, T. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, A.C.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J. -P.; Countryman, S. T.; Couvares, P.; Cowan, E. E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Craig, K.; Creighton, J. D. E.; Cripe, J.; Crowder, S. G.; Cumming, A.; Cunningham, A.L.; Cuoco, E.; Dal Canton, T.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Darman, N. S.; Dattilo, V.; Dave, I.; Daveloza, H. P.; Davier, M.; Davies, G. S.; Daw, E. J.; Day, R.; Debra, D.; Debreczeni, G.; Degallaix, J.; De laurentis, M.; Deleglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dereli, H.; Dergachev, V.A.; DeRosa, R. T.; Rosa, R.; DeSalvo, R.; Dhurandhar, S.; Diaz, M. C.; Di Fiore, L.; Giovanni, M.G.; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Virgilio, A.; Dojcinoski, G.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Douglas, R.; Downes, T. P.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Ducrot, M.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H. -B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Engels, W.; Essick, R. C.; Etzel, T.; Evans, T. M.; Evans, T. M.; Everett, R.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.M.; Fang, Q.; Farinon, S.; Farr, B.; Farr, W. M.; Favata, M.; Fays, M.; Fehrmann, H.; Fejer, M. M.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Fiori, I.; Fiorucci, D.; Fisher, R. P.; Flaminio, R.; Fletcher, M; Fournier, J. -D.; Franco, S; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fricke, T. T.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H. A. G.; Gair, J. R.; Gammaitoni, L.; Gaonkar, S. G.; Garufi, F.; Gatto, A.; Gaur, G.; Gehrels, N.; Gemme, G.; Gendre, B.; Genin, E.; Gennai, A.; George, J.; Gergely, L.; Ghosh, V. Germain Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.P.; Glaefke, A.; Goetz, E.; Goetz, R.; Gondan, L.; Gonzlez, G.; Castro, J. M. Gonzalez; Gopakumar, A.; Gordon, N. A.; Gorodetsky, M. L.; Gossan, S. E.; Lee-Gosselin, M.; Gouaty, R.; Graef, C.; Graff, P. B.; Granata, M.; Grant, A.; Gras, S.; Gray, C.M.; Greco, G.; Green, A. C.; Groot, P.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hacker, J. J.; Buffoni-Hall, R.; Hall, E. D.; Hammond, G.L.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hanson, P.J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Hartman, M. T.; Haster, C. -J.; Haughian, K.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hoak, D.; Hodge, K. A.; Hofman, D.; Hollitt, S. E.; Holt, K.; Holz, D. E.; Hopkins, P.; Hosken, D. J.; Hough, J.; Houston, E. A.; Howell, E. J.; Hu, Y. M.; Huang, S.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Idrisy, A.; Indik, N.; Ingram, D. R.; Inta, R.; Isa, H. N.; Isac, J. -M.; Isi, M.; Islas, G.; Isogai, T.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jang, D.H.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jimenez-Forteza, F.; Johnson, W.; Jones, I.D.; Jones, R.; Jonker, R. J. G.; Ju, L.; Haris, K.; Kalaghatgi, C. V.; Kalogera, V.; Kandhasamy, S.; Kang, G.H.; Kanner, J. B.; Karki, S.; Kasprzack, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kaur, T.; Kawabe, K.; Kawazoe, F.; Kefelian, F.; Kehl, M. S.; Keitel, D.; Kelley, D. B.; Kells, W.; Kennedy, R.E.; Key, J. S.; Khalaidovski, A.; Khalili, F. Y.; Khan, I.; Khan., S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, C.; Kim, J.; Kim, K.; Kim, Nam-Gyu; Kim, Namjun; Kim, Y.M.; King, E. J.; King, P. J.; Kinzel, D. L.; Kissel, J. S.; Kleybolte, L.; Klimenko, S.; Koehlenbeck, S. M.; Kokeyama, K.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Kringel, V.; Krishnan, B.; Krolak, A.; Krueger, C.; Kuehn, G.; Kumar, P.; Kuo, L.; Kutynia, A.; Lackey, B. D.; Landry, M.; Lange, J.; Lantz, B.; Lasky, P. D.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lebigot, E. O.; Lee, C.H.; Lee, K.H.; Lee, M.H.; Lee, K.; Lenon, A.; Leonardi, M.; Leong, J. R.; Leroy, N.; Letendre, N.; Levin, Y.; Levine, B. M.; Li, T. G. F.; Libson, A.; Littenberg, T. B.; Lockerbie, N. A.; Logue, J.; Lombardi, A. L.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lueck, H.; Lundgren, A. P.; Luo, J.; Lynch, R.; Ma, Y.; MacDonald, T.T.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magana-Sandoval, F.; Magee, R. M.; Mageswaran, M.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Mandel, I.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Marka, S.; Marka, Z.; Markosyan, A. S.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martin, R.M.; Martynov, D. V.; Marx, J. N.; Mason, K.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; Mazzolo, G.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Meidam, J.; Melatos, A.; Mendell, G.; Mendoza-Gandara, D.; Mercer, R. A.; Merilh, E. L.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, J.; Millhouse, M.; Minenkov, Y.; Ming, J.; Mirshekari, S.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moggi, A.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, B.C.; Moore, J.C.; Moraru, D.; Gutierrez Moreno, M.; Morriss, S. R.; Mossavi, K.; Mours, B.; Mow-Lowry, C. M.; Mueller, C. L.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, S.D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Murphy, D. J.; Murray, P.G.; Mytidis, A.; Nardecchia, I.; Naticchioni, L.; Nayak, R. K.; Necula, V.; Nedkova, K.; Nelemans, G.; Gutierrez-Neri, M.; Neunzert, A.; Newton-Howes, G.; Nguyen, T. T.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Nocera, F.; Nolting, D.; Normandin, M. E. N.; Nuttall, L. K.; Oberling, J.; Ochsner, E.; O'Dell, J.; Oelker, E.; Ogin, G. H.; Oh, J.; Oh, S. H.; Ohme, F.; Oliver, M. B.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; O'Shaughnessy, R.; Ottaway, D. J.; Ottens, R. S.; Overmier, H.; Owen, B. J.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Paris, H. R.; Parker, W.S; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patricelli, B.; Patrick, Z.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perreca, A.; Phelps, M.; Piccinni, O. J.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poggiani, R.; Popolizio, P.; Post, A.; Powell, J.; Prasad, J.; Predoi, V.; Premachandra, S. S.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L. G.; Puncken, O.; Punturo, M.; Puppo, P.; Puerrer, M.; Qi, H.; Qin, J.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rakhmanov, M.; Rapagnani, P.; Raymond, V.; Razzano, M.; Re, V.; Read, J.; Reed, C. M.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Rew, H.; Reyes, S. D.; Ricci, F.; Riles, K.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, R.; Romanov, G.; Romie, J. H.; Rosinska, D.; Rowan, S.; Ruediger, A.; Ruggi, P.; Ryan, K.A.; Sachdev, P.S.; Sadecki, T.; Sadeghian, L.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sanchez, E. J.; Sandberg, V.; Sandeen, B.; Sanders, J. R.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Sauter, O.; Savage, R. L.; Sawadsky, A.; Schale, P.; Schilling, R.; Schmidt, J; Schmidt, P.; Schnabel, R.B.; Schofield, R. M. S.; Schoenbeck, A.; Schreiber, K.E.C.; Schuette, D.; Schutz, B. F.; Scott, J.; Scott, M.S.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Serna, G.; Setyawati, Y.; Sevigny, A.; Shaddock, D. A.; Shah, S.; Shahriar, M. S.; Shaltev, M.; Shao, Z.M.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sigg, D.; Silva, António Dias da; Simakov, D.; Singer, A; Singer, L. P.; Singh, A.; Singh, R.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Slutsky, J.; Smith, R. J. E.; Smith, N.D.; Smith, R. J. E.; Son, E. J.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Srivastava, A. K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Stone, J.R.; Strain, K. A.; Straniero, N.; Stratta, G.; Strauss, N. A.; Strigin, S. E.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sutton, P. J.; Swinkels, B. L.; Szczepanczyk, M. J.; Tacca, M.D.; Talukder, D.; Tanner, D. B.; Tapai, M.; Tarabrin, S. P.; Taracchini, A.; Taylor, W.R.; Theeg, T.; Thirugnanasambandam, M. P.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Tomlinson, C.; Tonelli, M.; Torres, C. V.; Torrie, C. I.; Toyra, D.; Travasso, F.; Traylor, G.; Trifiro, D.; Tringali, M. C.; Trozzo, L.; Tse, M.; Turconi, M.; Tuyenbayev, D.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Valdes, G.; van Bakel, N.; Van Beuzekom, Martin; van den Brand, J. F. J.; Van Den Broeck, C.F.F.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Vass, S.; Vasuth, M.; Vaulin, R.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P.J.; Venkateswara, K.; Verkindt, D.; Vetrano, F.; Vicere, A.; Vinciguerra, S.; Vine, D. J.; Vinet, J. -Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Voss, D. V.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, MT; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, M.; Wang, X.; Wang, Y.; Ward, R. L.; Warner, J.; Was, M.; Weaver, B.; Wei, L. -W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Welborn, T.; Wen, L.M.; Wessels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; Whitcomb, S. E.; White, D. J.; Whiting, B. F.; Williams, D.R.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Worden, J.; Wright, J.L.; Wu, G.; Yablon, J.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yap, M. J.; Yu, H.; Yvert, M.; Zadrozny, A.; Zangrando, L.; Zanolin, M.; Zendri, J. -P.; Zevin, M.; Zhang, F.; Zhang, L.; Zhang, M.; Zhang, Y.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, X. J.; Zotov, N.; Zucker, M. E.; Zuraw, S. E.; Zweizig, J.

    2016-01-01

    On 14 September 2015, a gravitational wave signal from a coalescing black hole binary system was observed by the Advanced LIGO detectors. This paper describes the transient noise backgrounds used to determine the significance of the event (designated GW150914) and presents the results of

  5. Signal Analysis of Helicopter Blade-Vortex-Interaction Acoustic Noise Data

    Science.gov (United States)

    Rogers, James C.; Dai, Renshou

    1998-01-01

    Blade-Vortex-Interaction (BVI) produces annoying high-intensity impulsive noise. NASA Ames collected several sets of BVI noise data during in-flight and wind tunnel tests. The goal of this work is to extract the essential features of the BVI signals from the in-flight data and examine the feasibility of extracting those features from BVI noise recorded inside a large wind tunnel. BVI noise generating mechanisms and BVI radiation patterns an are considered and a simple mathematical-physical model is presented. It allows the construction of simple synthetic BVI events that are comparable to free flight data. The boundary effects of the wind tunnel floor and ceiling are identified and more complex synthetic BVI events are constructed to account for features observed in the wind tunnel data. It is demonstrated that improved recording of BVI events can be attained by changing the geometry of the rotor hub, floor, ceiling and microphone. The Euclidean distance measure is used to align BVI events from each blade and improved BVI signals are obtained by time-domain averaging the aligned data. The differences between BVI events for individual blades are then apparent. Removal of wind tunnel background noise by optimal Wiener-filtering is shown to be effective provided representative noise-only data have been recorded. Elimination of wind tunnel reflections by cepstral and optimal filtering deconvolution is examined. It is seen that the cepstral method is not applicable but that a pragmatic optimal filtering approach gives encouraging results. Recommendations for further work include: altering measurement geometry, real-time data observation and evaluation, examining reflection signals (particularly those from the ceiling) and performing further analysis of expected BVI signals for flight conditions of interest so that microphone placement can be optimized for each condition.

  6. Signal processing in a randomly time varying system.

    Science.gov (United States)

    Adomian, G.

    1972-01-01

    Stochastic operators are applied to an analysis of some deterministic systems of signal transformation. The distribution of a random process at the output of a system is given through its distribution at the input and through a stochastic Green's function. A two-point correlation function is derived to obtain a solution to differential equations which contain coefficients, boundary conditions, or right-hand terms representing random processes.

  7. Finding signal in the noise: Analyzing low signal-to-noise galaxy spectra & optimizing the Robert Stobie Spectrograph's Near InfraRed detector system

    Science.gov (United States)

    Mosby, Gregory, Jr.

    Ground-based optical and near infrared observational astronomy is naturally limited by the Earth's atmosphere and the vast distances of the objects to be studied. Technically, we are also limited by the precision and accuracy of our instrumentation. In this thesis, I describe strategies to move observational astronomy forward in light of these limitations. Specifically, I present a method of stellar population analysis that is precise and accurate in the limit of low signal-to-noise with an emphasis on faint quasar host galaxy spectra. I present an investigation and test of a simple model of persistence in HgCdTe detector arrays aimed at the removal of this spurious signal from data. Finally, I present an overview of the Robert Stobie Spectrograph Near InfraRed (RSS-NIR) instrument's detector system that I have optimized for low read noise and background limited performance. The advancement of observational astronomy will always be limited by our ability to efficiently detect the signals we need. This thesis reviews the progress made to enhance ground-based astronomy capability.

  8. Multichannel active control of random noise in a small reverberant room

    DEFF Research Database (Denmark)

    Laugesen, Søren; Elliott, Stephen J.

    1993-01-01

    An algorithm for multichannel adaptive IIR (infinite impulse response) filtering is presented and applied to the active control of broadband random noise in a small reverberant room. Assuming complete knowledge of the primary noise, the theoretically optimal reductions of acoustic energy...... with the primary noise field generated by a panel excited by a loudspeaker in an adjoining room. These results show that far better performances are provided by IIR and FIR filters when the primary source has a lightly damped dynamic behavior which the active controller must model...... multichannel FIR (finite impulse response) and IIR filters are then compared for a four-secondary-source, eight-error microphone active control system, and it is found that for the present application FIR filters are sufficient when the primary noise source is a loudspeaker. Some experiments are then presented...

  9. Robustness of digitally modulated signal features against variation in HF noise model

    Directory of Open Access Journals (Sweden)

    Shoaib Mobien

    2011-01-01

    Full Text Available Abstract High frequency (HF band has both military and civilian uses. It can be used either as a primary or backup communication link. Automatic modulation classification (AMC is of an utmost importance in this band for the purpose of communications monitoring; e.g., signal intelligence and spectrum management. A widely used method for AMC is based on pattern recognition (PR. Such a method has two main steps: feature extraction and classification. The first step is generally performed in the presence of channel noise. Recent studies show that HF noise could be modeled by Gaussian or bi-kappa distributions, depending on day-time. Therefore, it is anticipated that change in noise model will have impact on features extraction stage. In this article, we investigate the robustness of well known digitally modulated signal features against variation in HF noise. Specifically, we consider temporal time domain (TTD features, higher order cumulants (HOC, and wavelet based features. In addition, we propose new features extracted from the constellation diagram and evaluate their robustness against the change in noise model. This study is targeting 2PSK, 4PSK, 8PSK, 16QAM, 32QAM, and 64QAM modulations, as they are commonly used in HF communications.

  10. Symbol signal-to-noise ratio loss in square-wave subcarrier downconversion

    Science.gov (United States)

    Feria, Y.; Statman, J.

    1993-01-01

    This article presents the simulated results of the signal-to-noise ratio (SNR) loss in the process of a square-wave subcarrier down conversion. In a previous article, the SNR degradation was evaluated at the output of the down converter based on the signal and noise power change. Unlike in the previous article, the SNR loss is defined here as the difference between the actual and theoretical symbol SNR's for the same symbol-error rate at the output of the symbol matched filter. The results show that an average SNR loss of 0.3 dB can be achieved with tenth-order infinite impulse response (IIR) filters. This loss is a 0.2-dB increase over the SNR degradation in the previous analysis where neither the signal distortion nor the symbol detector was considered.

  11. Adaptive Filtering for FSCW Signal-to-noise Ratio Enhancement of SAW Interrogation Units

    Directory of Open Access Journals (Sweden)

    Díaz Luis

    2016-01-01

    Full Text Available A digital filter that improves the signal-to-noise ratio of the response of a FSCW (Frequency Stepped Continuous Wave scheme is presented. An improvement in signal-to-noise ratio represents an enhanced readout distance. This work considers this architecture as an interrogation unit for SAW tags with time and phase encoding. The parameters of the proposed digital filter, which is a non-linear edge preserving filter, were studied and tested for this specific application. An improvement of around 20dB in the SNR level was achieved. This filter preserves the phase of the signal at the time position of the reflectors, which is critical for correct identification of the code in phase encoding schemes.

  12. Signal analysis of voltage noise in welding arcs. [gas tungsten arc welding

    Science.gov (United States)

    Elis, E.; Eagar, T. W.

    1982-01-01

    Gas tungsten arc welds were made on low alloy steel plates to which intentional defects (discontinuities) were imposed. Disruption of shielding gas, welding over surface films, and tack welds produce changes in what is otherwise a relatively uniform voltage signal. The arc voltage was 15 volts + or - 2 volts with 300 mV ripple noise from the power supply. Changes in this steady noise voltage varied from 50 mV to less than one millivolt depending on the severity and the type of change experienced. In some instances the changes were easily detected by analysis of the signal in real time, while in other cases the signal had to transformed to the frequency domain in order to detect the changes. Discontinuities as small as 1.5 mm in length were detected. The ultimate sensitivity and reproducibility of the technique is still being investigated.

  13. Optimal causal filtering for 1 /fα-type noise in single-electrode EEG signals.

    Science.gov (United States)

    Paris, Alan; Atia, George; Vosoughi, Azadeh; Berman, Stephen A

    2016-08-01

    Understanding the mode of generation and the statistical structure of neurological noise is one of the central problems of biomedical signal processing. We have developed a broad class of abstract biological noise sources we call hidden simplicial tissues. In the simplest cases, such tissue emits what we have named generalized van der Ziel-McWhorter (GVZM) noise which has a roughly 1/fα spectral roll-off. Our previous work focused on the statistical structure of GVZM frequency spectra. However, causality of processing operations (i.e., dependence only on the past) is an essential requirement for real-time applications to seizure detection and brain-computer interfacing. In this paper we outline the theoretical background for optimal causal time-domain filtering of deterministic signals embedded in GVZM noise. We present some of our early findings concerning the optimal filtering of EEG signals for the detection of steady-state visual evoked potential (SSVEP) responses and indicate the next steps in our ongoing research.

  14. EigenPrism: inference for high dimensional signal-to-noise ratios.

    Science.gov (United States)

    Janson, Lucas; Barber, Rina Foygel; Candès, Emmanuel

    2017-09-01

    Consider the following three important problems in statistical inference, namely, constructing confidence intervals for (1) the error of a high-dimensional (p > n) regression estimator, (2) the linear regression noise level, and (3) the genetic signal-to-noise ratio of a continuous-valued trait (related to the heritability). All three problems turn out to be closely related to the little-studied problem of performing inference on the [Formula: see text]-norm of the signal in high-dimensional linear regression. We derive a novel procedure for this, which is asymptotically correct when the covariates are multivariate Gaussian and produces valid confidence intervals in finite samples as well. The procedure, called EigenPrism, is computationally fast and makes no assumptions on coefficient sparsity or knowledge of the noise level. We investigate the width of the EigenPrism confidence intervals, including a comparison with a Bayesian setting in which our interval is just 5% wider than the Bayes credible interval. We are then able to unify the three aforementioned problems by showing that the EigenPrism procedure with only minor modifications is able to make important contributions to all three. We also investigate the robustness of coverage and find that the method applies in practice and in finite samples much more widely than just the case of multivariate Gaussian covariates. Finally, we apply EigenPrism to a genetic dataset to estimate the genetic signal-to-noise ratio for a number of continuous phenotypes.

  15. Temporal profile of gene transcription noise modulated by cross-talking signal transduction pathways.

    Science.gov (United States)

    Sun, Qiwen; Tang, Moxun; Yu, Jianshe

    2012-02-01

    Gene transcription is a central cellular process and is stochastic in nature. The stochasticity has been studied in real cells and in theory, but often for the transcription activated by a single signaling pathway at steady-state. As transcription of many genes is involved with multiple pathways, we investigate how the transcription efficiency and noise is modulated by cross-talking pathways. We model gene transcription as a renewal process for which the gene can be turned on by different pathways. We determine the transcription efficiency by solving a system of differential equations, and obtain the mathematical formula of the noise strength by the Laplace transform and standard techniques in renewal theory. Our numerical examples demonstrate that cross-talking pathways are capable of inducing more cells to transcribe than the steady-state level after a short time period of signal transduction, and creating exceedingly high stationary transcription noise strength. In contrast, it is shown that one signaling pathway alone is unable to do so. Very strikingly, it is observed that the noise strength varies gradually over most values of the system parameters, but changes abruptly over a narrow range in the neighborhoods of some critical parameter values.

  16. Research on voltage characteristic of the third generation low-light-level image intensifier tube's output signal to noise ratio

    Science.gov (United States)

    Bai, Xiaofeng; Yin, Lei; Hu, Wen; Shi, Feng; Hou, Zhipeng; Shi, Hongli; He, Yingping

    2012-10-01

    Signal to noise ratio is an important parameter to evaluate the 3rd generation low-light-level image intensifier. In this article, voltage in different poles have been changed respectively, output signal to noise ratio referring to different voltages have been studied, and the relationship between each voltage and output signal to noise ratio has been analyzed. The study results show that voltage of photocathode is not less than 150 V, voltage of MCP is between 800 V and 900 V, and voltage of screen is between 5000 V and 6000 V while output signal to noise ratio of filmed image intensifier is optimized. The study in this article is worthwhile for developing signal to noise ratio of the 3rd low-light-level image intensifier sufficiently.

  17. Physically secured orthogonal frequency division multiplexing-passive optical network employing noise-based encryption and signal recovery process

    Science.gov (United States)

    Jin, Wei; Zhang, Chongfu; Yuan, Weicheng

    2016-02-01

    We propose a physically enhanced secure scheme for direct detection-orthogonal frequency division multiplexing-passive optical network (DD-OFDM-PON) and long reach coherent detection-orthogonal frequency division multiplexing-passive optical network (LRCO-OFDM-PON), by employing noise-based encryption and channel/phase estimation. The noise data generated by chaos mapping are used to substitute training sequences in preamble to realize channel estimation and frame synchronization, and also to be embedded on variable number of key-selected randomly spaced pilot subcarriers to implement phase estimation. Consequently, the information used for signal recovery is totally hidden as unpredictable noise information in OFDM frames to mask useful information and to prevent illegal users from correctly realizing OFDM demodulation, and thereby enhancing resistance to attackers. The levels of illegal-decryption complexity and implementation complexity are theoretically discussed. Through extensive simulations, the performances of the proposed channel/phase estimation and the security introduced by encrypted pilot carriers have been investigated in both DD-OFDM and LRCO-OFDM systems. In addition, in the proposed secure DD-OFDM/LRCO-OFDM PON models, both legal and illegal receiving scenarios have been considered. These results show that, by utilizing the proposed scheme, the resistance to attackers can be significantly enhanced in DD-OFDM-PON and LRCO-OFDM-PON systems without performance degradations.

  18. Fractional White-Noise Limit and Paraxial Approximation for Waves in Random Media

    Science.gov (United States)

    Gomez, Christophe; Pinaud, Olivier

    2017-12-01

    This work is devoted to the asymptotic analysis of high frequency wave propagation in random media with long-range dependence. We are interested in two asymptotic regimes, that we investigate simultaneously: the paraxial approximation, where the wave is collimated and propagates along a privileged direction of propagation, and the white-noise limit, where random fluctuations in the background are well approximated in a statistical sense by a fractional white noise. The fractional nature of the fluctuations is reminiscent of the long-range correlations in the underlying random medium. A typical physical setting is laser beam propagation in turbulent atmosphere. Starting from the high frequency wave equation with fast non-Gaussian random oscillations in the velocity field, we derive the fractional Itô-Schrödinger equation, that is, a Schrödinger equation with potential equal to a fractional white noise. The proof involves a fine analysis of the backscattering and of the coupling between the propagating and evanescent modes. Because of the long-range dependence, classical diffusion-approximation theorems for equations with random coefficients do not apply, and we therefore use moment techniques to study the convergence.

  19. Fractional White-Noise Limit and Paraxial Approximation for Waves in Random Media

    Science.gov (United States)

    Gomez, Christophe; Pinaud, Olivier

    2017-07-01

    This work is devoted to the asymptotic analysis of high frequency wave propagation in random media with long-range dependence. We are interested in two asymptotic regimes, that we investigate simultaneously: the paraxial approximation, where the wave is collimated and propagates along a privileged direction of propagation, and the white-noise limit, where random fluctuations in the background are well approximated in a statistical sense by a fractional white noise. The fractional nature of the fluctuations is reminiscent of the long-range correlations in the underlying random medium. A typical physical setting is laser beam propagation in turbulent atmosphere. Starting from the high frequency wave equation with fast non-Gaussian random oscillations in the velocity field, we derive the fractional Itô-Schrödinger equation, that is, a Schrödinger equation with potential equal to a fractional white noise. The proof involves a fine analysis of the backscattering and of the coupling between the propagating and evanescent modes. Because of the long-range dependence, classical diffusion-approximation theorems for equations with random coefficients do not apply, and we therefore use moment techniques to study the convergence.

  20. Allan Variance Computed in Space Domain: Definition and Application to InSAR Data to Characterize Noise and Geophysical Signal.

    Science.gov (United States)

    Cavalié, Olivier; Vernotte, François

    2016-04-01

    The Allan variance was introduced 50 years ago for analyzing the stability of frequency standards. In addition to its metrological interest, it may be also considered as an estimator of the large trends of the power spectral density (PSD) of frequency deviation. For instance, the Allan variance is able to discriminate different types of noise characterized by different power laws in the PSD. The Allan variance was also used in other fields than time and frequency metrology: for more than 20 years, it has been used in accelerometry, geophysics, geodesy, astrophysics, and even finances. However, it seems that up to now, it has been exclusively applied for time series analysis. We propose here to use the Allan variance on spatial data. Interferometric synthetic aperture radar (InSAR) is used in geophysics to image ground displacements in space [over the synthetic aperture radar (SAR) image spatial coverage] and in time thanks to the regular SAR image acquisitions by dedicated satellites. The main limitation of the technique is the atmospheric disturbances that affect the radar signal while traveling from the sensor to the ground and back. In this paper, we propose to use the Allan variance for analyzing spatial data from InSAR measurements. The Allan variance was computed in XY mode as well as in radial mode for detecting different types of behavior for different space-scales, in the same way as the different types of noise versus the integration time in the classical time and frequency application. We found that radial Allan variance is the more appropriate way to have an estimator insensitive to the spatial axis and we applied it on SAR data acquired over eastern Turkey for the period 2003-2011. Spatial Allan variance allowed us to well characterize noise features, classically found in InSAR such as phase decorrelation producing white noise or atmospheric delays, behaving like a random walk signal. We finally applied the spatial Allan variance to an InSAR time

  1. Selective attention and the auditory vertex potential. 2: Effects of signal intensity and masking noise

    Science.gov (United States)

    Schwent, V. L.; Hillyard, S. A.; Galambos, R.

    1975-01-01

    A randomized sequence of tone bursts was delivered to subjects at short inter-stimulus intervals with the tones originating from one of three spatially and frequency specific channels. The subject's task was to count the tones in one of the three channels at a time, ignoring the other two, and press a button after each tenth tone. In different conditions, tones were given at high and low intensities and with or without a background white noise to mask the tones. The N sub 1 component of the auditory vertex potential was found to be larger in response to attended channel tones in relation to unattended tones. This selective enhancement of N sub 1 was minimal for loud tones presented without noise and increased markedly for the lower tone intensity and in noise added conditions.

  2. Hearing aid processing of loud speech and noise signals: Consequences for loudness perception and listening comfort

    DEFF Research Database (Denmark)

    Schmidt, Erik

    2007-01-01

    Hearing aid processing of loud speech and noise signals: Consequences for loudness perception and listening comfort. Sound processing in hearing aids is determined by the fitting rule. The fitting rule describes how the hearing aid should amplify speech and sounds in the surroundings, such that t......Hearing aid processing of loud speech and noise signals: Consequences for loudness perception and listening comfort. Sound processing in hearing aids is determined by the fitting rule. The fitting rule describes how the hearing aid should amplify speech and sounds in the surroundings...... research -for example investigations of loudness perception in hearing impaired listeners. Most research has been focused on speech and sounds at medium input-levels (e.g., 60-65 dB SPL). It is well documented that for speech at conversational levels, hearing aid-users prefer the signal to be amplified...... in regard to perceived level variation, loudness and overall acceptance. In the second experiment, two signals containing speech and noise at 75 dB SPL RMS-level, were compressed with six compression ratios from 1:1 to 10:1 and three release times from 40 ms to 4000 ms. In this experiment, subjects rated...

  3. Modeling of signal propagation and sensor performance for infrasound and blast noise

    Science.gov (United States)

    Glaser, Danney R.; Wilson, D. Keith; Waldrop, Lauren E.; Hart, Carl R.; White, Michael J.; Nykaza, Edward T.; Swearingen, Michelle E.

    2017-05-01

    This paper describes a comprehensive modeling approach for infrasonic (sub-audible acoustic) signals, which starts with an accurate representation of the source spectrum and directivity, propagates the signals through the environment, and senses and processes the signals at the receiver. The calculations are implemented within EASEE (Environmental Awareness for Sensor and Emitter Employment), which is a general software framework for modeling the impacts of terrain and weather on target signatures and the performance of a diverse range of battlefield sensing systems, including acoustic, seismic, RF, visible, and infrared. At each stage in the modeling process, the signals are described by realistic statistical distributions. Sensor performance is quantified using statistical metrics such as probability of detection and target location error. To extend EASEE for infrasonic calculations, new feature sets were created including standard octaves and one-third octaves. A library of gunfire and blast noise spectra and directivity functions was added from ERDC's BNOISE (Blast Noise) and SARNAM (Small Arms Range Noise Assessment Model) software. Infrasonic propagation modeling is supported by extension of several existing propagation algorithms, including a basic ground impedance model, and the Green's function parabolic equation (GFPE), which provides accurate numerical solutions for wave propagation in a refractive atmosphere. The BNOISE propagation algorithm, which is based on tables generated by a fast-field program (FFP), was also added. Finally, an extensive library of transfer functions for microphones operating in the infrasonic range were added, which interface to EASEE's sensor performance algorithms. Example calculations illustrate terrain and atmospheric impacts on infrasonic signal propagation and the directivity characteristics of blast noise.

  4. Spectral data de-noising using semi-classical signal analysis: application to localized MRS

    KAUST Repository

    Laleg-Kirati, Taous-Meriem

    2016-09-05

    In this paper, we propose a new post-processing technique called semi-classical signal analysis (SCSA) for MRS data de-noising. Similar to Fourier transformation, SCSA decomposes the input real positive MR spectrum into a set of linear combinations of squared eigenfunctions equivalently represented by localized functions with shape derived from the potential function of the Schrodinger operator. In this manner, the MRS spectral peaks represented as a sum of these \\'shaped like\\' functions are efficiently separated from noise and accurately analyzed. The performance of the method is tested by analyzing simulated and real MRS data. The results obtained demonstrate that the SCSA method is highly efficient in localized MRS data de-noising and allows for an accurate data quantification.

  5. Tracking random walk of individual domain walls in cylindrical nanomagnets with resistance noise.

    Science.gov (United States)

    Singh, Amrita; Mukhopadhyay, Soumik; Ghosh, Arindam

    2010-08-06

    The stochasticity of domain-wall (DW) motion in magnetic nanowires has been probed by measuring slow fluctuations, or noise, in electrical resistance at small magnetic fields. By controlled injection of DWs into isolated cylindrical nanowires of nickel, we have been able to track the motion of the DWs between the electrical leads by discrete steps in the resistance. Closer inspection of the time dependence of noise reveals a diffusive random walk of the DWs with a universal kinetic exponent. Our experiments outline a method with which electrical resistance is able to detect the kinetic state of the DWs inside the nanowires, which can be useful in DW-based memory designs.

  6. Optimization of polarizer azimuth in improving signal-to-noise ratio in Kerr microscopy.

    Science.gov (United States)

    Wang, X; Lian, J; Xu, X J; Li, X; Li, P; Li, M M; Wang, Y; Liu, Y X

    2016-03-01

    The magneto optical Kerr effect (MOKE) is a widely used technique in magnetic domain imaging for its high surface sensitivity and external magnetic compatibility. Optimization of Kerr microscopy will improve the detecting sensitivity and provide high-quality domain images. In this work, we provide a method to optimize the polarizer azimuth in improving the signal-to-noise ratio (S/N) in longitudinal Kerr microscopy with the generalized magneto optical ellipsometry. Detailed analysis of the MOKE signal and the noise components are provided to study the optimum polarizer and analyzer azimuth combinations. Results show that, for a fixed polarizer angle 1°, the laser intensity noise and the shot noise, which vary with the input laser power, have a similar amplitude and decline with the analyzer azimuth increasing. When the analyzer is set at the extinction place, the Johnson noise plays a dominate role in the total noise. Then, the S/N values are calculated to find the optimum polarizer and analyzer azimuth. Results show that the optimum polarizer and analyzer azimuth combination for Permalloy is (18.35°, 68.35°) under an incident angle of 45°. After that, the S/N of 200 nm Permalloy at different analyzer angles with the polarizer azimuth set at 18.35° is measured to verify the validity of the simulation results. At last, the S/N at different incident angles is calculated. Results show that the optimum incident angle of 200 nm Permalloy film to improve the S/N is 70.35° under the polarizer and analyzer angles set at the optimal combinations (18.35°, 68.35°).

  7. The effect of hearing aid signal-processing schemes on acceptable noise levels: perception and prediction.

    Science.gov (United States)

    Wu, Yu-Hsiang; Stangl, Elizabeth

    2013-01-01

    The acceptable noise level (ANL) test determines the maximum noise level that an individual is willing to accept while listening to speech. The first objective of the present study was to systematically investigate the effect of wide dynamic range compression processing (WDRC), and its combined effect with digital noise reduction (DNR) and directional processing (DIR), on ANL. Because ANL represents the lowest signal-to-noise ratio (SNR) that a listener is willing to accept, the second objective was to examine whether the hearing aid output SNR could predict aided ANL across different combinations of hearing aid signal-processing schemes. Twenty-five adults with sensorineural hearing loss participated in the study. ANL was measured monaurally in two unaided and seven aided conditions, in which the status of the hearing aid processing schemes (enabled or disabled) and the location of noise (front or rear) were manipulated. The hearing aid output SNR was measured for each listener in each condition using a phase-inversion technique. The aided ANL was predicted by unaided ANL and hearing aid output SNR, under the assumption that the lowest acceptable SNR at the listener's eardrum is a constant across different ANL test conditions. Study results revealed that, on average, WDRC increased (worsened) ANL by 1.5 dB, while DNR and DIR decreased (improved) ANL by 1.1 and 2.8 dB, respectively. Because the effects of WDRC and DNR on ANL were opposite in direction but similar in magnitude, the ANL of linear/DNR-off was not significantly different from that of WDRC/DNR-on. The results further indicated that the pattern of ANL change across different aided conditions was consistent with the pattern of hearing aid output SNR change created by processing schemes. Compared with linear processing, WDRC creates a noisier sound image and makes listeners less willing to accept noise. However, this negative effect on noise acceptance can be offset by DNR, regardless of microphone mode

  8. Online denoising method to handle intraindividual variability of signal-to-noise ratio in continuous glucose monitoring.

    Science.gov (United States)

    Facchinetti, Andrea; Sparacino, Giovanni; Cobelli, Claudio

    2011-09-01

    In the last decade, the availability of new minimally invasive subcutaneous sensors for monitoring glucose level continuously stimulated research on new online strategies for improving the treatment of diabetes, including hyper/hypoglycemic alert generators and artificial pancreas. An important aspect that has to be dealt with in these applications is the random measurement noise that affects continuous glucose monitoring (CGM) signals. One major difficulty is that for a given sensor technology, the signal-to-noise ratio (SNR) can vary from subject to subject (interindividual variability) and also within subject (intraindividual variability). Recently, a denoising approach implemented through a Kalman filter with parameters automatically tuned, once for all, in a burn-in interval was proposed to cope with the interindividual variability of SNR. In this paper, we propose a new denoising method able to cope also with the intraindividual variability of the SNR. The method resorts to a Bayesian smoothing procedure that uses a statistically-based criterion to determine, and continuously update, filter parameters in real time. The performance of the method is assessed on both Monte Carlo simulation and 24 real CGM time series obtained with the Glucoday system (Menarini, Florence, Italy). The method has a general applicability, also outside from the CGM context.

  9. The effects of noise-bandwidth, noise-fringe duration, and temporal signal location on the binaural masking-level difference.

    Science.gov (United States)

    Yasin, Ifat; Henning, G Bruce

    2012-07-01

    The effects of forward and backward noise fringes on binaural signal detectability were investigated. Masked thresholds for a 12-ms, 250-Hz, sinusoidal signal masked by Gaussian noise, centered at 250 Hz, with bandwidths from 3 to 201 Hz, were obtained in N(0)S(0) and N(0)S(π) configurations. The signal was (a) temporally centered in a 12-ms noise burst (no fringe), (b) presented at the start of a 600-ms noise burst (backward fringe), or (c) temporally centered in a 600-ms noise burst (forward-plus-backward fringe). For noise bandwidths between 3 and 75 Hz, detection in N(0)S(0) improved with the addition of a backward fringe, improving further with an additional forward fringe; there was little improvement in N(0)S(π). The binaural masking-level difference (BMLD) increased from 0 to 8 dB with a forward-plus-backward fringe as noise bandwidths increased to 100 Hz, increasing slightly to 10 dB at 201 Hz. This two-stage increase was less pronounced with a backward fringe. With no fringe, the BMLD was about 10-14 dB at all bandwidths. Performance appears to result from the interaction of across-time and across-frequency listening strategies and the possible effects of gain reduction and suppression, which combine in complex ways. Current binaural models are, as yet, unable to account fully for these effects.

  10. Signal-to-noise ratio for source determination and for a comodulated masker in goldfish, Carassius auratus.

    Science.gov (United States)

    Fay, Richard R

    2011-05-01

    The masking effects of white and amplitude comodulated noise were studied with respect to simple signal detection and sound source determination in goldfish. A stimulus generalization method was used to determine the signal-to-noise ratio required to completely determine the signal's characteristics. It was found that the S∕N required for this determination is about 4 dB greater than that required for signal detection, or was about 4 dB greater than the critical masking ratio. This means that the potential harm to fish of a given masking noise is at least 4 dB greater than previously thought, based on critical masking ratios. However, for amplitude comodulated noise between 10 and 50 Hz modulation rate, the potential harmful effects are up to 5.3 dB less than would be predicted from the critical masking ratio for unmodulated noise.

  11. Random Deep Belief Networks for Recognizing Emotions from Speech Signals

    Directory of Open Access Journals (Sweden)

    Guihua Wen

    2017-01-01

    Full Text Available Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition.

  12. Sequential time interleaved random equivalent sampling for repetitive signal

    Science.gov (United States)

    Zhao, Yijiu; Liu, Jingjing

    2016-12-01

    Compressed sensing (CS) based sampling techniques exhibit many advantages over other existing approaches for sparse signal spectrum sensing; they are also incorporated into non-uniform sampling signal reconstruction to improve the efficiency, such as random equivalent sampling (RES). However, in CS based RES, only one sample of each acquisition is considered in the signal reconstruction stage, and it will result in more acquisition runs and longer sampling time. In this paper, a sampling sequence is taken in each RES acquisition run, and the corresponding block measurement matrix is constructed using a Whittaker-Shannon interpolation formula. All the block matrices are combined into an equivalent measurement matrix with respect to all sampling sequences. We implemented the proposed approach with a multi-cores analog-to-digital converter (ADC), whose ADC cores are time interleaved. A prototype realization of this proposed CS based sequential random equivalent sampling method has been developed. It is able to capture an analog waveform at an equivalent sampling rate of 40 GHz while sampled at 1 GHz physically. Experiments indicate that, for a sparse signal, the proposed CS based sequential random equivalent sampling exhibits high efficiency.

  13. Statistics-based filtering for low signal-to-noise ratios, applied to rocket plume imaging

    Science.gov (United States)

    Hovland, Harald

    2017-05-01

    Extracting information from low signal to noise ratio images poses significant challenges. Noise makes extracting spatial features difficult, in particular if extraction of both large, smooth features at the same time as point-like features is required. This work describes a new statistical approach, able to handle both simultaneously, with the capacity of handling both positive and negative contrast signatures. The basic idea in this approach is that each pixel value can represent underlying statistics to a varying degree, depending on how similar it is to samples taken close to it, spatially and/or temporally. If the sample is similar to its surroundings, it is strongly filtered and also affects the filtering of neighboring samples, but if it is significantly different, it will remain largely unfiltered and does not influence neighboring pixel filtering. Simulations show that the filtering maintains energy conservation, significantly limits noise and at the same time maintains signal integrity. The filter is found to adapt to noise characteristics and spatiotemporal variations of the background. The technique is found to be well suited to rocket plume imaging, but is adaptable to a broad range of other applications.

  14. Nonlinear Bayesian estimation of BOLD signal under non-Gaussian noise.

    Science.gov (United States)

    Khan, Ali Fahim; Younis, Muhammad Shahzad; Bajwa, Khalid Bashir

    2015-01-01

    Modeling the blood oxygenation level dependent (BOLD) signal has been a subject of study for over a decade in the neuroimaging community. Inspired from fluid dynamics, the hemodynamic model provides a plausible yet convincing interpretation of the BOLD signal by amalgamating effects of dynamic physiological changes in blood oxygenation, cerebral blood flow and volume. The nonautonomous, nonlinear set of differential equations of the hemodynamic model constitutes the process model while the weighted nonlinear sum of the physiological variables forms the measurement model. Plagued by various noise sources, the time series fMRI measurement data is mostly assumed to be affected by additive Gaussian noise. Though more feasible, the assumption may cause the designed filter to perform poorly if made to work under non-Gaussian environment. In this paper, we present a data assimilation scheme that assumes additive non-Gaussian noise, namely, the e-mixture noise, affecting the measurements. The proposed filter MAGSF and the celebrated EKF are put to test by performing joint optimal Bayesian filtering to estimate both the states and parameters governing the hemodynamic model under non-Gaussian environment. Analyses using both the synthetic and real data reveal superior performance of the MAGSF as compared to EKF.

  15. Investigation of a glottal related harmonics-to-noise ratio and spectral tilt as indicators of glottal noise in synthesized and human voice signals.

    LENUS (Irish Health Repository)

    Murphy, Peter J

    2008-03-01

    The harmonics-to-noise ratio (HNR) of the voiced speech signal has implicitly been used to infer information regarding the turbulent noise level at the glottis. However, two problems exist for inferring glottal noise attributes from the HNR of the speech wave form: (i) the measure is fundamental frequency (f0) dependent for equal levels of glottal noise, and (ii) any deviation from signal periodicity affects the ratio, not just turbulent noise. An alternative harmonics-to-noise ratio formulation [glottal related HNR (GHNR\\')] is proposed to overcome the former problem. In GHNR\\' a mean over the spectral range of interest of the HNRs at specific harmonic\\/between-harmonic frequencies (expressed in linear scale) is calculated. For the latter issue [(ii)] two spectral tilt measures are shown, using synthesis data, to be sensitive to glottal noise while at the same time being comparatively insensitive to other glottal aperiodicities. The theoretical development predicts that the spectral tilt measures reduce as noise levels increase. A conventional HNR estimator, GHNR\\' and two spectral tilt measures are applied to a data set of 13 pathological and 12 normal voice samples. One of the tilt measures and GHNR\\' are shown to provide statistically significant differentiating power over a conventional HNR estimator.

  16. Computationally rapid method of estimating signal-to-noise ratio for phased array image reconstructions.

    Science.gov (United States)

    Wiens, Curtis N; Kisch, Shawn J; Willig-Onwuachi, Jacob D; McKenzie, Charles A

    2011-10-01

    Measuring signal-to-noise ratio (SNR) for parallel MRI reconstructions is difficult due to spatially dependent noise amplification. Existing approaches for measuring parallel MRI SNR are limited because they are not applicable to all reconstructions, require significant computation time, or rely on repeated image acquisitions. A new SNR estimation approach is proposed, a hybrid of the repeated image acquisitions method detailed in the National Electrical Manufacturers Association (NEMA) standard and the Monte Carlo based pseudo-multiple replica method, in which the difference between images reconstructed from the unaltered acquired data and that same data reconstructed after the addition of calibrated pseudo-noise is used to estimate the noise in the parallel MRI image reconstruction. This new noise estimation method can be used to rapidly compute the pixel-wise SNR of the image generated from any parallel MRI reconstruction of a single acquisition. SNR maps calculated with the new method are validated against existing SNR calculation techniques. Copyright © 2011 Wiley-Liss, Inc.

  17. Noise modeling in a signal conditioning circuit for low power audio application using resistive sensor

    Directory of Open Access Journals (Sweden)

    Meillère Stéphane

    2016-01-01

    Full Text Available Piezoresistive sensors convert a physical value into a resistance variation. Often four resistive elements are connected together in a Wheatstone bridge to provide electrical variations of sensors. When this structure is biased with a fixed voltage source or a current source the topology provides a differential output voltage. To exploit information a conditioning circuit is associated to the bridge. In most cases it consists of an instrumentation amplifier followed by a data converter to obtain very quickly a digital representation of information. Due to the high input impedance of the instrumentation amplifier, bridge sensitivity is preserved. A filter may be added to avoid aliasing or a continuous time sigma-delta modulator that includes filtering feature. This study is concerning the conditioning structure for piezoresistive sensors bridge especially fully integrated microphones for biomedical application. The bridge signal to noise ratio is set by biasing the amplifier stage by current. The noise performance becomes the limiting factor of the read-out circuit. Current mode topologies drive amplifiers design where inputs are the main noise contributor. Modeling noise contribution is a key point in the design of the conditioning circuit. The current consumption leads noise performances too. A proposed architecture was implemented in a 65nm CMOS standard technology for performance measurement and evaluation with nanowire based microphone dedicated to hearing aids application.

  18. Analisis Jarak Terhadap Redaman SNR (Signal To Noise Ratio, Dan Kecepatan Download Pada Jaringan ADSL

    Directory of Open Access Journals (Sweden)

    Anggun Fitrian Isnawati

    2010-11-01

    Full Text Available ADSL (Asymetric Digital Subscriber Line adalah teknologi yang paling banyak digunakan untuk memberikan layanan broadband , lebih dari 60% pasar broadband di dunia menggunakan teknologi ini. ADSL merupakan sebuah teknologi yang tangguh, mempunyai kemampuan untuk mendukung aplikasi-aplikasi multimedia seperti voice, video, dan juga data. Konfigurasi ADSL juga sangat sederhana, cukup menggunakan infrastruktur jaringan lokal kabel tembaga yang sudah ada. Namun ADSL juga masih memiliki kekurangan, diantaranya jarak jangkauan untuk ADSL hanya berkisar ± 5 km. Selain itu, jarak pelanggan yang jauh dari sentral sangat  mempengaruhi untuk nilai kecepatan download. Hal ini, dikarenakan semakin jauh jarak yang berarti media penghantar maka akan semakin banyak redaman yang terjadi pada media tersebut yang menyebabkan turunnya Signal to Noise Ratio dimana dalam hal ini dapat diartikan kekuatan sinyal. Sehingga dari hal-hal tersebut akan mempengaruhi kualitas kecepatan download. Dari sinilah yang kemudian akan dibandingkan bagaimana pengaruh jarak terhadap redaman, Signal to Noise Ratio, dan juga kecepatan download.

  19. Degradation of signal to noise ratio in optical free space data links due to background illumination.

    Science.gov (United States)

    Leeb, W R

    1989-08-15

    In free space optical data transmission systems illumination of the receiver antenna by background radiation will decrease the signal to noise ratio. We derive expressions for that degradation both for direct and for heterodyne/homodyne receivers. Examples are given for cases where the sun, the moon, the earth, and Venus illuminate earth orbiting receivers operating at wavelengths of 0.85 microm, 1.3 microm, and 10.6 microm. Direct detection receivers will typically suffer a degradation of between 5 and 15 dB at lambda = 0.85 microm and lambda = 1.3 microm when illuminated by the sun. Heterodyne/homodyne receivers at 10.6 microm degrade more with sun radiation (typically 4 dB) than at the smaller wavelengths ( approximately 0.3 dB). The moon, earth, and Venus cause negligible reduction of signal to noise ratio.

  20. Assessing signal-to-noise in quantitative proteomics: multivariate statistical analysis in DIGE experiments.

    Science.gov (United States)

    Friedman, David B

    2012-01-01

    All quantitative proteomics experiments measure variation between samples. When performing large-scale experiments that involve multiple conditions or treatments, the experimental design should include the appropriate number of individual biological replicates from each condition to enable the distinction between a relevant biological signal from technical noise. Multivariate statistical analyses, such as principal component analysis (PCA), provide a global perspective on experimental variation, thereby enabling the assessment of whether the variation describes the expected biological signal or the unanticipated technical/biological noise inherent in the system. Examples will be shown from high-resolution multivariable DIGE experiments where PCA was instrumental in demonstrating biologically significant variation as well as sample outliers, fouled samples, and overriding technical variation that would not be readily observed using standard univariate tests.

  1. Error signal sensing for active noise control in turbofan engine nacelles

    Science.gov (United States)

    Walker, Bruce; Hersh, Alan; Rice, Edward

    2002-05-01

    Blade passage harmonic tones are a significant component of turbofan engine noise under approach conditions. Active noise control (ANC) offers a tool for suppression of these tones, with the caveat that interference patterns in the sound field can lead to poor or even negative correlation between in-duct sound pressures and radiated sound power. Various modal decomposition and wavenumber separation schemes have been investigated in attempt to overcome this obstacle. The paper will discuss methods that have been applied to design and implementation of microphone arrays and signal processing techniques to provide unambiguous error signals for ANC systems in these complex acoustical environments and will present results of computer simulations and field tests. [Work sponsored by NASA Glenn and NASA Langley Research Centers.

  2. Signal and Noise in the Perception of Facial Emotion Expressions: From Labs to Life.

    Science.gov (United States)

    Hess, Ursula; Kafetsios, Konstantinos; Mauersberger, Heidi; Blaison, Christophe; Kessler, Carolin-Louisa

    2016-08-01

    Human interactions are replete with emotional exchanges, and hence, the ability to decode others' emotional expressions is of great importance. The present research distinguishes between the emotional signal (the intended emotion) and noise (perception of secondary emotions) in social emotion perception and investigates whether these predict the quality of social interactions. In three studies, participants completed laboratory-based assessments of emotion recognition ability and later reported their perceptions of naturally occurring social interactions. Overall, noise perception in the recognition task was associated with perceiving more negative emotions in others and perceiving interactions more negatively. Conversely, signal perception of facial emotion expressions was associated with higher quality in social interactions. These effects were moderated by relationship closeness in Greece but not in Germany. These findings suggest that emotion recognition as assessed in the laboratory is a valid predictor of social interaction quality. Thus, emotion recognition generalizes from the laboratory to everyday life. © 2016 by the Society for Personality and Social Psychology, Inc.

  3. Enhancement of the Signal-to-Noise Ratio in Sonic Logging Waveforms by Seismic Interferometry

    KAUST Repository

    Aldawood, Ali

    2012-04-01

    Sonic logs are essential tools for reliably identifying interval velocities which, in turn, are used in many seismic processes. One problem that arises, while logging, is irregularities due to washout zones along the borehole surfaces that scatters the transmitted energy and hence weakens the signal recorded at the receivers. To alleviate this problem, I have extended the theory of super-virtual refraction interferometry to enhance the signal-to-noise ratio (SNR) sonic waveforms. Tests on synthetic and real data show noticeable signal-to-noise ratio (SNR) enhancements of refracted P-wave arrivals in the sonic waveforms. The theory of super-virtual interferometric stacking is composed of two redatuming steps followed by a stacking procedure. The first redatuming procedure is of correlation type, where traces are correlated together to get virtual traces with the sources datumed to the refractor. The second datuming step is of convolution type, where traces are convolved together to dedatum the sources back to their original positions. The stacking procedure following each step enhances the signal to noise ratio of the refracted P-wave first arrivals. Datuming with correlation and convolution of traces introduces severe artifacts denoted as correlation artifacts in super-virtual data. To overcome this problem, I replace the datuming with correlation step by datuming with deconvolution. Although the former datuming method is more robust, the latter one reduces the artifacts significantly. Moreover, deconvolution can be a noise amplifier which is why a regularization term is utilized, rendering the datuming with deconvolution more stable. Tests of datuming with deconvolution instead of correlation with synthetic and real data examples show significant reduction of these artifacts. This is especially true when compared with the conventional way of applying the super-virtual refraction interferometry method.

  4. Signal-to-Noise Ratio Prediction and Validation for Space Shuttle GPS Flight Experiment

    Science.gov (United States)

    Hwu, Shian U.; Adkins, Antha A.; Loh, Yin-Chung; Brown, Lisa C.; Sham, Catherine C.; Kroll, Quin D.

    2002-01-01

    A deterministic method for Space Station Global Positioning System (GPS) Signal-To- Noise Ratio (SNR) predictions is proposed. The complex electromagnetic interactions between GPS antennas and surrounding Space Station structures are taken into account by computational electromagnetic technique. This computer simulator is capable of taking into account multipath effects from dynamically changed solar panels and thermal radiators. A comparison with recent collected Space Station GPS system flight experiment data is presented. The simulation results are in close agreement with flight data.

  5. Testing for near I (2) trends when the signal to noise ratio is small

    DEFF Research Database (Denmark)

    Juselius, Katarina

    Researchers seldom find evidence of I(2) in exchange rates, prices, and other macroeconomics time series when they test the order of integration using univariate Dickey-Fuller tests. In contrast, when using the multivariate ML trace test we frequently find double unit roots in the data. Our paper...... demonstrates by simulations that this often happens when the signal-to-noise-ratio is small....

  6. Circuit for echo and noise suppression of accoustic signals transmitted through a drill string

    Science.gov (United States)

    Drumheller, Douglas S.; Scott, Douglas D.

    1993-01-01

    An electronic circuit for digitally processing analog electrical signals produced by at least one acoustic transducer is presented. In a preferred embodiment of the present invention, a novel digital time delay circuit is utilized which employs an array of First-in-First-out (FiFo) microchips. Also, a bandpass filter is used at the input to this circuit for isolating drill string noise and eliminating high frequency output.

  7. Circuit for echo and noise suppression of acoustic signals transmitted through a drill string

    Science.gov (United States)

    Drumheller, D.S.; Scott, D.D.

    1993-12-28

    An electronic circuit for digitally processing analog electrical signals produced by at least one acoustic transducer is presented. In a preferred embodiment of the present invention, a novel digital time delay circuit is utilized which employs an array of First-in-First-out (FiFo) microchips. Also, a bandpass filter is used at the input to this circuit for isolating drill string noise and eliminating high frequency output. 20 figures.

  8. Improving measuring accuracy of inharmonious signal voltage under the additive noise condition

    Directory of Open Access Journals (Sweden)

    Horbatyi I. V.

    2017-04-01

    Full Text Available The basic known methods of signal voltage measuring were considered. The circuit solutions used in the construction of digital voltmeters were analyzed. Their advantages and defects were analized. Method of direct assessment of alternating current voltage is proposed to improve by using the developed method for measuring root-mean-square value of alternating current voltage and the device for the realization of the method. It is set, that the use of improved method provides an increase of the inharmonious signal voltage measuring accuracy in conditions of additive noise. Circuit solutions that used for making of digital multimeter using the improved method for measuring of alternating current voltage were described.

  9. Improvements in the Signal-to-Noise Ratio of Superconducting Gravimeter Observations by Improved Atmospheric Reductions

    Science.gov (United States)

    Wuensch, Johann; Kroner, Corinna; Förste, Christoph

    2010-05-01

    The high accuracy of Superconducting Gravimeters provides important advance in the knowledge of the solid Earth. Appropriate atmospheric and hydrological reductions are a prerequisite e.g.for the discovering of core signals such as Slichter triplett and core modes. In order to obtain a further improvement of the signal-to-noise ratio of the gravimeter data in the spectral range between 2 h and 48 h, 10 min air pressure and temperature data of 96 German meteorological stations were included in the atmospheric reduction based on the Merriam approach (Merriam, 1992). The results are compared in their performance to the application of a local air pressure regression.

  10. Subspace-Based Noise Reduction for Speech Signals via Diagonal and Triangular Matrix Decompositions

    DEFF Research Database (Denmark)

    Hansen, Per Christian; Jensen, Søren Holdt

    We survey the definitions and use of rank-revealing matrix decompositions in single-channel noise reduction algorithms for speech signals. Our algorithms are based on the rank-reduction paradigm and, in particular, signal subspace techniques. The focus is on practical working algorithms, using both...... diagonal (eigenvalue and singular value) decompositions and rank-revealing triangular decompositions (ULV, URV, VSV, ULLV and ULLIV). In addition we show how the subspace-based algorithms can be evaluated and compared by means of simple FIR filter interpretations. The algorithms are illustrated...

  11. Enhanced signal-to-noise ratios in frog hearing can be achieved through amplitude death

    CERN Document Server

    Ahn, Kang-Hun

    2013-01-01

    In the ear, hair cells transform mechanical stimuli into neuronal signals with great sensitivity relying on certain active processes. Individual hair cell bundles of non-mammals such as frogs and turtles are known to show spontaneous oscillation. However hair bundles in vivo must be quiet in the absence of stimuli, otherwise, the signal is drowned in intrinsic noise. Thus, a certain mechanism is needed to exist in order to suppress intrinsic noise. Here, through a model study of elastically coupled hair bundles of bullfrog sacculi, we show that a low stimulus threshold and a high signal-to-noise ratio (SNR) can be achieved through the amplitude death phenomenon (the cessation of spontaneous oscillations by coupling). This phenomenon occurs only when the coupled hair bundles have inhomogeneous distribution, which is likely to be the case in biological systems. We show that the SNR has non-monotonic dependence on the mass of the overlying membrane, and find out that the SNR has maximum value in the region of th...

  12. Reduction Of Power Line Humming And High Frequency Noise From Electrocardiogram Signals

    Directory of Open Access Journals (Sweden)

    Mohammed Nabil Abdalazim Mursi

    2015-06-01

    Full Text Available ABSTRACT With the latest advancements in electronics several techniques are used for removal of unwanted entities from signals especially that are implied in the most complicated applications. The removal of power line interference from most sensitive medical monitoring equipments can also be achieved by implementing various useful techniques. The power line interference 5060 Hz is the main source of noise in most of bio-electric signals. The thesis report presents the removal of power line interference and other single frequency tones from ECG signal using the advanced adaptive filtering technique with least mean square LMS algorithm. The thesis is based on digital signal processing DSP techniques with MATLAB package. The MATLAB package will be used in the thesis work which is a powerful tool for the interactive design in most of the scientific applications and complex engineering calculations. In addition so as to achieve the goal of thesis the removal of harmonics hum and high frequency noise from ECG signal by using general notch rejection filters is investigated and implemented.

  13. Correlation techniques for the improvement of signal-to-noise ratio in measurements with stochastic processes

    CERN Document Server

    Reddy, V R; Reddy, T G; Reddy, P Y; Reddy, K R

    2003-01-01

    An AC modulation technique is described to convert stochastic signal variations into an amplitude variation and its retrieval through Fourier analysis. It is shown that this AC detection of signals of stochastic processes when processed through auto- and cross-correlation techniques improve the signal-to-noise ratio; the correlation techniques serve a similar purpose of frequency and phase filtering as that of phase-sensitive detection. A few model calculations applied to nuclear spectroscopy measurements such as Angular Correlations, Mossbauer spectroscopy and Pulse Height Analysis reveal considerable improvement in the sensitivity of signal detection. Experimental implementation of the technique is presented in terms of amplitude variations of harmonics representing the derivatives of normal spectra. Improved detection sensitivity to spectral variations is shown to be significant. These correlation techniques are general and can be made applicable to all the fields of particle counting where measurements ar...

  14. The Revised Speech Perception in Noise Test (R-SPIN) in a multiple signal-to-noise ratio paradigm.

    Science.gov (United States)

    Wilson, Richard H; McArdle, Rachel; Watts, Kelly L; Smith, Sherri L

    2012-09-01

    The Revised Speech Perception in Noise Test (R-SPIN; Bilger, 1984b) is composed of 200 target words distributed as the last words in 200 low-predictability (LP) and 200 high-predictability (HP) sentences. Four list pairs, each consisting of two 50-sentence lists, were constructed with the target word in a LP and HP sentence. Traditionally the R-SPIN is presented at a signal-to-noise ratio (SNR, S/N) of 8 dB with the listener task to repeat the last word in the sentence. The purpose was to determine the practicality of altering the R-SPIN format from a single SNR paradigm into a multiple SNR paradigm from which the 50% points for the HP and LP sentences can be calculated. Three repeated measures experiments were conducted. Forty listeners with normal hearing and 184 older listeners with pure-tone hearing loss participated in the sequence of experiments. The R-SPIN sentences were edited digitally (1) to maintain the temporal relation between the sentences and babble, (2) to establish the SNRs, and (3) to mix the speech and noise signals to obtain SNRs between -1 and 23 dB. All materials were recorded on CD and were presented through an earphone with the responses recorded and analyzed at the token level. For reference purposes the Words-in-Noise Test (WIN) was included in the first experiment. In Experiment 1, recognition performances by listeners with normal hearing were better than performances by listeners with hearing loss. For both groups, performances on the HP materials were better than performances on the LP materials. Performances on the LP materials and on the WIN were similar. Performances at 8 dB S/N were the same with the traditional fixed level presentation and the descending presentation level paradigms. The results from Experiment 2 demonstrated that the four list pairs of R-SPIN materials produced good first approximation psychometric functions over the -4 to 23 dB S/N range, but there were irregularities. The data from Experiment 2 were used in

  15. Noise equivalent circuit of a semiconductor laser diode

    Science.gov (United States)

    Harder, C.; Margalit, S.; Yariv, A.; Katz, J.; Shacham, J.

    1982-01-01

    A small-signal model of a semiconductor laser is extended to include the effects of intrinsic noise by adding current and voltage noise sources. The current noise source represents the shot noise of carrier recombination, while the voltage noise source represents the random process of simulated emission. The usefulness of the noise equivalent circuit is demonstrated by calculating the modulation and noise characteristics of a current-driven diode as a function of bias current and frequency.

  16. Noise equivalent circuit of a semiconductor laser diode

    Science.gov (United States)

    Harder, C.; Margalit, S.; Yariv, A.; Katz, J.; Shacham, J.

    1982-03-01

    A small-signal model of a semiconductor laser is extended to include the effects of intrinsic noise by adding current and voltage noise sources. The current noise source represents the shot noise of carrier recombination, while the voltage noise source represents the random process of simulated emission. The usefulness of the noise equivalent circuit is demonstrated by calculating the modulation and noise characteristics of a current-driven diode as a function of bias current and frequency.

  17. Direct Observations of GPS L1 Signal-to-Noise Degradation due to Solar Radio Bursts

    Science.gov (United States)

    Cerruti, A. P.; Kintner, P. M.; Gary, D.; Lanzerotti, L.

    2006-05-01

    GPS signals, systems, and navigation accuracy are vulnerable to a variety of space weather effects mostly caused by the ionosphere. This paper considers a different class of space weather effects on GPS signals: solar radio bursts. We present the first direct observations of GPS L1 (1.6 GHz) carrier-to-noise degradation on two different models of GPS receivers due to the solar radio burst associated with the 7 September, 2005 solar flare. The solar radio burst consisted of two periods of 1.6 GHz activity at approximately 17:40 UT and again at 18:30 UT. All the receivers that were affected by the solar radio burst were in the sun-lit hemisphere: three identical receivers were collocated at the Arecibo Observatory, and four identical receivers of a different model were located in Brazil. For both models, all GPS satellites in view were affected similarly. In some cases the decrease in the GPS L1 signal-to-noise agreed perfectly with the solar radio burst amplitudes, while in other cases there was no association. Further analysis indicated that only the right hand circularly polarized (RHCP) emissions affected the GPS signals. Since GPS signals are RHCP and GPS antennas are also RHCP, the null effect of the LHCP power confirms our hypothesis that the solar radio bursts are causal. The maximum solar radio burst power associated with the 7 September 2005 flare had a peak intensity of about 8,700 solar flux units (SFU) RHCP at 1,600 MHz, which caused a corresponding decrease in the signal- to-noise of about 2.5 dB across all visible satellites. Furthermore, an event with a peak intensity of 5,000 SFU RHCP at 1,600 MHz caused a 2 dB fade for nearly 15 minutes. To further investigate the effect of solar radio bursts, we also examined the emissions associated with the 28 October 2003 flare. Although polarization data was not available for this even, a similar association was found between 1,400 MHz solar radio power and GPS signal-to-noise degradation. The maximum

  18. Noise-to-signal transition of a Brownian particle in the cubic potential: II. optical trapping geometry

    Science.gov (United States)

    Zemánek, Pavel; Šiler, Martin; Brzobohatý, Oto; Jákl, Petr; Filip, Radim

    2016-06-01

    The noise-to-signal transitions belong to an exciting group of processes in physics. In Filip and Zemánek (2016, J. Opt. 18 065401) we theoretically analyse the stochastic noise-to-signal transition of overdamped Brownian motion of a particle in the cubic potential. In this part, we propose a feasible experimental setup for a proof-of-principle experiment that uses methods of optical trapping in shaped laser beams which provide cubic and quadratic potentials. Theoretical estimates and results from the numerical simulations indicate that the noise-to-signal transition can be observed under realistic experimental conditions.

  19. An Objective Parameter for Quantifying the Turbulent Noise Portion of Voice Signals.

    Science.gov (United States)

    Lin, Liyu; Calawerts, William; Dodd, Keith; Jiang, Jack J

    2016-11-01

    Currently, there are no objective measures capable of distinguishing between all four voice signal types proposed by Titze in 1995 and updated by Sprecher in 2010. We propose an objective metric that distinguishes between voice signal types based on the aperiodicity present in a signal. One hundred fifty voice signal samples were randomly selected from the Disordered Voice Database and subjectively sorted into the appropriate voice signal category on the basis of the classification scheme presented in Sprecher 2010. Short-time Fourier transform was applied to each voice sample to produce a spectrum for each signal. The spectrum of each signal was divided into 250 time segments. Next, these segments were compared to each other and used to calculate an outcome named spectrum convergence ratio (SCR). Finally, the mean SCR was calculated for each of the four voice signal types. SCR was capable of significantly differentiating between each of the four voice signal types (P voice signal types as currently available parameters. SCR was capable of objectively distinguishing between all four voice signal types. This metric could be used by clinicians to quickly and efficiently diagnose voice disorders and monitor improvements in voice acoustical signals during treatment methods. Copyright © 2016 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

  20. Mechanisms for Extracting a Signal from Noise as Revealed through the Specificity and Generality of Task Training

    Science.gov (United States)

    Chang, Dorita H. F.; Kourtzi, Zoe

    2013-01-01

    Visual judgments critically depend on (1) the detection of meaningful items from cluttered backgrounds and (2) the discrimination of an item from highly similar alternatives. Learning and experience are known to facilitate these processes, but the specificity with which these processes operate is poorly understood. Here we use psychophysical measures of human participants to test learning in two types of commonly used tasks that target segmentation (signal-in-noise, or “coarse” tasks) versus the discrimination of highly similar items (feature difference, or “fine” tasks). First, we consider the processing of binocular disparity signals, examining performance on signal-in-noise and feature difference tasks after a period of training on one of these tasks. Second, we consider the generality of learning between different visual features, testing performance on both task types for displays defined by disparity, motion, or orientation. We show that training on a feature difference task also improves performance on signal-in-noise tasks, but only for the same visual feature. By contrast, training on a signal-in-noise task has limited benefits for fine judgments of the same feature but supports learning that generalizes to signal-in-noise tasks for other features. These findings indicate that commonly used signal-in-noise tasks require at least three distinct components: feature representations, signal-specific selection, and a generalized process that enhances segmentation. As such, there is clear potential to harness areas of commonality (both within and between cues) to improve impaired perceptual functions. PMID:23825402

  1. Effect of Acute Noise Exposure on Salivary Cortisol: A Randomized Controlled Trial.

    Science.gov (United States)

    Pouryaghoub, Gholamreza; Mehrdad, Ramin; Valipouri, Alireza

    2016-10-01

    Cardiovascular adverse effects are interesting aspects of occupational noise exposure. One possible mechanism of these effects is an alternation in hypothalamic-pituitary-adrenal axis. Our aim was to measure salivary cortisol response to relatively high-intensity noise exposure in a controlled randomized trial study. We exposed 50 male volunteers to 90 dBA noise for 20 minutes and compared their level of salivary cortisol with 50 non-exposed controls. Salivary samples obtained before and after exposure. Before intervention means (SD) salivary cortisol level were 3.24 (0.47)ng/ml and 3.25 (0.41)ng/ml for exposed and non-exposed groups respectively. Mean salivary cortisol level increased to 4.17 ng/mlafter intervention in exposure group. This increment was statistically significant (P=0.00). Mean salivary cortisol level of the non-exposed group had statistically non-significant decrement after this period (0.2 ng/ml). The difference between salivary cortisol level of non-exposed and exposed groups after the intervention was statistically significant. Noise exposure may affect the hypothalamic-pituitary-adrenal axis activity, and this may be one of the mechanisms of noise exposure cardiovascular effects.

  2. Spectral analysis of fundamental signal and noise performances in photoconductors for mammography.

    Science.gov (United States)

    Kim, Ho Kyung; Lim, Chang Hwy; Tanguay, Jesse; Yun, Seungman; Cunningham, Ian A

    2012-05-01

    This study investigates the fundamental signal and noise performance limitations imposed by the stochastic nature of x-ray interactions in selected photoconductor materials, such as Si, a-Se, CdZnTe, HgI(2), PbI(2), PbO, and TlBr, for x-ray spectra typically used in mammography. It is shown how Monte Carlo simulations can be combined with a cascaded model to determine the absorbed energy distribution for each combination of photoconductor and x-ray spectrum. The model is used to determine the quantum efficiency, mean energy absorption per interaction, Swank noise factor, secondary quantum noise, and zero-frequency detective quantum efficiency (DQE). The quantum efficiency of materials with higher atomic number and density demonstrates a larger dependence on convertor thickness than those with lower atomic number and density with the exception of a-Se. The mean deposited energy increases with increasing average energy of the incident x-ray spectrum. HgI(2), PbI(2), and CdZnTe demonstrate the largest increase in deposited energy with increasing mass loading and a-Se and Si the smallest. The best DQE performances are achieved with PbO and TlBr. For mass loading greater than 100 mg cm(-2), a-Se, HgI(2), and PbI(2) provide similar DQE values to PbO and TlBr. The quantum absorption efficiency, average deposited energy per interacting x-ray, Swank noise factor, and detective quantum efficiency are tabulated by means of graphs which may help with the design and selection of materials for photoconductor-based mammography detectors. Neglecting the electrical characteristics of photoconductor materials and taking into account only x-ray interactions, it is concluded that PbO shows the strongest signal-to-noise ratio performance of the materials investigated in this study.

  3. Signal to noise ratio in water balance maps with different resolution

    Science.gov (United States)

    Yan, Ziqi; Gottschalk, Lars; Wang, Jianhua

    2016-12-01

    What is the best resolution of annual water balance maps for a correct balance between the basic spatial signal in the observations of precipitation, actual evapotranspiration and runoff across a larger drainage basin and the error in estimates for grid cells in the map to avoid giving a false impression of accuracy? To answer this question an approach based a signal to noise ratio is proposed, which allows finding the optimal resolution maximizing the signal in the map. The approach is demonstrated on gauge data in the Huai River Basin, China. Stochastic interpolation methods were applied to create grid maps of long-term mean values, as well as for estimating variances of the three water balance components in a range of scales from 5 × 5 km to 200 × 200 km2 grid cells. Interpolation algorithms using covariances of long-term means of data with different spatial support were developed. The identified optimal resolutions by the signal to noise ratio appeared to be very different - 10 × 10, 50 × 50, and 30 × 30 km2 for precipitation, actual evapotranspiration, and runoff, respectively. These values are directly linked to the observation network densities. The magnitude of the signal to noise ratio shows similar strong differences with values 34, 3.7, and 5.4, respectively. It gives a direct indication of the reliability of the map, which can be considered as satisfactory only for precipitation for the data available for the present study. The critical factors for this magnitude are parameters characterising the spatial covariance in data and the network density.

  4. Measurement with verification of stationary signals and noise in extremely quiet environments: Measuring below the noise floor

    Science.gov (United States)

    Ellingson, Roger M.; Gallun, Frederick J.; Bock, Guillaume

    2015-01-01

    It can be problematic to measure stationary acoustic sound pressure level in any environment when the target level approaches or lies below the minimum measureable sound pressure level of the measurement system itself. This minimum measureable level, referred to as the inherent measurement system noise floor, is generally established by noise emission characteristics of measurement system components such as microphones, preamplifiers, and other system circuitry. In this paper, methods are presented and shown accurate measuring stationary levels within 20 dB above and below this system noise floor. Methodology includes (1) measuring inherent measurement system noise, (2) subtractive energy based, inherent noise adjustment of levels affected by system noise floor, and (3) verifying accuracy of inherent noise adjustment technique. While generalizable to other purposes, the techniques presented here were specifically developed to quantify ambient noise levels in very quiet rooms used to evaluate free-field human hearing thresholds. Results obtained applying the methods to objectively measure and verify the ambient noise level in an extremely quiet room, using various measurement system noise floors and analysis bandwidths, are presented and discussed. The verified results demonstrate the adjustment method can accurately extend measurement range to 20 dB below the measurement system noise floor, and how measurement system frequency bandwidth can affect accuracy of reported noise levels. PMID:25786932

  5. Statistical properties of a filtered Poisson process with additive random noise: Distributions, correlations and moment estimation

    CERN Document Server

    Theodorsen, Audun; Rypdal, Martin

    2016-01-01

    The filtered Poisson process is often used as a reference model for intermittent fluctuations in physical systems. Here, this process is extended by adding a noise term, either as a purely additive term to the process or as a dynamical term in a stochastic differential equation. The moments, probability density function, auto- correlation function and power spectral density are derived and used to compare the effects of the different noise terms. Monte-Carlo studies of synthetic time series are used to investigate the accuracy of parameter estimation and to identify methods for separating the noise types. It is shown that the probability density function and the three lowest moments provide accurate estimations of the parameters, but are unable to separate the noise types. The auto-correlation function and the power spectral density also provide methods for estimating the model parameters, as well as being capable of determining the noise type. The number of times the signal passes a prescribed threshold in t...

  6. Ambient awareness: From random noise to digital closeness in online social networks

    OpenAIRE

    Levordashka, Ana; Utz, Sonja

    2016-01-01

    Ambient awareness refers to the awareness social media users develop of their online network in result of being constantly exposed to social information, such as microblogging updates. Although each individual bit of information can seem like random noise, their incessant reception can amass to a coherent representation of social others. Despite its growing popularity and important implications for social media research, ambient awareness on public social media has not been studied empiricall...

  7. Nonlinear decomposition-and-denoising approach for removal of signal-dependent noise of a digital color camera

    Science.gov (United States)

    Saito, Takahiro; Ishii, Yuki; Komatsu, Takashi

    2007-06-01

    In a digital camera, several factors cause signal-dependency of additive noise. Many denoising methods have been proposed, but unfortunately most of them do not work well for the actual signal-dependent noise. To solve the problem of removing the signal-dependent noise of a digital camera, this paper presents a denoising approach via the nonlinear image-decomposition. In the nonlinear decomposition-and-denoising approach, at the first nonlinear image-decomposition stage, multiplicative image-decomposition is performed, and a noisy image is represented as a product of its two components so that its structural component corresponding to a cartoon approximation of the noisy image may not be corrupted by the noise and its texture component may collect almost all the noise. At the successive nonlinear denoising stage, intensity of the separated structural component is utilized instead of the unknown true signal value, to adapt the soft-thresholding-type denoising manipulation of the texture component to the signal dependency of the noise. At the final image-synthesis stage, the separated structure component is combined with the denoised texture component, and thus a sharpness-preserved denoised image is reproduced. The nonlinear decomposition-and-denoising approach selectively removes the signal-dependent noise of a digital camera without not only blurring sharp edges but also destroying visually important textures.

  8. Signal-to-noise performance analysis of streak tube imaging lidar systems. II. Theoretical analysis and discussion.

    Science.gov (United States)

    Wu, Lei; Wang, Xiaopeng; Yang, Hongru; Yu, Bing; Chen, Chao; Yang, Bin; Yuan, Liang; Wu, Lipeng; Xue, Zhanli; Li, Gaoping; Wu, Baoning

    2012-12-20

    In the preceding paper (referred to here as paper I), we presented a general signal-to-noise performance analysis of a streak tube imaging lidar (STIL) system within the framework of linear cascaded systems theory. A cascaded model is proposed for characterizing the signal-to-noise performance of a STIL system with an internal or external intensified streak tube receiver. The STIL system can be decomposed into a series of cascaded imaging chains whose signal and noise transfer properties are described by the general (or the spatial-frequency dependent) noise factors (NFs). Equations for the general NFs of the cascaded chains (or the main components) in the STIL system are derived. This work investigates the signal-to-noise performance of an external intensified STIL system. The implementation of the cascaded model for predicting and evaluating the signal-to-noise performance of the external intensified STIL system is described. Some factors that limit the signal-to-noise performance of the external intensified STIL system are analyzed and discussed.

  9. Active random noise control using adaptive learning rate neural networks with an immune feedback law

    Science.gov (United States)

    Sasaki, Minoru; Kuribayashi, Takumi; Ito, Satoshi

    2005-12-01

    In this paper an active random noise control using adaptive learning rate neural networks with an immune feedback law is presented. The adaptive learning rate strategy increases the learning rate by a small constant if the current partial derivative of the objective function with respect to the weight and the exponential average of the previous derivatives have the same sign, otherwise the learning rate is decreased by a proportion of its value. The use of an adaptive learning rate attempts to keep the learning step size as large as possible without leading to oscillation. In the proposed method, because of the immune feedback law change a learning rate of the neural networks individually and adaptively, it is expected that a cost function minimize rapidly and training time is decreased. Numerical simulations and experiments of active random noise control with the transfer function of the error path will be performed, to validate the convergence properties of the adaptive learning rate Neural Networks with the immune feedback law. Control results show that adaptive learning rate Neural Networks control structure can outperform linear controllers and conventional neural network controller for the active random noise control.

  10. Real-time determination of the signal-to-noise ratio of partly coherent seismic time series

    DEFF Research Database (Denmark)

    Kjeldsen, Peter Møller

    1994-01-01

    A suitable measure of the quality of signals used in exploration seismics is the signal-to-noise ratio (S/N) of the recorded signals (traces). However, the S/N of the single unstacked traces may vary considerably due to changing weather conditions during the exploration session. Since...

  11. Modeling high signal-to-noise ratio in a novel silicon MEMS microphone with comb readout

    Science.gov (United States)

    Manz, Johannes; Dehe, Alfons; Schrag, Gabriele

    2017-05-01

    Strong competition within the consumer market urges the companies to constantly improve the quality of their devices. For silicon microphones excellent sound quality is the key feature in this respect which means that improving the signal-to-noise ratio (SNR), being strongly correlated with the sound quality is a major task to fulfill the growing demands of the market. MEMS microphones with conventional capacitive readout suffer from noise caused by viscous damping losses arising from perforations in the backplate [1]. Therefore, we conceived a novel microphone design based on capacitive read-out via comb structures, which is supposed to show a reduction in fluidic damping compared to conventional MEMS microphones. In order to evaluate the potential of the proposed design, we developed a fully energy-coupled, modular system-level model taking into account the mechanical motion, the slide film damping between the comb fingers, the acoustic impact of the package and the capacitive read-out. All submodels are physically based scaling with all relevant design parameters. We carried out noise analyses and due to the modular and physics-based character of the model, were able to discriminate the noise contributions of different parts of the microphone. This enables us to identify design variants of this concept which exhibit a SNR of up to 73 dB (A). This is superior to conventional and at least comparable to high-performance variants of the current state-of-the art MEMS microphones [2].

  12. Noise Reduction of Steel Cord Conveyor Belt Defect Electromagnetic Signal by Combined Use of Improved Wavelet and EMD

    Directory of Open Access Journals (Sweden)

    Hong-Wei Ma

    2016-09-01

    Full Text Available In order to reduce the noise of a defect electromagnetic signal of the steel cord conveyor belt used in coal mines, a new signal noise reduction method by combined use of the improved threshold wavelet and Empirical Mode Decomposition (EMD is proposed. Firstly, the denoising method based on the improved threshold wavelet is applied to reduce the noise of a defect electromagnetic signal obtained by an electromagnetic testing system. Then, the EMD is used to decompose the denoised signal and then the effective Intrinsic Mode Function (IMF is extracted by the dominant eigenvalue strategy. Finally, the signal reconstruction is carried out by utilizing the obtained IMF. In order to verify the proposed noise reduction method, the experiments are carried out in two cases including the defective joint and steel wire rope break. The experimental results show that the proposed method in this paper obtains the higher Signal to Noise Ratio (SNR for the defect electromagnetic signal noise reduction of steel cord conveyor belts.

  13. Effects of signal features and background noise on distance cue discrimination by a songbird.

    Science.gov (United States)

    Pohl, Nina U; Klump, Georg M; Langemann, Ulrike

    2015-04-01

    During the transmission of acoustic signals, the spectral and temporal properties of the original signal are degraded, and with increasing distance more and more echo patterns are imposed. It is well known that these physical alterations provide useful cues to assess the distance of a sound source. Previous studies in birds have shown that birds employ the degree of degradation of a signal to estimate the distance of another singing male (referred to as ranging). Little is known about how acoustic masking by background noise interferes with ranging, and if the number of song elements and stimulus familiarity affect the ability to discriminate between degraded and undegraded signals. In this study we trained great tits (Parus major L.) to discriminate between signal variants in two background types, a silent condition and a condition consisting of a natural dawn chorus. We manipulated great tit song types to simulate patterns of reverberation and degradation equivalent to transmission distances of between 5 and 160 m. The birds' responses were significantly affected by the differences between the signal variants and by background type. In contrast, stimulus familiarity or their element number had no significant effect on signal discrimination. Although background type was a significant main effect with respect to the response latencies, the great tits' overall performance in the noisy dawn chorus was similar to the performance in silence. © 2015. Published by The Company of Biologists Ltd.

  14. Signal-to-Noise Ratio Measures Efficacy of Biological Computing Devices and Circuits

    Science.gov (United States)

    Beal, Jacob

    2015-01-01

    Engineering biological cells to perform computations has a broad range of important potential applications, including precision medical therapies, biosynthesis process control, and environmental sensing. Implementing predictable and effective computation, however, has been extremely difficult to date, due to a combination of poor composability of available parts and of insufficient characterization of parts and their interactions with the complex environment in which they operate. In this paper, the author argues that this situation can be improved by quantitative signal-to-noise analysis of the relationship between computational abstractions and the variation and uncertainty endemic in biological organisms. This analysis takes the form of a ΔSNRdB function for each computational device, which can be computed from measurements of a device’s input/output curve and expression noise. These functions can then be combined to predict how well a circuit will implement an intended computation, as well as evaluating the general suitability of biological devices for engineering computational circuits. Applying signal-to-noise analysis to current repressor libraries shows that no library is currently sufficient for general circuit engineering, but also indicates key targets to remedy this situation and vastly improve the range of computations that can be used effectively in the implementation of biological applications. PMID:26177070

  15. Skalabilitas Signal to Noise Ratio (SNR pada Pengkodean Video dengan Derau Gaussian

    Directory of Open Access Journals (Sweden)

    Agus Purwadi

    2015-04-01

    Full Text Available In video transmission, there is a possibility of packet lost an d a large load variation on the bandwidth. These are the source of network congestion, which can interfere the communication data rate. This study discusses a system to overcome the congestion with Signal-to-noise ratio (SNR scalability-based approach, for the video sequence encoding method into two layers, which is a solution to decrease encoding mode for each packet and channel coding rate. The goal is to minimize any distortion from the source to the destination. The coding system used is a video coding standards that is MPEG-2 or H.263 with SNR scalability. The algorithm used for motion compensation, temporal redundancy and spatial redundancy is the Discrete Cosine Transform (DCT and quantization. The transmission error is simulated by adding Gaussian noise (error on motion vectors. From the simulation results, the SNR and Peak Signal to Noise Ratio (PSNR in the noisy video frames decline with averages of 3dB and 4dB respectively.

  16. Noise Reduction of MEMS Gyroscope Based on Direct Modeling for an Angular Rate Signal

    Directory of Open Access Journals (Sweden)

    Liang Xue

    2015-02-01

    Full Text Available In this paper, a novel approach for processing the outputs signal of the microelectromechanical systems (MEMS gyroscopes was presented to reduce the bias drift and noise. The principle for the noise reduction was presented, and an optimal Kalman filter (KF was designed by a steady-state filter gain obtained from the analysis of KF observability. In particular, the true angular rate signal was directly modeled to obtain an optimal estimate and make a self-compensation for the gyroscope without needing other sensor’s information, whether in static or dynamic condition. A linear fit equation that describes the relationship between the KF bandwidth and modeling parameter of true angular rate was derived from the analysis of KF frequency response. The test results indicated that the MEMS gyroscope having an ARW noise of 4.87°/h0.5 and a bias instability of 44.41°/h were reduced to 0.4°/h0.5 and 4.13°/h by the KF under a given bandwidth (10 Hz, respectively. The 1σ estimated error was reduced from 1.9°/s to 0.14°/s and 1.7°/s to 0.5°/s in the constant rate test and swing rate test, respectively. It also showed that the filtered angular rate signal could well reflect the dynamic characteristic of the input rate signal in dynamic conditions. The presented algorithm is proved to be effective at improving the measurement precision of the MEMS gyroscope.

  17. Capacity-Approaching Signal Constellations for the Additive Exponential Noise Channel

    CERN Document Server

    Goff, Stéphane Y Le

    2011-01-01

    We present a new family of signal constellations, called log constellations, that can be used to design near-capacity coded modulation schemes over additive exponential noise (AEN) channels. Log constellations are designed by geometrically approximating the input distribution that maximizes the AEN channel capacity. The mutual information achievable over AEN channels with both coded modulation (CM) and bit-interleaved coded modulation (BICM) approaches is evaluated for various signal sets. In the case of CM, the proposed log constellations outperform, sometimes by over half a decibel, the best existing signal sets available from the literature, and can display error performance within only 0.12 dB of the AEN channel capacity. In the context of BICM, log constellations do not offer significant performance advantages over the best existing constellations. As the potential performance degradation resulting from the use of BICM instead of CM is larger than 1 dB, BICM may however not be a suitable design approach ...

  18. VLSI implementation of a new LMS-based algorithm for noise removal in ECG signal

    Science.gov (United States)

    Satheeskumaran, S.; Sabrigiriraj, M.

    2016-06-01

    Least mean square (LMS)-based adaptive filters are widely deployed for removing artefacts in electrocardiogram (ECG) due to less number of computations. But they posses high mean square error (MSE) under noisy environment. The transform domain variable step-size LMS algorithm reduces the MSE at the cost of computational complexity. In this paper, a variable step-size delayed LMS adaptive filter is used to remove the artefacts from the ECG signal for improved feature extraction. The dedicated digital Signal processors provide fast processing, but they are not flexible. By using field programmable gate arrays, the pipelined architectures can be used to enhance the system performance. The pipelined architecture can enhance the operation efficiency of the adaptive filter and save the power consumption. This technique provides high signal-to-noise ratio and low MSE with reduced computational complexity; hence, it is a useful method for monitoring patients with heart-related problem.

  19. Development of a simple low noise amplifier for recording of sensory mass signals from peripheral nerves.

    Science.gov (United States)

    Stieglitz, Thomas; Klausmann, Dominic; Krueger, Thilo B

    2009-02-01

    In the present work, a simple low noise amplifier system with relatively few components for the recording of peripheral nerve signals via electrodes, such as cuff electrodes, was developed. The amplifier system was developed with the aid of a computer-aided characterization tool, which allowed the characterization of bioelectric signal amplifiers and the identification of system parameters. Three commercially available amplifier systems were investigated with this tool regarding their technical parameters. In addition, peripheral sensory nerve mass signals were analyzed to validate the target specifications for the amplifier to be designed with regard to amplitude and frequency range. An amplifier was designed and developed according to these specifications, characterized in comparison to the commercial amplifiers, and successfully applied in pilot experiments on the sciatic nerve in a rat animal model.

  20. Impact of in-band crosstalk and amplified spontaneous emission noise in differentially phase-shift keying signal

    Science.gov (United States)

    Kim, Chul Han

    2017-09-01

    The relative impact of in-band crosstalk and amplified spontaneous emission (ASE) noise on a system's performance has been investigated with a differentially phase-shift keying signal. I have first measured an ASE noise-induced penalty without any in-band crosstalk and then estimated the system's penalty with a simple addition of the measured ASE noise-induced penalty and the calculated in-band crosstalk-induced penalty. Using this approach, the estimated penalty agreed well with a measured system penalty when the Q value was 3 or an optical signal-to-noise ratio (OSNR) of the signal was higher than 30 dB at Q=6. To estimate the system penalty with a low OSNR level at Q=6, an addition of signal-ASE and signal-in-band crosstalk beat noises were added with a weighting factor. Based on this approach, a discrepancy between the estimated and the measured penalties was reduced drastically with an OSNR of 20 dB at Q=6. However, a small discrepancy was still observed even with the weighted addition of two beat noises. Thus, I have confirmed that the effect of in-band crosstalk-in-band crosstalk beat noise should be taken into account for the proper estimation of a system penalty with an OSNR of <30 dB at Q=6.

  1. Real-time Signal-to-noise Ratio (SNR) Estimation for BPSK and QPSK Modulation Using the Active Communications Channel

    Science.gov (United States)

    Manning, Robert M. (Inventor)

    2007-01-01

    Method and apparatus for estimating signal-to-noise ratio (SNR) gamma of a composite input signal e(t) on a phase modulated (e.g., BPSK) communications link. A first demodulator receives the composite input signal and a stable carrier signal and outputs an in-phase output signal; a second demodulator receives the composite input signal and a phase-shifted version of the carrier signal and outputs a quadrature-phase output signal; and phase error theta(sub E)(t) contained within the composite input signal e(t) is calculated from the outputs of the first and second demodulators. A time series of statistically independent phase error measurements theta(sub E)(t(sub 1)), theta (sub E)(t(sub 2)),..., theta (sub E)(t(sub k)) is obtained from the composite input signal subtending a time interval delta t = t(sub k) - t(sub 1) whose value is small enough such that gamma(t) and sigma(t) can be taken to be constant in delta t. A biased estimate gamma(sup *) for the signal-to-noise ratio (SNR) gamma if the composite input signal is calculated using maximum likelihood (ML) estimation techniques, and an unbiased estimate gamma(sup ^) for the signal-to-noise ratio (SNR) gamma of the composite input signal is determined from the biased estimate gamma(sup *), such as by use of a look-up table.

  2. Spatial Prediction Filtering of Acoustic Clutter and Random Noise in Medical Ultrasound Imaging.

    Science.gov (United States)

    Shin, Junseob; Huang, Lianjie

    2017-02-01

    One of the major challenges in array-based medical ultrasound imaging is the image quality degradation caused by sidelobes and off-axis clutter, which is an inherent limitation of the conventional delay-and-sum (DAS) beamforming operating on a finite aperture. Ultrasound image quality is further degraded in imaging applications involving strong tissue attenuation and/or low transmit power. In order to effectively suppress acoustic clutter from off-axis targets and random noise in a robust manner, we introduce in this paper a new adaptive filtering technique called frequency-space (F-X) prediction filtering or FXPF, which was first developed in seismic imaging for random noise attenuation. Seismologists developed FXPF based on the fact that linear and quasilinear events or wavefronts in the time-space (T-X) domain are manifested as a superposition of harmonics in the frequency-space (F-X) domain, which can be predicted using an auto-regressive (AR) model. We describe the FXPF technique as a spectral estimation or a direction-of-arrival problem, and explain why adaptation of this technique into medical ultrasound imaging is beneficial. We apply our new technique to simulated and tissue-mimicking phantom data. Our results demonstrate that FXPF achieves CNR improvements of 26% in simulated noise-free anechoic cyst, 109% in simulated anechoic cyst contaminated with random noise of 15 dB SNR, and 93% for experimental anechoic cyst from a custom-made tissue-mimicking phantom. Our findings suggest that FXPF is an effective technique to enhance ultrasound image contrast and has potential to improve the visualization of clinically important anatomical structures and diagnosis of diseased conditions.

  3. Signal-Induced Noise Effects in a Photon Counting System for Stratospheric Ozone Measurement

    Science.gov (United States)

    Harper, David B.; DeYoung, Russell J.

    1998-01-01

    Signal-induced noise (SIN) is a common effect resulting when a photomultiplier tube (PMT) is saturated, for a brief moment, with a high intensity light pulse. After the laser pulse is sent into the atmosphere a very large light return, from either the near-field or a cloud, causes the PMT to momentarily saturate. The PMT is gated off at this time so no signal is seen at the anode. When the PMT gate is turned on, the far-field light return from the atmosphere is observed. This signal is distorted, however because of the addition of SIN to the received light signal causing a slower than expected decay of the atmospheric signal return. We have characterized SIN responses to varying parameters of the incident light on the PMT. These varied parameters included incident wavelength, PMT voltage, incident intensity, and tube type. We found that only the amplitude of the SIN was effected by varying PMT voltages and light intensities. The amplitude increased linearly as input light intensity increased. Different incident wavelengths at the same intensity did not effect the amplitude or the temporal behavior of the SIN response. Finally, different PMT tubes with similar physical structures exhibited similar SIN responses although with different amplitudes. The different amplitudes can be attributed to the different gains and operating voltages of each tube. These results suggest that SIN is caused by photocathode electron dynamics such as charge accumulation on internal PMT surfaces. These surfaces then emit the electrons slowly resulting in a long decay noise signal. With the SIN responses characterized we can now try to develop a method to reduce or eliminate SIN in DIAL systems.

  4. Effects of manipulating the signal-to-noise envelope power ratio on speech intelligibility

    DEFF Research Database (Denmark)

    Jørgensen, Søren; Decorsière, Remi Julien Blaise; Dau, Torsten

    2015-01-01

    Jørgensen and Dau [(2011). J. Acoust. Soc. Am. 130, 1475–1487] suggested a metric for speech intelligibility prediction based on the signal-to-noise envelope power ratio (SNRenv), calculated at the output of a modulation-frequency selective process. In the framework of the speech-based envelope...... power spectrum model (sEPSM), the SNRenv was demonstrated to account for speech intelligibility data in various conditions with linearly and nonlinearly processed noisy speech, as well as for conditions with stationary and fluctuating interferers. Here, the relation between the SNRenv and speech...... intelligibility was investigated further by systematically varying the modulation power of either the speech or the noise before mixing the two components, while keeping the overall power ratio of the two components constant. A good correspondence between the data and the corresponding sEPSM predictions...

  5. GPS low noise amplifier with high immunity to wireless jamming signals and power control option

    Directory of Open Access Journals (Sweden)

    H. Schulz

    2004-01-01

    Full Text Available A SiGe GPS low noise amplifier with power control option and high immunity to wireless jamming signals is presented. These novel features applied to Atmel’s ATR0610 GPS LNA allow significant power saving at the radio interface while meeting the out-of-band linearity requirements. The results show the noise figure less than 2.1 dB, including the embedded pre-select filter, and out-of-band IIP3 above +8 dBm in the frequency range between 1.8GHz and 2 GHz with 3mA current consumption. The GPS system performance shows GPS sensitivity below -141 dBm with 5 ms integration interval.

  6. Noise Gating Solar Images

    Science.gov (United States)

    DeForest, Craig; Seaton, Daniel B.; Darnell, John A.

    2017-08-01

    I present and demonstrate a new, general purpose post-processing technique, "3D noise gating", that can reduce image noise by an order of magnitude or more without effective loss of spatial or temporal resolution in typical solar applications.Nearly all scientific images are, ultimately, limited by noise. Noise can be direct Poisson "shot noise" from photon counting effects, or introduced by other means such as detector read noise. Noise is typically represented as a random variable (perhaps with location- or image-dependent characteristics) that is sampled once per pixel or once per resolution element of an image sequence. Noise limits many aspects of image analysis, including photometry, spatiotemporal resolution, feature identification, morphology extraction, and background modeling and separation.Identifying and separating noise from image signal is difficult. The common practice of blurring in space and/or time works because most image "signal" is concentrated in the low Fourier components of an image, while noise is evenly distributed. Blurring in space and/or time attenuates the high spatial and temporal frequencies, reducing noise at the expense of also attenuating image detail. Noise-gating exploits the same property -- "coherence" -- that we use to identify features in images, to separate image features from noise.Processing image sequences through 3-D noise gating results in spectacular (more than 10x) improvements in signal-to-noise ratio, while not blurring bright, resolved features in either space or time. This improves most types of image analysis, including feature identification, time sequence extraction, absolute and relative photometry (including differential emission measure analysis), feature tracking, computer vision, correlation tracking, background modeling, cross-scale analysis, visual display/presentation, and image compression.I will introduce noise gating, describe the method, and show examples from several instruments (including SDO

  7. The tradeoff between signal detection and recognition rules auditory sensitivity under variable background noise conditions.

    Science.gov (United States)

    Lugli, Marco

    2015-12-07

    Animal acoustic communication commonly takes place under masked conditions. For instance, sound signals relevant for mating and survival are very often masked by background noise, which makes their detection and recognition by organisms difficult. Ambient noise (AN) varies in level and shape among different habitats, but also remarkable variations in time and space occurs within the same habitat. Variable AN conditions mask hearing thresholds of the receiver in complex and unpredictable ways, thereby causing distortions in sound perception. When communication takes place in a noisy environment, a highly sensitive system might confer no advantage to the receiver compared to a less sensitive one. The effects of noise masking on auditory thresholds and hearing-related functions are well known, and the potential role of AN in the evolution of the species' auditory sensitivity has been recognized by few authors. The mechanism of the underlying selection process has never been explored, however. Here I present a simple fitness model that seeks for the best sensitivity of a hearing system performing the detection and recognition of the sound under variable AN conditions. The model predicts higher sensitivity (i.e. lower hearing thresholds) as best strategy for species living in quiet habitats and lower sensitivity (i.e. higher hearing thresholds) as best strategy for those living in noisy habitats provided the cost of incorrect recognition is not low. The tradeoff between detection and recognition of acoustic signals appears to be a key factor determining the best level of hearing sensitivity of a species when acoustic communication is corrupted by noise. Copyright © 2015 Elsevier Ltd. All rights reserved.

  8. Subjective assessment of cochlear implant users' signal-to-noise ratio requirements for different levels of wireless device usability.

    Science.gov (United States)

    Julstrom, Stephen; Kozma-Spytek, Linda

    2014-01-01

    In order to better inform the development and revision of the American National Standards Institute C63.19 and American National Standards Institute/Telecommunications Industry Association-1083 hearing aid compatibility standards, a previous study examined the signal strength and signal (speech)-to-noise (interference) ratio needs of hearing aid users when using wireless and cordless phones in the telecoil coupling mode. This study expands that examination to cochlear implant (CI) users, in both telecoil and microphone modes of use. The purpose of this study was to evaluate the magnetic and acoustic signal levels needed by CI users for comfortable telephone communication and the users' tolerance relative to the speech levels of various interfering wireless communication-related noise types. Design was a descriptive and correlational study. Simulated telephone speech and eight interfering noise types presented as continuous signals were linearly combined and were presented together either acoustically or magnetically to the participants' CIs. The participants could adjust the loudness of the telephone speech and the interfering noises based on several assigned criteria. The 21 test participants ranged in age from 23-81 yr. All used wireless phones with their CIs, and 15 also used cordless phones at home. There were 12 participants who normally used the telecoil mode for telephone communication, whereas 9 used the implant's microphone; all were tested accordingly. A guided-intake questionnaire yielded general background information for each participant. A custom-built test control box fed by prepared speech-and-noise files enabled the tester or test participant, as appropriate, to switch between the various test signals and to precisely control the speech-and-noise levels independently. The tester, but not the test participant, could read and record the selected levels. Subsequent analysis revealed the preferred speech levels, speech (signal)-to-noise ratios, and the

  9. Signal to noise ratio of energy selective x-ray photon counting systems with pileup.

    Science.gov (United States)

    Alvarez, Robert E

    2014-11-01

    To derive fundamental limits on the effect of pulse pileup and quantum noise in photon counting detectors on the signal to noise ratio (SNR) and noise variance of energy selective x-ray imaging systems. An idealized model of the response of counting detectors to pulse pileup is used. The model assumes a nonparalyzable response and delta function pulse shape. The model is used to derive analytical formulas for the noise and energy spectrum of the recorded photons with pulse pileup. These formulas are first verified with a Monte Carlo simulation. They are then used with a method introduced in a previous paper [R. E. Alvarez, "Near optimal energy selective x-ray imaging system performance with simple detectors," Med. Phys. 37, 822-841 (2010)] to compare the signal to noise ratio with pileup to the ideal SNR with perfect energy resolution. Detectors studied include photon counting detectors with pulse height analysis (PHA), detectors that simultaneously measure the number of photons and the integrated energy (NQ detector), and conventional energy integrating and photon counting detectors. The increase in the A-vector variance with dead time is also computed and compared to the Monte Carlo results. A formula for the covariance of the NQ detector is developed. The validity of the constant covariance approximation to the Cramèr-Rao lower bound (CRLB) for larger counts is tested. The SNR becomes smaller than the conventional energy integrating detector (Q) SNR for 0.52, 0.65, and 0.78 expected number photons per dead time for counting (N), two, and four bin PHA detectors, respectively. The NQ detector SNR is always larger than the N and Q SNR but only marginally so for larger dead times. Its noise variance increases by a factor of approximately 3 and 5 for the A1 and A2 components as the dead time parameter increases from 0 to 0.8 photons per dead time. With four bin PHA data, the increase in variance is approximately 2 and 4 times. The constant covariance approximation

  10. Impacts of regular and random noise on the behaviour, growth and development of larval Atlantic cod (Gadus morhua).

    Science.gov (United States)

    Nedelec, Sophie L; Simpson, Stephen D; Morley, Erica L; Nedelec, Brendan; Radford, Andrew N

    2015-10-22

    Anthropogenic noise impacts behaviour and physiology in many species, but responses could change with repeat exposures. As repeat exposures can vary in regularity, identifying regimes with less impact is important for regulation. We use a 16-day split-brood experiment to compare effects of regular and random acoustic noise (playbacks of recordings of ships), relative to ambient-noise controls, on behaviour, growth and development of larval Atlantic cod (Gadus morhua). Short-term noise caused startle responses in newly hatched fish, irrespective of rearing noise. Two days of both regular and random noise regimes reduced growth, while regular noise led to faster yolk sac use. After 16 days, growth in all three sound treatments converged, although fish exposed to regular noise had lower body width-length ratios. Larvae with lower body width-length ratios were easier to catch in a predator-avoidance experiment. Our results demonstrate that the timing of acoustic disturbances can impact survival-related measures during development. Much current work focuses on sound levels, but future studies should consider the role of noise regularity and its importance for noise management and mitigation measures. © 2015 The Authors.

  11. Average bit error probability of binary coherent signaling over generalized fading channels subject to additive generalized gaussian noise

    KAUST Repository

    Soury, Hamza

    2012-06-01

    This letter considers the average bit error probability of binary coherent signaling over flat fading channels subject to additive generalized Gaussian noise. More specifically, a generic closed form expression in terms of the Fox\\'s H function is offered for the extended generalized-K fading case. Simplifications for some special fading distributions such as generalized-K fading and Nakagami-m fading and special additive noise distributions such as Gaussian and Laplacian noise are then presented. Finally, the mathematical formalism is illustrated by some numerical examples verified by computer based simulations for a variety of fading and additive noise parameters. © 2012 IEEE.

  12. Exact Symbol Error Probability of Square M-QAM Signaling over Generalized Fading Channels subject to Additive Generalized Gaussian Noise

    KAUST Repository

    Soury, Hamza

    2013-07-01

    This paper considers the average symbol error probability of square Quadrature Amplitude Modulation (QAM) coherent signaling over flat fading channels subject to additive generalized Gaussian noise. More specifically, a generic closedform expression in terms of the Fox H function and the bivariate Fox H function is offered for the extended generalized-K fading case. Simplifications for some special fading distributions such as generalized-K fading, Nakagami-m fading, and Rayleigh fading and special additive noise distributions such as Gaussian and Laplacian noise are then presented. Finally, the mathematical formalism is illustrated by some numerical examples verified by computer based simulations for a variety of fading and additive noise parameters.

  13. Brain-computer interfaces increase whole-brain signal to noise.

    Science.gov (United States)

    Papageorgiou, T Dorina; Lisinski, Jonathan M; McHenry, Monica A; White, Jason P; LaConte, Stephen M

    2013-08-13

    Brain-computer interfaces (BCIs) can convert mental states into signals to drive real-world devices, but it is not known if a given covert task is the same when performed with and without BCI-based control. Using a BCI likely involves additional cognitive processes, such as multitasking, attention, and conflict monitoring. In addition, it is challenging to measure the quality of covert task performance. We used whole-brain classifier-based real-time functional MRI to address these issues, because the method provides both classifier-based maps to examine the neural requirements of BCI and classification accuracy to quantify the quality of task performance. Subjects performed a covert counting task at fast and slow rates to control a visual interface. Compared with the same task when viewing but not controlling the interface, we observed that being in control of a BCI improved task classification of fast and slow counting states. Additional BCI control increased subjects' whole-brain signal-to-noise ratio compared with the absence of control. The neural pattern for control consisted of a positive network comprised of dorsal parietal and frontal regions and the anterior insula of the right hemisphere as well as an expansive negative network of regions. These findings suggest that real-time functional MRI can serve as a platform for exploring information processing and frontoparietal and insula network-based regulation of whole-brain task signal-to-noise ratio.

  14. Noise reduction in brainwaves by using both EEG signals and frontal viewing camera images.

    Science.gov (United States)

    Bang, Jae Won; Choi, Jong-Suk; Park, Kang Ryoung

    2013-05-13

    Electroencephalogram (EEG)-based brain-computer interfaces (BCIs) have been used in various applications, including human-computer interfaces, diagnosis of brain diseases, and measurement of cognitive status. However, EEG signals can be contaminated with noise caused by user's head movements. Therefore, we propose a new method that combines an EEG acquisition device and a frontal viewing camera to isolate and exclude the sections of EEG data containing these noises. This method is novel in the following three ways. First, we compare the accuracies of detecting head movements based on the features of EEG signals in the frequency and time domains and on the motion features of images captured by the frontal viewing camera. Second, the features of EEG signals in the frequency domain and the motion features captured by the frontal viewing camera are selected as optimal ones. The dimension reduction of the features and feature selection are performed using linear discriminant analysis. Third, the combined features are used as inputs to support vector machine (SVM), which improves the accuracy in detecting head movements. The experimental results show that the proposed method can detect head movements with an average error rate of approximately 3.22%, which is smaller than that of other methods.

  15. Noise Reduction in Brainwaves by Using Both EEG Signals and Frontal Viewing Camera Images

    Directory of Open Access Journals (Sweden)

    Kang Ryoung Park

    2013-05-01

    Full Text Available Electroencephalogram (EEG-based brain-computer interfaces (BCIs have been used in various applications, including human–computer interfaces, diagnosis of brain diseases, and measurement of cognitive status. However, EEG signals can be contaminated with noise caused by user’s head movements. Therefore, we propose a new method that combines an EEG acquisition device and a frontal viewing camera to isolate and exclude the sections of EEG data containing these noises. This method is novel in the following three ways. First, we compare the accuracies of detecting head movements based on the features of EEG signals in the frequency and time domains and on the motion features of images captured by the frontal viewing camera. Second, the features of EEG signals in the frequency domain and the motion features captured by the frontal viewing camera are selected as optimal ones. The dimension reduction of the features and feature selection are performed using linear discriminant analysis. Third, the combined features are used as inputs to support vector machine (SVM, which improves the accuracy in detecting head movements. The experimental results show that the proposed method can detect head movements with an average error rate of approximately 3.22%, which is smaller than that of other methods.

  16. Phenomenological analysis of random telegraph noise in amorphous TiOx-based bipolar resistive switching random access memory devices.

    Science.gov (United States)

    Lee, Jung-Kyu; Lee, Ju-Wan; Bae, Jong-Ho; Park, Jinwon; Chung, Sung-Woong; Roh, Jae Sung; Hong, Sung-Joo; Lee, Jong-Ho

    2012-07-01

    As dimensions of resistive random access memories (RRAMs) devices continue to shrink, the low-frequency noise of nanoscale devices has become increasingly important in evaluating the device reliability. Thus, we investigated random telegraph noise (RTN) caused by capture and emission of an electron at traps. We physically analyzed capture and emission processes through systematic measurements of amorphous TiOx (alpha-TiOx)-based bipolar RRAMs. RTNs were observed during high-resistance state (HRS) in most devices. However, discrete switching behavior was scarcely observed in low-resistance state (LRS) as most of traps in the alpha-TiOx were filled with mobile ions such as O2- in LRS. The capture and emission processes of an electron at traps are largely divided into two groups: (1) both capture and emission processes are mainly affected by electric field; and (2) one of the capture and emission processes is only influenced by the thermal process. This paper provides fundamental physics required to understand the mechanism of RTNs in alpha-TiOx-based bipolar RRAMs.

  17. Kalman Filtering for Discrete Stochastic Systems with Multiplicative Noises and Random Two-Step Sensor Delays

    Directory of Open Access Journals (Sweden)

    Dongyan Chen

    2015-01-01

    Full Text Available This paper is concerned with the optimal Kalman filtering problem for a class of discrete stochastic systems with multiplicative noises and random two-step sensor delays. Three Bernoulli distributed random variables with known conditional probabilities are introduced to characterize the phenomena of the random two-step sensor delays which may happen during the data transmission. By using the state augmentation approach and innovation analysis technique, an optimal Kalman filter is constructed for the augmented system in the sense of the minimum mean square error (MMSE. Subsequently, the optimal Kalman filtering is derived for corresponding augmented system in initial instants. Finally, a simulation example is provided to demonstrate the feasibility and effectiveness of the proposed filtering method.

  18. Optimization of noise in non-integrated instrumentation amplifier for the amplification of very low electrophysiological [corrected] signals. Case of electro cardio graphic signals (ECG).

    Science.gov (United States)

    Ngounou, Guy Merlin; Kom, Martin

    2014-12-01

    In this paper we present an instrumentation amplifier with discrete elements and optimized noise for the amplification of very low signals. In amplifying signals of very weak amplitude, the noise can completely absorb these signals if the used amplifier does not present the optimal guarantee to minimize the noise. Based on related research and re-viewing of recent patents Journal of Medical Systems, 30:205-209, 2006, we suggest an approach of noise reduction in amplification much more thoroughly than re-viewing of recent patents and we deduce from it the general criteria necessary and essential to achieve this optimization. The comparison of these criteria with the provisions adopted in practice leads to the inadequacy of conventional amplifiers for effective noise reduction. The amplifier we propose is an instrumentation amplifier with active negative feedback and optimized noise for the amplification of signals with very low amplitude. The application of this method in the case of electro cardio graphic signals (ECG) provides simulation results fully in line with forecasts.

  19. Stimulation of the Locus Ceruleus Modulates Signal-to-Noise Ratio in the Olfactory Bulb.

    Science.gov (United States)

    Manella, Laura C; Petersen, Nicholas; Linster, Christiane

    2017-11-29

    Norepinephrine (NE) has been shown to influence sensory, and specifically olfactory processing at the behavioral and physiological levels, potentially by regulating signal-to-noise ratio (S/N). The present study is the first to look at NE modulation of olfactory bulb (OB) in regards to S/N in vivo We show, in male rats, that locus ceruleus stimulation and pharmacological infusions of NE into the OB modulate both spontaneous and odor-evoked neural responses. NE in the OB generated a non-monotonic dose-response relationship, suppressing mitral cell activity at high and low, but not intermediate, NE levels. We propose that NE enhances odor responses not through direct potentiation of the afferent signal per se, but rather by reducing the intrinsic noise of the system. This has important implications for the ways in which an animal interacts with its olfactory environment, particularly as the animal shifts from a relaxed to an alert behavioral state.SIGNIFICANCE STATEMENT Sensory perception can be modulated by behavioral states such as hunger, fear, stress, or a change in environmental context. Behavioral state often affects neural processing via the release of circulating neurochemicals such as hormones or neuromodulators. We here show that the neuromodulator norepinephrine modulates olfactory bulb spontaneous activity and odor responses so as to generate an increased signal-to-noise ratio at the output of the olfactory bulb. Our results help interpret and improve existing ideas for neural network mechanisms underlying behaviorally observed improvements in near-threshold odor detection and discrimination. Copyright © 2017 the authors 0270-6474/17/3711605-11$15.00/0.

  20. Signals and noise in magnetic observatory annual means - Mantle conductivity and jerks

    Science.gov (United States)

    McLeod, Malcolm G.

    1992-11-01

    Geomagnetic temporal variations can yield valuable information on the electrical conductivity of earth's mantle and on motion of core fluid. The external-source signal in first differences of magnetic observatory annual means is primarily due to a degree-one spherical harmonic closely aligned with earth's magnetic dipole axis. The transfer function between the electromagnetically induced degree-one internal Gauss coefficient (Schmidt seminormalized) and the inducing degree-one external Gauss coefficient is 0.089 +/- 0.020 with a phase shift of +/- 45 deg for a 2-year period. This transfer function is consistent with a nearly insulating mantle and a highly conducting core for which the theoretical transfer function is 0.082 with no phase shift. The temporal power spectrum for noise in first differences of magnetic observatory annual means is approximately white. Third differences of annual means are primarily noise and degree-one external-source signal; thus, when the degree-one external-source signal is removed from annual means third differences, the rms residuals for a given field component and time interval at a given observatory are a good indicator of noise for the relevant component, observatory, and time interval. These rms residuals were used as weights for construction of spherical harmonic models of geomagnetic secular variation. European secular variation graphs for the 1962-1983 time interval exhibit prominent changes of slope (geomagnetic jerks) in the geomagnetic east component at approximately 1970 and 1978. The jerk of 1970 (but not 1978) is evident on the geomagnetic north and vertical components. The vertical component exhibits additional slope changes at approximately 1966 and 1975.

  1. Noisy signaling: theory and experiment

    NARCIS (Netherlands)

    de Haan, T.; Offerman, T.; Sloof, R.

    2009-01-01

    We investigate a noisy signaling game, in which nature adds random noise to the message chosen. Theoretically, with an unfavorable prior the separating equilibrium vanishes for low noise. It reappears for intermediate and high noise, where messages increase with noise. A pooling equilibrium always

  2. Suppression of phase-induced intensity noise in fibre optic delay line signal processors using an optical phase modulation technique.

    Science.gov (United States)

    Chan, Erwin H W

    2010-10-11

    A technique that can suppress the dominant phase-induced intensity noise in fibre optic delay line signal processors is presented. It is based on phase modulation of the optical carrier to distribute the phase noise at the information band into a high frequency band which can be filtered out. This technique is suitable for suppressing the phase noise in various delay line structures and for integrating in the conventional fibre optic links. It can also suppress the coherent interference effect at the same time. A model for predicting the amount of phase noise reduction in various delay line structures using the optical phase modulation technique is presented for the first time and is experimentally verified. Experimental results demonstrate the technique can achieve a large phase noise reduction in various fibre optic delay line signal processors.

  3. MIMO Radar Transceiver Design for High Signal-to-Interference-Plus-Noise Ratio

    KAUST Repository

    Lipor, John

    2013-05-12

    Multiple-input multiple-output (MIMO) radar employs orthogonal or partially correlated transmit signals to achieve performance benefits over its phased-array counterpart. It has been shown that MIMO radar can achieve greater spatial resolution, improved signal-to-noise ratio (SNR) and target localization, and greater clutter resolution using space-time adaptive processing (STAP). This thesis explores various methods to improve the signal-to-interference-plus-noise ratio (SINR) via transmit and receive beamforming. In MIMO radar settings, it is often desirable to transmit power only to a given location or set of locations defined by a beampattern. Current methods involve a two- step process of designing the transmit covariance matrix R via iterative solutions and then using R to generate waveforms that fulfill practical constraints such as having a constant-envelope or drawing from a finite alphabet. In this document, a closed- form method to design R is proposed that utilizes the discrete Fourier transform (DFT) coefficients and Toeplitz matrices. The resulting covariance matrix fulfills the practical constraints such as positive semidefiniteness and the uniform elemental power constraint and provides performance similar to that of iterative methods, which require a much greater computation time. Next, a transmit architecture is presented 
that exploits the orthogonality of frequencies at discrete DFT values to transmit a sum of orthogonal signals from each antenna. The resulting waveforms provide a lower mean-square error than current methods at a much lower computational cost, and a simulated detection scenario demonstrates the performance advantages achieved. It is also desirable to receive signal power only from a given set of directions defined by a beampattern. In a later chapter of this document, the problem of receive beampattern matching is formulated and three solutions to this problem are demonstrated. We show that partitioning the received data vector

  4. Signal to Noise Studies on Thermographic Data with Fabricated Defects for Defense Structures

    Science.gov (United States)

    Zalameda, Joseph N.; Rajic, Nik; Genest, Marc

    2006-01-01

    There is a growing international interest in thermal inspection systems for asset life assessment and management of defense platforms. The efficacy of flash thermography is generally enhanced by applying image processing algorithms to the observations of raw temperature. Improving the defect signal to noise ratio (SNR) is of primary interest to reduce false calls and allow for easier interpretation of a thermal inspection image. Several factors affecting defect SNR were studied such as data compression and reconstruction using principal component analysis and time window processing.

  5. Signal to Noise Ratio Estimations for a Volcanic ASH Detection Lidar. Case Study: The Met Office

    Science.gov (United States)

    Georgoussis, George; Adam, Mariana; Avdikos, George

    2016-06-01

    In this paper we calculate the Signal-to-Noise (SNR) ratio of a 3-channel commercial (Raymetics) volcanic ash detection system, (LR111-D300), already operating under Met Office organization. The methodology for the accurate estimation is presented for day and nighttime conditions. The results show that SNR values are higher than 10 for ranges up to 13 km for both nighttime and daytime conditions. This is a quite good result compared with other values presented in bibliography and proves that such system is able to detect volcanic ash over a range of 20 km.

  6. Signal to Noise Ratio Estimations for a Volcanic ASH Detection Lidar. Case Study: The Met Office

    Directory of Open Access Journals (Sweden)

    Georgoussis George

    2016-01-01

    Full Text Available In this paper we calculate the Signal-to-Noise (SNR ratio of a 3-channel commercial (Raymetics volcanic ash detection system, (LR111-D300, already operating under Met Office organization. The methodology for the accurate estimation is presented for day and nighttime conditions. The results show that SNR values are higher than 10 for ranges up to 13 km for both nighttime and daytime conditions. This is a quite good result compared with other values presented in bibliography and proves that such system is able to detect volcanic ash over a range of 20 km.

  7. External Noise and External Signal Induced Transition of Gene Switch and Coherence Resonance in the Genetic Regulatory System.

    Science.gov (United States)

    Shi, Jian-Cheng; Luo, Min; Dong, Tao; Huang, Chu-Sheng

    2017-06-01

    The transition of gene switch induced by external noises (multiplicative external noise and additive external noise) and external signals is investigated in the genetic regulatory system. Results show that the state-to-state transition of gene switch as well as resonant behaviors, such as the explicit coherence resonance (ECR), implicit coherence resonance (ICR) and control parameter coherence biresonance (CPCBR), can appear when noises are injected into the genetic regulatory system. The ECR is increased with the increase of the control parameter value when starting from the supercritical Hopf bifurcation parameter point, and there exists a critical control parameter value for the occurrence of ECR. However, the ICR is decreased as the control parameter value is increased when starting from the subcritical Hopf bifurcation point. In particular, the coherence of ECR is higher and more sensitive to noise than that of ICR. When an external signal is introduced into the system, the enhancement or suppression of the CPCBR and the number of peaks strongly depend on the frequency and amplitude of the external signal. Furthermore, the gene regulation system can selectively enhance or decrease the noise-induced oscillation signals at preferred frequency and amplitude of an external signal.

  8. Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise

    Science.gov (United States)

    Brown, Patrick T.; Li, Wenhong; Cordero, Eugene C.; Mauget, Steven A.

    2015-01-01

    The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20th century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal. PMID:25898351

  9. Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise.

    Science.gov (United States)

    Brown, Patrick T; Li, Wenhong; Cordero, Eugene C; Mauget, Steven A

    2015-04-21

    The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20(th) century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal.

  10. Investigation of signal-to-noise ratio in frequency-domain multiphoton fluorescence lifetime imaging microscopy.

    Science.gov (United States)

    Zhang, Yide; Khan, Aamir A; Vigil, Genevieve D; Howard, Scott S

    2016-07-01

    Multiphoton microscopy (MPM) combined with fluorescence lifetime imaging microscopy (FLIM) has enabled three-dimensional quantitative molecular microscopy in vivo. The signal-to-noise ratio (SNR), and thus the imaging rate of MPM-FLIM, which is fundamentally limited by the shot noise and fluorescence saturation, has not been quantitatively studied yet. In this paper, we investigate the SNR performance of the frequency-domain (FD) MPM-FLIM with two figures of merit: the photon economy in the limit of shot noise, and the normalized SNR in the limit of saturation. The theoretical results and Monte Carlo simulations find that two-photon FD-FLIM requires 50% fewer photons to achieve the same SNR as conventional one-photon FLIM. We also analytically show that the MPM-FD-FLIM can exploit the DC and higher harmonic components generated by nonlinear optical mixing of the excitation light to improve SNR, reducing the required number of photons by an additional 50%. Finally, the effect of fluorophore saturation on the experimental SNR performance is discussed.

  11. Oscillation and noise determine signal transduction in shark multimodal sensory cells.

    Science.gov (United States)

    Braun, H A; Wissing, H; Schäfer, K; Hirsch, M C

    1994-01-20

    Oscillating membrane potentials that generate rhythmic impulse patterns are considered to be of particular significance for neuronal information processing. In contrast, noise is usually seen as a disturbance which limits the accuracy of information transfer. We show here, however, that noise in combination with intrinsic oscillations can provide neurons with particular encoding properties, a discovery we made when recording from single electro-sensory afferents of a fish. The temporal sequence of the impulse trains indicates oscillations that operate near the spike-triggering threshold. The oscillation frequency determines the basic rhythm of impulse generation, but whether or not an impulse is actually triggered essentially depends on superimposed noise. The probability of impulse generation can be altered considerably by minor modifications of oscillation baseline and amplitude, which may underlie the exquisite sensitivity of these receptors to thermal and electrical stimuli. Additionally, thermal, but not electrical, stimuli alter the oscillation frequency, allowing dual sensory messages to be conveyed in a single spike train. These findings demonstrate novel properties of sensory transduction which may be relevant for neuronal signalling in general.

  12. A complex symbol signal-to-noise ratio estimator and its performance

    Science.gov (United States)

    Feria, Y.

    1994-01-01

    This article presents an algorithm for estimating the signal-to-noise ratio (SNR) of signals that contain data on a downconverted suppressed carrier or the first harmonic of a square-wave subcarrier. This algorithm can be used to determine the performance of the full-spectrum combiner for the Galileo S-band (2.2- to 2.3-GHz) mission by measuring the input and output symbol SNR. A performance analysis of the algorithm shows that the estimator can estimate the complex symbol SNR using 10,000 symbols at a true symbol SNR of -5 dB with a mean of -4.9985 dB and a standard deviation of 0.2454 dB, and these analytical results are checked by simulations of 100 runs with a mean of -5.06 dB and a standard deviation of 0.2506 dB.

  13. Impact of hot-carrier degradation on the Low-Frequency Noise in MOSFETs under steady-state and periodic Large-Signal Excitation

    NARCIS (Netherlands)

    Kolhatkar, J.S.; Hoekstra, E.; Hof, A.J.; Salm, Cora; Schmitz, Jurriaan; Wallinga, Hans

    2005-01-01

    This letter reports the diagnostic power of the low-frequency noise analysis (steady-state and periodic large-signal excitation) in MOSFETs subjected to hot-carrier degradation. The LF noise under periodic large-signal excitation is shown to increase more rapidly than the LF noise in steady-state.

  14. Development of a Method for Selection of Effective Singular Values in Bearing Fault Signal De-Noising

    Directory of Open Access Journals (Sweden)

    Jie Gao

    2016-05-01

    Full Text Available Singular value decomposition (SVD is a widely used and powerful tool for signal extraction under noise. Noise attenuation relies on the selection of the effective singular value because these values are significant features of the useful signal. Traditional methods of selecting effective singular values (or selecting the useful components to rebuild the faulty signal consist of seeking the maximum peak of the differential spectrum of singular values. However, owing to the small number of selected effective singular values, these methods lead to excessive de-noised effects. In order to get a more appropriate number of effective singular values, which preserves the components of the original signal as much as possible, this paper used a difference curvature spectrum of incremental singular entropy to determine the number of effective singular values. Then the position was found where the difference of two peaks in the spectrum declines in an infinitely large degree for the first time, and this position was regarded as the boundary of singular values between noise and a useful signal. The experimental results showed that the modified methods could accurately extract the non-stationary bearing faulty signal under real background noise.

  15. Evaluating signal-to-noise ratios, loudness, and related measures as indicators of airborne sound insulation.

    Science.gov (United States)

    Park, H K; Bradley, J S

    2009-09-01

    Subjective ratings of the audibility, annoyance, and loudness of music and speech sounds transmitted through 20 different simulated walls were used to identify better single number ratings of airborne sound insulation. The first part of this research considered standard measures such as the sound transmission class the weighted sound reduction index (R(w)) and variations of these measures [H. K. Park and J. S. Bradley, J. Acoust. Soc. Am. 126, 208-219 (2009)]. This paper considers a number of other measures including signal-to-noise ratios related to the intelligibility of speech and measures related to the loudness of sounds. An exploration of the importance of the included frequencies showed that the optimum ranges of included frequencies were different for speech and music sounds. Measures related to speech intelligibility were useful indicators of responses to speech sounds but were not as successful for music sounds. A-weighted level differences, signal-to-noise ratios and an A-weighted sound transmission loss measure were good predictors of responses when the included frequencies were optimized for each type of sound. The addition of new spectrum adaptation terms to R(w) values were found to be the most practical approach for achieving more accurate predictions of subjective ratings of transmitted speech and music sounds.

  16. Free Energy Adjusted Peak Signal to Noise Ratio (FEA-PSNR) for Image Quality Assessment

    Science.gov (United States)

    Liu, Ning; Zhai, Guangtao

    2017-12-01

    Peak signal to noise ratio (PSNR), the de facto universal image quality metric has been widely criticized as having poor correlation with human subjective quality ratings. In this paper, it will be illustrated that the low performance of PSNR as an image quality metric is partially due to its inability of differentiating image contents. And it is revealed that the deviation between subjective score and PSNR for each type of distortions can be systematically captured by perceptual complexity of the target image. The free energy modelling technique is then introduced to simulate the human cognitive process and measure perceptual complexity of an image. Then it is shown that performance of PSNR can be effectively improved using a linear score mapping process considering image free energy and distortion type. The proposed free energy adjusted peak signal to noise ratio (FEA-PSNR) does not change computational steps the of ordinary PSNR and therefore it inherits the merits of being simple, derivable and physically meaningful. So FEA-PSNR can be easily integrated into existing PSNR based image processing systems to achieve more visually plausible results. And the proposed analysis approach can be extended to other types of image quality metrics for enhanced performance.

  17. The impact of signal-to-noise ratio on contextual cueing in children and adults.

    Science.gov (United States)

    Yang, Yingying; Merrill, Edward C

    2015-04-01

    Contextual cueing refers to a form of implicit spatial learning where participants incidentally learn to associate a target location with its repeated spatial context. Successful contextual learning produces an efficient visual search through familiar environments. Despite the fact that children exhibit the basic ability of implicit spatial learning, their general effectiveness in this form of learning can be compromised by other development-dependent factors. Learning to extract useful information (signal) in the presence of various amounts of irrelevant or distracting information (noise) characterizes one of the most important changes that occur with cognitive development. This research investigated whether signal-to-noise ratio (S/N) affects contextual cueing differently in children and adults. S/N was operationally defined as the ratio of repeated versus new displays encountered over time. Three ratio conditions were created: high (100%), medium (67%), and low (33%) conditions. Results suggested no difference in the acquisition of contextual learning effects in the high and medium conditions across three age groups (6- to 8-year-olds, 10- to 12-year-olds, and young adults). However, a significant developmental difference emerged in the low S/N condition. As predicted, adults exhibited significant contextual cueing effects, whereas older children showed marginally significant contextual cueing and younger children did not show cueing effects. Group differences in the ability to exhibit implicit contextual learning under low S/N conditions and the implications of this difference are discussed. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. Image artifacts and noise reduction algorithm for cone-beam computed tomography with low-signal projections.

    Science.gov (United States)

    Yang, Fu-Qiang; Zhang, Ding-Hua; Huang, Kui-Dong; Yang, Ya-Fei; Liao, Jin-Ming

    2017-10-10

    This study aims to investigate and test a new image reconstruction algorithm applying to the low-signal projections to generate high quality images by reducing the artifacts and noise in the cone-beam computed tomography (CBCT). For the low-signal and noisy projections, a multiple sampling method is first utilized in projection domain to suppress environmental noise, which guarantees the accuracy of the data for reconstruction, simultaneously. Next, a fuzzy entropy based method with block matching 3D (BM3D) filtering algorithm is employed to improve the image quality to reduce artifacts and noise in image domain. Then, simulation studies on polychromatic spectrum were performed to evaluate the performance of the proposed new algorithm. Study results demonstrated significant improvement in the signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) of the images reconstructed using the new algorithm. SNRs and CNRs of the new images were averagely 40% and 20% higher than those of the previous images reconstructed using the traditional algorithms, respectively. As a result, since the new image reconstruction algorithm effectively reduced the artifacts and noise, and produced images with better contour and grayscale distribution, it has the potential to improve image quality using the original CBCT data with the low and missing signals.

  19. Statistical analysis of random telegraph noise in HfO2-based RRAM devices in LRS

    Science.gov (United States)

    Puglisi, Francesco Maria; Pavan, Paolo; Larcher, Luca; Padovani, Andrea

    2015-11-01

    In this work, we present a thorough statistical characterization of Random Telegraph Noise (RTN) in HfO2-based Resistive Random Access Memory (RRAM) cells in Low Resistive State (LRS). Devices are tested under a variety of operational conditions. A Factorial Hidden Markov Model (FHMM) analysis is exploited to extrapolate the properties of the traps causing multi-level RTN in LRS. The trapping and de-trapping of charge carriers into/out of defects located in the proximity of the conductive filament results in a shielding effect on a portion of the conductive filament, leading to the observed RTN current fluctuations. It is found that both oxygen vacancies and oxygen ions defects may be responsible for the observed RTN. The variations of the current observed at subsequent set/reset cycles are instead attributed to the stochastic variations in the filament due to oxidation/reduction processes during reset and set operations, respectively.

  20. Transcranial Random Noise Stimulation Does Not Enhance the Effects of Working Memory Training.

    Science.gov (United States)

    Holmes, Joni; Byrne, Elizabeth M; Gathercole, Susan E; Ewbank, Michael P

    2016-10-01

    Transcranial random noise stimulation (tRNS), a noninvasive brain stimulation technique, enhances the generalization and sustainability of gains following mathematical training. Here it is combined for the first time with working memory training in a double-blind randomized controlled trial. Adults completed 10 sessions of Cogmed Working Memory Training with either active tRNS or sham stimulation applied bilaterally to dorsolateral pFC. Training was associated with gains on both the training tasks and on untrained tests of working memory that shared overlapping processes with the training tasks, but not with improvements on working memory tasks with distinct processing demands or tests of other cognitive abilities (e.g., IQ, maths). There was no evidence that tRNS increased the magnitude or transfer of these gains. Thus, combining tRNS with Cogmed Working Memory Training provides no additional therapeutic value.

  1. Random exponential attractor for cocycle and application to non-autonomous stochastic lattice systems with multiplicative white noise

    Science.gov (United States)

    Zhou, Shengfan

    2017-08-01

    We first establish some sufficient conditions for constructing a random exponential attractor for a continuous cocycle on a separable Banach space and weighted spaces of infinite sequences. Then we apply our abstract result to study the existence of random exponential attractors for non-autonomous first order dissipative lattice dynamical systems with multiplicative white noise.

  2. Estimating two-point statistics from derivatives of a signal containing noise: Application to auto-correlation functions of turbulent Lagrangian tracks.

    Science.gov (United States)

    Machicoane, N; Huck, P D; Volk, R

    2017-06-01

    This article describes a method for calculating moments and correlation functions of signal derivatives, which were rid of experimental noise without the use of filtering operations. The method is based on the computation of the ensemble-average of different time (or spatial) increments of the signal. The hypotheses are that the noise is white and not correlated with the signal; however, the method is also shown to work with colored noise. The method is first developed, considering white noise, and benchmarked with synthetic trajectories containing noise with variable signal-to-noise ratios. It is then tested on experimental trajectories in the context of Lagrangian tracking of particles in turbulent flows, either containing a short-correlated noise or a colored noise.

  3. Estimating two-point statistics from derivatives of a signal containing noise: Application to auto-correlation functions of turbulent Lagrangian tracks

    Science.gov (United States)

    Machicoane, N.; Huck, P. D.; Volk, R.

    2017-06-01

    This article describes a method for calculating moments and correlation functions of signal derivatives, which were rid of experimental noise without the use of filtering operations. The method is based on the computation of the ensemble-average of different time (or spatial) increments of the signal. The hypotheses are that the noise is white and not correlated with the signal; however, the method is also shown to work with colored noise. The method is first developed, considering white noise, and benchmarked with synthetic trajectories containing noise with variable signal-to-noise ratios. It is then tested on experimental trajectories in the context of Lagrangian tracking of particles in turbulent flows, either containing a short-correlated noise or a colored noise.

  4. Few-Flakes Reduced Graphene Oxide Sensors for Organic Vapors with a High Signal-to-Noise Ratio.

    Science.gov (United States)

    Hasan, Nowzesh; Zhang, Wenli; Radadia, Adarsh D

    2017-10-21

    This paper reports our findings on how to prepare a graphene oxide-based gas sensor for sensing fast pulses of volatile organic compounds with a better signal-to-noise ratio. We use rapid acetone pulses of varying concentrations to test the sensors. First, we compare the effect of graphene oxide deposition method (dielectrophoresis versus solvent evaporation) on the sensor's response. We find that dielectrophoresis yields films with uniform coverage and better sensor response. Second, we examine the effect of chemical reduction. Contrary to prior reports, we find that graphene oxide reduction leads to a reduction in sensor response and current noise, thus keeping the signal-to-noise ratio the same. We found that if we sonicated the sensor in acetone, we created a sensor with a few flakes of reduced graphene oxide. Such sensors provided a higher signal-to-noise ratio that could be correlated to the vapor concentration of acetone with better repeatability. Modeling shows that the sensor's response is due to one-site Langmuir adsorption or an overall single exponent process. Further, the desorption of acetone as deduced from the sensor recovery signal follows a single exponent process. Thus, we show a simple way to improve the signal-to-noise ratio in reduced graphene oxide sensors.

  5. Few-Flakes Reduced Graphene Oxide Sensors for Organic Vapors with a High Signal-to-Noise Ratio

    Directory of Open Access Journals (Sweden)

    Nowzesh Hasan

    2017-10-01

    Full Text Available This paper reports our findings on how to prepare a graphene oxide-based gas sensor for sensing fast pulses of volatile organic compounds with a better signal-to-noise ratio. We use rapid acetone pulses of varying concentrations to test the sensors. First, we compare the effect of graphene oxide deposition method (dielectrophoresis versus solvent evaporation on the sensor’s response. We find that dielectrophoresis yields films with uniform coverage and better sensor response. Second, we examine the effect of chemical reduction. Contrary to prior reports, we find that graphene oxide reduction leads to a reduction in sensor response and current noise, thus keeping the signal-to-noise ratio the same. We found that if we sonicated the sensor in acetone, we created a sensor with a few flakes of reduced graphene oxide. Such sensors provided a higher signal-to-noise ratio that could be correlated to the vapor concentration of acetone with better repeatability. Modeling shows that the sensor’s response is due to one-site Langmuir adsorption or an overall single exponent process. Further, the desorption of acetone as deduced from the sensor recovery signal follows a single exponent process. Thus, we show a simple way to improve the signal-to-noise ratio in reduced graphene oxide sensors.

  6. Random telegraph noise and resistance switching analysis of oxide based resistive memory.

    Science.gov (United States)

    Choi, Shinhyun; Yang, Yuchao; Lu, Wei

    2014-01-07

    Resistive random access memory (RRAM) devices (e.g."memristors") are widely believed to be a promising candidate for future memory and logic applications. Although excellent performance has been reported, the nature of resistance switching is still under extensive debate. In this study, we perform systematic investigation of the resistance switching mechanism in a TaOx based RRAM through detailed noise analysis, and show that the resistance switching from high-resistance to low-resistance is accompanied by a semiconductor-to-metal transition mediated by the accumulation of oxygen-vacancies in the conduction path. Specifically, pronounced random-telegraph noise (RTN) with values up to 25% was observed in the device high-resistance state (HRS) but not in the low-resistance state (LRS). Through time-domain and temperature dependent analysis, we show that the RTN effect shares the same origin as the resistive switching effects, and both can be traced to the (re)distribution of oxygen vacancies (VOs). From noise and transport analysis we further obtained the density of states and average distance of the VOs at different resistance states, and developed a unified model to explain the conduction in both the HRS and the LRS and account for the resistance switching effects in these devices. Significantly, it was found that even though the conduction channel area is larger in the HRS, during resistive switching a localized region gains significantly higher VO and dominates the conduction process. These findings reveal the complex dynamics involved during resistive switching and will help guide continued optimization in the design and operation of this important emerging device class.

  7. Is level irrelevant in "irrelevant speech"? Effects of loudness, signal-to-noise ratio, and binaural unmasking.

    Science.gov (United States)

    Ellermeier, W; Hellbruck, J

    1998-10-01

    A series of experiments explored the role of level, signal-to-noise ratio, and the masking-level difference in the irrelevant speech effect (ISE). In Experiment 1 the detrimental effects of irrelevant sound on serial recall were found to be the same whether the material (speech or music) was presented at a high (75 dB[A]) or low (60 dB[A]) overall level. In Experiment 2, adding pink noise to the speech signal produced a linear improvement in performance with decreasing speech-to-noise ratios. In Experiment 3 the contribution of binaural unmasking to the ISE was found to be negligible. The results (a) confirm that the segmented, changing nature of the irrelevant sound is crucial in producing the ISE and (b) suggest that the adverse effects of disruptive auditory input may be alleviated by introducing additional uniform masking noise.

  8. An artificial EMG generation model based on signal-dependent noise and related application to motion classification.

    Science.gov (United States)

    Furui, Akira; Hayashi, Hideaki; Nakamura, Go; Chin, Takaaki; Tsuji, Toshio

    2017-01-01

    This paper proposes an artificial electromyogram (EMG) signal generation model based on signal-dependent noise, which has been ignored in existing methods, by introducing the stochastic construction of the EMG signals. In the proposed model, an EMG signal variance value is first generated from a probability distribution with a shape determined by a commanded muscle force and signal-dependent noise. Artificial EMG signals are then generated from the associated Gaussian distribution with a zero mean and the generated variance. This facilitates representation of artificial EMG signals with signal-dependent noise superimposed according to the muscle activation levels. The frequency characteristics of the EMG signals are also simulated via a shaping filter with parameters determined by an autoregressive model. An estimation method to determine EMG variance distribution using rectified and smoothed EMG signals, thereby allowing model parameter estimation with a small number of samples, is also incorporated in the proposed model. Moreover, the prediction of variance distribution with strong muscle contraction from EMG signals with low muscle contraction and related artificial EMG generation are also described. The results of experiments conducted, in which the reproduction capability of the proposed model was evaluated through comparison with measured EMG signals in terms of amplitude, frequency content, and EMG distribution demonstrate that the proposed model can reproduce the features of measured EMG signals. Further, utilizing the generated EMG signals as training data for a neural network resulted in the classification of upper limb motion with a higher precision than by learning from only measured EMG signals. This indicates that the proposed model is also applicable to motion classification.

  9. An artificial EMG generation model based on signal-dependent noise and related application to motion classification

    Science.gov (United States)

    Hayashi, Hideaki; Nakamura, Go; Chin, Takaaki; Tsuji, Toshio

    2017-01-01

    This paper proposes an artificial electromyogram (EMG) signal generation model based on signal-dependent noise, which has been ignored in existing methods, by introducing the stochastic construction of the EMG signals. In the proposed model, an EMG signal variance value is first generated from a probability distribution with a shape determined by a commanded muscle force and signal-dependent noise. Artificial EMG signals are then generated from the associated Gaussian distribution with a zero mean and the generated variance. This facilitates representation of artificial EMG signals with signal-dependent noise superimposed according to the muscle activation levels. The frequency characteristics of the EMG signals are also simulated via a shaping filter with parameters determined by an autoregressive model. An estimation method to determine EMG variance distribution using rectified and smoothed EMG signals, thereby allowing model parameter estimation with a small number of samples, is also incorporated in the proposed model. Moreover, the prediction of variance distribution with strong muscle contraction from EMG signals with low muscle contraction and related artificial EMG generation are also described. The results of experiments conducted, in which the reproduction capability of the proposed model was evaluated through comparison with measured EMG signals in terms of amplitude, frequency content, and EMG distribution demonstrate that the proposed model can reproduce the features of measured EMG signals. Further, utilizing the generated EMG signals as training data for a neural network resulted in the classification of upper limb motion with a higher precision than by learning from only measured EMG signals. This indicates that the proposed model is also applicable to motion classification. PMID:28640883

  10. Design of high-resolution and multilevel reference pattern for improvement of both light utilization efficiency and signal-to-noise ratio in coaxial holographic data storage.

    Science.gov (United States)

    Nobukawa, Teruyoshi; Nomura, Takanori

    2014-06-10

    A high-resolution and multilevel designed reference pattern (DRP) is presented for improvement of both light utilization efficiency and the signal-to-noise ratio (SNR) of reconstructed images in coaxial holographic data storage. With a DRP, the desired Fourier power spectrum of a reference beam is obtained. Numerical and experimental results show that the DRP increases the SNR compared with that of a random phase mask (RPM). Moreover, the light utilization efficiency of the DRP is higher than that of a high-resolution RPM. In addition, the effect of the phase level and the pixel pitch of DRPs on the SNR and the light utilization efficiency are investigated.

  11. Detection of sub-threshold periodic signal by multiplicative and additive cross-correlated sine-Wiener noises in the FitzHugh-Nagumo neuron

    Science.gov (United States)

    Yao, Yuangen; Ma, Chengzhang; Wang, Canjun; Yi, Ming; Gui, Rong

    2018-02-01

    We study the effects of multiplicative and additive cross-correlated sine-Wiener (CCSW) noises on the performance of sub-threshold periodic signal detection in the FitzHugh-Nagumo (FHN) neuron by calculating Fourier coefficients Q for measuring synchronization between sub-threshold input signal and the response of system. CCSW noises-induced transitions of electrical activity in the FHN neuron model can be observed. Moreover, the performance of sub-threshold periodic signal detection is achieved at moderate noise strength, cross-correlation time and cross-correlation strength of CCSW noises, which indicate the occurrence of CCSW noises-induced stochastic resonance. Furthermore, the performance of sub-threshold signal detection is strongly sensitive to cross-correlation time of CCSW noises. Therefore, the performance can be effectively controlled by regulating cross-correlation time of CCSW noises. These results provide a possible mechanism for amplifying or detecting the sub-threshold signal in the nervous system.

  12. 2D stochastic-integral models for characterizing random grain noise in titanium alloys

    Energy Technology Data Exchange (ETDEWEB)

    Sabbagh, Harold A.; Murphy, R. Kim; Sabbagh, Elias H. [Victor Technologies, LLC, PO Box 7706, Bloomington, IN 47407-7706 (United States); Cherry, Matthew [University of Dayton Research Institute, 300 College Park Dr., Dayton, OH 45410 (United States); Pilchak, Adam; Knopp, Jeremy S.; Blodgett, Mark P. [Air Force Research Laboratory (AFRL/RXC), Wright Patterson AFB OH 45433-7817 (United States)

    2014-02-18

    We extend our previous work, in which we applied high-dimensional model representation (HDMR) and analysis of variance (ANOVA) concepts to the characterization of a metallic surface that has undergone a shot-peening treatment to reduce residual stresses, and has, therefore, become a random conductivity field. That example was treated as a onedimensional problem, because those were the only data available. In this study, we develop a more rigorous two-dimensional model for characterizing random, anisotropic grain noise in titanium alloys. Such a model is necessary if we are to accurately capture the 'clumping' of crystallites into long chains that appear during the processing of the metal into a finished product. The mathematical model starts with an application of the Karhunen-Loève (K-L) expansion for the random Euler angles, θ and φ, that characterize the orientation of each crystallite in the sample. The random orientation of each crystallite then defines the stochastic nature of the electrical conductivity tensor of the metal. We study two possible covariances, Gaussian and double-exponential, which are the kernel of the K-L integral equation, and find that the double-exponential appears to satisfy measurements more closely of the two. Results based on data from a Ti-7Al sample will be given, and further applications of HDMR and ANOVA will be discussed.

  13. Noise induced changes in the expression of p38/MAPK signaling proteins in the sensory epithelium of the inner ear

    OpenAIRE

    Jamesdaniel, Samson; Hu, Bohua; Kermany, Mohammad Habiby; Jiang, HaiYan; Ding, Dalian; Coling, Donald; Salvi, Richard

    2011-01-01

    Noise exposure is a major cause of hearing loss. Classical methods of studying protein involvement have provided a basis for understanding signaling pathways that mediate hearing loss and damage repair but do not lend themselves to studying large networks of proteins that are likely to increase or decrease during noise trauma. To address this issue, antibody microarrays were used to quantify the very early changes in protein expression in three distinct regions of the chinchilla cochlea 2 h a...

  14. Signal-to-noise ratio estimation on SEM images using cubic spline interpolation with Savitzky-Golay smoothing.

    Science.gov (United States)

    Sim, K S; Kiani, M A; Nia, M E; Tso, C P

    2014-01-01

    A new technique based on cubic spline interpolation with Savitzky-Golay noise reduction filtering is designed to estimate signal-to-noise ratio of scanning electron microscopy (SEM) images. This approach is found to present better result when compared with two existing techniques: nearest neighbourhood and first-order interpolation. When applied to evaluate the quality of SEM images, noise can be eliminated efficiently with optimal choice of scan rate from real-time SEM images, without generating corruption or increasing scanning time. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

  15. Analysis of biomedical signals by flicker-noise spectroscopy: Identification of photosensitive epilepsy using magnetoencephalograms

    Science.gov (United States)

    Timashev, S. F.; Polyakov, Yu. S.; Yulmetyev, R. M.; Demin, S. A.; Panischev, O. Yu.; Shimojo, S.; Bhattacharya, J.

    2009-04-01

    The flicker-noise spectroscopy (FNS) approach is used to determine the dynamic characteristics of neuromagnetic responses by analyzing the magnetoencephalographic (MEG) signals recorded as the response of a group of control human subjects and a patient with photosensitive epilepsy (PSE) to equiluminant flickering stimuli of different color combinations. Parameters characterizing the analyzed stochastic biomedical signals for different frequency bands are identified. It is shown that the classification of the parameters of analyzed MEG responses with respect to different frequency bands makes it possible to separate the contribution of the chaotic component from the overall complex dynamics of the signals. It is demonstrated that the chaotic component can be adequately described by the anomalous diffusion approximation in the case of control subjects. On the other hand, the chaotic component for the patient is characterized by a large number of high-frequency resonances. This implies that healthy organisms can suppress the perturbations brought about by the flickering stimuli and reorganize themselves. The organisms affected by photosensitive epilepsy no longer have this ability. This result also gives a way to simulate the separate stages of the brain cortex activity in vivo. The examples illustrating the use of the “FNS device” for identifying even the slightest individual differences in the activity of human brains using their responses to external standard stimuli show a unique possibility to develop the “individual medicine” of the future.

  16. Normal-hearing listener preferences of music as a function of signal-to-noise-ratio

    Science.gov (United States)

    Barrett, Jillian G.

    2005-04-01

    Optimal signal-to-noise ratios (SNR) for speech discrimination are well-known, well-documented phenomena. Discrimination preferences and functions have been studied for both normal-hearing and hard-of-hearing populations, and information from these studies has provided clearer indices on additional factors affecting speech discrimination ability and SNR preferences. This knowledge lends itself to improvements in hearing aids and amplification devices, telephones, television and radio transmissions, and a wide arena of recorded media such as movies and music. This investigation was designed to identify the preferred signal-to-background ratio (SBR) of normal-hearing listeners in a musical setting. The signal was the singer's voice, and music was considered the background. Subjects listened to an unfamiliar ballad with a female singer, and rated seven different SBR treatments. When listening to melodic motifs with linguistic content, results indicated subjects preferred SBRs similar to those in conventional speech discrimination applications. However, unlike traditional speech discrimination studies, subjects did not prefer increased levels of SBR. Additionally, subjects had a much larger acceptable range of SBR in melodic motifs where the singer's voice was not intended to communicate via linguistic means, but by the pseudo-paralinguistic means of vocal timbre and harmonic arrangements. Results indicate further studies investigating perception of singing are warranted.

  17. Development of output signal-to-noise ratio tester for microchannel plate and fluorescent screen component

    Science.gov (United States)

    Wu, Xinglin; Qiu, Yafeng; Zhou, Jin; Qian, Yunsheng

    The core components of Image intensifier is microchannel plate (MCP) and fluorescent screen component. The present paper deeply studies output signal-to-noise ratio (SNR) characteristics of MCP and fluorescent screen component. A tester system using to the evaluation of characteristics of the output SNR of MCP and fluorescent screen component, consists of a vacuum system, a surface electron source, mechanical mechanism components ,a high-voltage power supply system, a signal processing system, communication interfaces, a data acquisition and control system, computer system, and testing software. a hot cathode used as an electron source, generates a surface electron flow to provide the input signal. A photomultiplier tube is used to detection faceplate output brightness of the light spot. Then, the output SNR of MCP and fluorescent screen component is processed with a combination of methods of the hardware filter and digital filtering software. The output SNR of MCP and fluorescent screen component is measured under different conditions, and the results are analyzed. This test system Provide a technical to promote the image intensifier research, and experience to testing other parameters or in other areas of research.

  18. An Ultrahigh Frequency Partial Discharge Signal De-Noising Method Based on a Generalized S-Transform and Module Time-Frequency Matrix.

    Science.gov (United States)

    Liu, Yushun; Zhou, Wenjun; Li, Pengfei; Yang, Shuai; Tian, Yan

    2016-06-22

    Due to electromagnetic interference in power substations, the partial discharge (PD) signals detected by ultrahigh frequency (UHF) antenna sensors often contain various background noises, which may hamper high voltage apparatus fault diagnosis and localization. This paper proposes a novel de-noising method based on the generalized S-transform and module time-frequency matrix to suppress noise in UHF PD signals. The sub-matrix maximum module value method is employed to calculate the frequencies and amplitudes of periodic narrowband noise, and suppress noise through the reverse phase cancellation technique. In addition, a singular value decomposition de-noising method is employed to suppress Gaussian white noise in UHF PD signals. Effective singular values are selected by employing the fuzzy c-means clustering method to recover the PD signals. De-noising results of simulated and field detected UHF PD signals prove the feasibility of the proposed method. Compared with four conventional de-noising methods, the results show that the proposed method can suppress background noise in the UHF PD signal effectively, with higher signal-to-noise ratio and less waveform distortion.

  19. Modeling the effects of distortion, contrast, and signal-to-noise ratio on stereophotogrammetric range mapping

    Science.gov (United States)

    Sellar, R. Glenn; Deen, Robert G.; Huffman, William C.; Willson, Reginald G.

    2016-09-01

    Stereophotogrammetry typically employs a pair of cameras, or a single moving camera, to acquire pairs of images from different camera positions, in order to create a three dimensional `range map' of the area being observed. Applications of this technique for building three-dimensional shape models include aerial surveying, remote sensing, machine vision, and robotics. Factors that would be expected to affect the quality of the range maps include the projection function (distortion) of the lenses and the contrast (modulation) and signal-to-noise ratio (SNR) of the acquired image pairs. Basic models of the precision with which the range can be measured assume a pinhole-camera model of the geometry, i.e. that the lenses provide perspective projection with zero distortion. Very-wide-angle or `fisheye' lenses, however (for e.g. those used by robotic vehicles) typically exhibit projection functions that differ significantly from this assumption. To predict the stereophotogrammetric range precision for such applications, we extend the model to the case of an equidistant lens projection function suitable for a very-wide-angle lens. To predict the effects of contrast and SNR on range precision, we perform numerical simulations using stereo image pairs acquired by a stereo camera pair on NASA's Mars rover Curiosity. Contrast is degraded and noise is added to these data in a controlled fashion and the effects on the quality of the resulting range maps are assessed.

  20. Signal-to-noise based local decorrelation compensation for speckle interferometry applications.

    Science.gov (United States)

    Molimard, Jérôme; Cordero, Raul; Vautrin, Alain

    2008-07-01

    Speckle-based interferometric techniques allow assessing the whole-field deformation induced on a specimen due to the application of load. These high sensitivity optical techniques yield fringe images generated by subtracting speckle patterns captured while the specimen undergoes deformation. The quality of the fringes, and in turn the accuracy of the deformation measurements, strongly depends on the speckle correlation. Specimen rigid body motion leads to speckle decorrelation that, in general, cannot be effectively counteracted by applying a global translation to the involved speckle patterns. In this paper, we propose a recorrelation procedure based on the application of locally evaluated translations. The proposed procedure implies dividing the field into several regions, applying a local translation, and calculating, in every region, the signal-to-noise ratio (SNR). Since the latter is a correlation indicator (the noise increases with the decorrelation) we argue that the proper translation is that which maximizes the locally evaluated SNR. The search of the proper local translations is, of course, an interactive process that can be facilitated by using a SNR optimization algorithm. The performance of the proposed recorrelation procedure was tested on two examples. First, the SNR optimization algorithm was applied to fringe images obtained by subtracting simulated speckle patterns. Next, it was applied to fringe images obtained by using a shearography optical setup from a specimen subjected to mechanical deformation. Our results show that the proposed SNR optimization method can significantly improve the reliability of measurements performed by using speckle-based techniques.

  1. From noise to signal - a new approach to LHCb muon optimization

    CERN Document Server

    Kashchuk, A P

    2010-01-01

    One has to exploit the LHCb muon detector at the lowest possible gas gain and operational voltage in order to minimize the charge accumulated during 10 years of the LHCb experiment keeping the aging effects as low as possible. The detector lifetime prolongation 1.5-2 times can be achieved following the optimization of the LHCb muon system proposed in this note. An optimization of the LHCb muon system assumes: minimization of the electronics thresholds and detector gas gain, a choice of the working point near the knee of the efficiency plateau at high enough efficiency at stabilization the signal-to-noise ratio during long-term data taking runs by gas gain stabilization. An efficiency of each chamber tuned once by a time alignment remains constant at the constant gas gain. Cluster size, cross-talks, multi-hits become constant and minimal at constant and minimal gas gain. It is shown in the note how to reconstruct the noise distribution in each chamber already installed in the pit and to measure precisely offse...

  2. Autoregressive linear least square single scanning electron microscope image signal-to-noise ratio estimation.

    Science.gov (United States)

    Sim, Kok Swee; NorHisham, Syafiq

    2016-11-01

    A technique based on linear Least Squares Regression (LSR) model is applied to estimate signal-to-noise ratio (SNR) of scanning electron microscope (SEM) images. In order to test the accuracy of this technique on SNR estimation, a number of SEM images are initially corrupted with white noise. The autocorrelation function (ACF) of the original and the corrupted SEM images are formed to serve as the reference point to estimate the SNR value of the corrupted image. The LSR technique is then compared with the previous three existing techniques known as nearest neighbourhood, first-order interpolation, and the combination of both nearest neighborhood and first-order interpolation. The actual and the estimated SNR values of all these techniques are then calculated for comparison purpose. It is shown that the LSR technique is able to attain the highest accuracy compared to the other three existing techniques as the absolute difference between the actual and the estimated SNR value is relatively small. SCANNING 38:771-782, 2016. © 2016 Wiley Periodicals, Inc. © Wiley Periodicals, Inc.

  3. Analysis of Bidirectional Associative Memory using Self-consistent Signal to Noise Analysis and Statistical Neurodynamics

    Science.gov (United States)

    Shouno, Hayaru; Kido, Shoji; Okada, Masato

    2004-09-01

    Bidirectional associative memory (BAM) is a kind of an artificial neural network used to memorize and retrieve heterogeneous pattern pairs. Many efforts have been made to improve BAM from the the viewpoint of computer application, and few theoretical studies have been done. We investigated the theoretical characteristics of BAM using a framework of statistical-mechanical analysis. To investigate the equilibrium state of BAM, we applied self-consistent signal to noise analysis (SCSNA) and obtained a macroscopic parameter equations and relative capacity. Moreover, to investigate not only the equilibrium state but also the retrieval process of reaching the equilibrium state, we applied statistical neurodynamics to the update rule of BAM and obtained evolution equations for the macroscopic parameters. These evolution equations are consistent with the results of SCSNA in the equilibrium state.

  4. Shuttle bit rate synchronizer. [signal to noise ratios and error analysis

    Science.gov (United States)

    Huey, D. C.; Fultz, G. L.

    1974-01-01

    A shuttle bit rate synchronizer brassboard unit was designed, fabricated, and tested, which meets or exceeds the contractual specifications. The bit rate synchronizer operates at signal-to-noise ratios (in a bit rate bandwidth) down to -5 dB while exhibiting less than 0.6 dB bit error rate degradation. The mean acquisition time was measured to be less than 2 seconds. The synchronizer is designed around a digital data transition tracking loop whose phase and data detectors are integrate-and-dump filters matched to the Manchester encoded bits specified. It meets the reliability (no adjustments or tweaking) and versatility (multiple bit rates) of the shuttle S-band communication system through an implementation which is all digital after the initial stage of analog AGC and A/D conversion.

  5. Optimal Signal Filtration in Optical Sensors with Natural Squeezing of Vacuum Noises

    Science.gov (United States)

    Gusev, A. V.; Kulagin, V. V.

    1996-01-01

    The structure of optimal receiver is discussed for optical sensor measuring a small displacement of probe mass. Due to nonlinear interaction of the field and the mirror, a reflected wave is in squeezed state (natural squeezing), two quadratures of which are correlated and therefore one can increase signal-to-noise ratio and overcome the SQL. A measurement procedure realizing such correlation processing of two quadratures is clarified. The required combination of quadratures can be produced via mixing of pump field reflected from the mirror with local oscillator phase modulated field in duel-detector homodyne scheme. Such measurement procedure could be useful not only for resonant bar gravitational detector but for laser longbase interferometric detectors as well.

  6. Multi-images deconvolution improves signal-to-noise ratio on gated stimulated emission depletion microscopy

    Energy Technology Data Exchange (ETDEWEB)

    Castello, Marco [Nanobiophotonics, Nanophysics, Istituto Italiano di Tecnologia, Via Morego 30, Genoa, 16163 (Italy); DIBRIS, University of Genoa, Via Opera Pia 13, Genoa 16145 (Italy); Diaspro, Alberto [Nanobiophotonics, Nanophysics, Istituto Italiano di Tecnologia, Via Morego 30, Genoa, 16163 (Italy); Nikon Imaging Center, Via Morego 30, Genoa 16163 (Italy); Vicidomini, Giuseppe, E-mail: giuseppe.vicidomini@iit.it [Nanobiophotonics, Nanophysics, Istituto Italiano di Tecnologia, Via Morego 30, Genoa, 16163 (Italy)

    2014-12-08

    Time-gated detection, namely, only collecting the fluorescence photons after a time-delay from the excitation events, reduces complexity, cost, and illumination intensity of a stimulated emission depletion (STED) microscope. In the gated continuous-wave- (CW-) STED implementation, the spatial resolution improves with increased time-delay, but the signal-to-noise ratio (SNR) reduces. Thus, in sub-optimal conditions, such as a low photon-budget regime, the SNR reduction can cancel-out the expected gain in resolution. Here, we propose a method which does not discard photons, but instead collects all the photons in different time-gates and recombines them through a multi-image deconvolution. Our results, obtained on simulated and experimental data, show that the SNR of the restored image improves relative to the gated image, thereby improving the effective resolution.

  7. Estimation of Signal Coherence Threshold and Concealed Spectral Lines Applied to Detection of Turbofan Engine Combustion Noise

    Science.gov (United States)

    Miles, Jeffrey Hilton

    2010-01-01

    Combustion noise from turbofan engines has become important, as the noise from sources like the fan and jet are reduced. An aligned and un-aligned coherence technique has been developed to determine a threshold level for the coherence and thereby help to separate the coherent combustion noise source from other noise sources measured with far-field microphones. This method is compared with a statistics based coherence threshold estimation method. In addition, the un-aligned coherence procedure at the same time also reveals periodicities, spectral lines, and undamped sinusoids hidden by broadband turbofan engine noise. In calculating the coherence threshold using a statistical method, one may use either the number of independent records or a larger number corresponding to the number of overlapped records used to create the average. Using data from a turbofan engine and a simulation this paper shows that applying the Fisher z-transform to the un-aligned coherence can aid in making the proper selection of samples and produce a reasonable statistics based coherence threshold. Examples are presented showing that the underlying tonal and coherent broad band structure which is buried under random broadband noise and jet noise can be determined. The method also shows the possible presence of indirect combustion noise. Copyright 2011 Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America.

  8. Random resampling masks: a non-Bayesian one-shot strategy for noise reduction in digital holography.

    Science.gov (United States)

    Bianco, V; Paturzo, M; Memmolo, P; Finizio, A; Ferraro, P; Javidi, B

    2013-03-01

    Holographic imaging may become severely degraded by a mixture of speckle and incoherent additive noise. Bayesian approaches reduce the incoherent noise, but prior information is needed on the noise statistics. With no prior knowledge, one-shot reduction of noise is a highly desirable goal, as the recording process is simplified and made faster. Indeed, neither multiple acquisitions nor a complex setup are needed. So far, this result has been achieved at the cost of a deterministic resolution loss. Here we propose a fast non-Bayesian denoising method that avoids this trade-off by means of a numerical synthesis of a moving diffuser. In this way, only one single hologram is required as multiple uncorrelated reconstructions are provided by random complementary resampling masks. Experiments show a significant incoherent noise reduction, close to the theoretical improvement bound, resulting in image-contrast improvement. At the same time, we preserve the resolution of the unprocessed image.

  9. Attention-Dependent Modulation of Cortical Taste Circuits Revealed by Granger Causality with Signal-Dependent Noise

    Science.gov (United States)

    Luo, Qiang; Ge, Tian; Grabenhorst, Fabian; Feng, Jianfeng; Rolls, Edmund T.

    2013-01-01

    We show, for the first time, that in cortical areas, for example the insular, orbitofrontal, and lateral prefrontal cortex, there is signal-dependent noise in the fMRI blood-oxygen level dependent (BOLD) time series, with the variance of the noise increasing approximately linearly with the square of the signal. Classical Granger causal models are based on autoregressive models with time invariant covariance structure, and thus do not take this signal-dependent noise into account. To address this limitation, here we describe a Granger causal model with signal-dependent noise, and a novel, likelihood ratio test for causal inferences. We apply this approach to the data from an fMRI study to investigate the source of the top-down attentional control of taste intensity and taste pleasantness processing. The Granger causality with signal-dependent noise analysis reveals effects not identified by classical Granger causal analysis. In particular, there is a top-down effect from the posterior lateral prefrontal cortex to the insular taste cortex during attention to intensity but not to pleasantness, and there is a top-down effect from the anterior and posterior lateral prefrontal cortex to the orbitofrontal cortex during attention to pleasantness but not to intensity. In addition, there is stronger forward effective connectivity from the insular taste cortex to the orbitofrontal cortex during attention to pleasantness than during attention to intensity. These findings indicate the importance of explicitly modeling signal-dependent noise in functional neuroimaging, and reveal some of the processes involved in a biased activation theory of selective attention. PMID:24204221

  10. Attention-dependent modulation of cortical taste circuits revealed by Granger causality with signal-dependent noise.

    Directory of Open Access Journals (Sweden)

    Qiang Luo

    2013-10-01

    Full Text Available We show, for the first time, that in cortical areas, for example the insular, orbitofrontal, and lateral prefrontal cortex, there is signal-dependent noise in the fMRI blood-oxygen level dependent (BOLD time series, with the variance of the noise increasing approximately linearly with the square of the signal. Classical Granger causal models are based on autoregressive models with time invariant covariance structure, and thus do not take this signal-dependent noise into account. To address this limitation, here we describe a Granger causal model with signal-dependent noise, and a novel, likelihood ratio test for causal inferences. We apply this approach to the data from an fMRI study to investigate the source of the top-down attentional control of taste intensity and taste pleasantness processing. The Granger causality with signal-dependent noise analysis reveals effects not identified by classical Granger causal analysis. In particular, there is a top-down effect from the posterior lateral prefrontal cortex to the insular taste cortex during attention to intensity but not to pleasantness, and there is a top-down effect from the anterior and posterior lateral prefrontal cortex to the orbitofrontal cortex during attention to pleasantness but not to intensity. In addition, there is stronger forward effective connectivity from the insular taste cortex to the orbitofrontal cortex during attention to pleasantness than during attention to intensity. These findings indicate the importance of explicitly modeling signal-dependent noise in functional neuroimaging, and reveal some of the processes involved in a biased activation theory of selective attention.

  11. Maintaining acoustic communication at a cocktail party: heterospecific masking noise improves signal detection through frequency separation.

    Science.gov (United States)

    Siegert, M E; Römer, H; Hartbauer, M

    2013-12-15

    We examined acoustic masking in a chirping katydid species of the Mecopoda elongata complex due to interference with a sympatric Mecopoda species where males produce continuous trills at high amplitudes. Frequency spectra of both calling songs range from 1 to 80 kHz; the chirper species has more energy in a narrow frequency band at 2 kHz and above 40 kHz. Behaviourally, chirper males successfully phase-locked their chirps to playbacks of conspecific chirps under masking conditions at signal-to-noise ratios (SNRs) of -8 dB. After the 2 kHz band in the chirp had been equalised to the level in the masking trill, the breakdown of phase-locked synchrony occurred at a SNR of +7 dB. The remarkable receiver performance is partially mirrored in the selective response of a first-order auditory interneuron (TN1) to conspecific chirps under these masking conditions. However, the selective response is only maintained for a stimulus including the 2 kHz component, although this frequency band has no influence on the unmasked TN1 response. Remarkably, the addition of masking noise at 65 dB sound pressure level (SPL) to threshold response levels of TN1 for pure tones of 2 kHz enhanced the sensitivity of the response by 10 dB. Thus, the spectral dissimilarity between masker and signal at a rather low frequency appears to be of crucial importance for the ability of the chirping species to communicate under strong masking by the trilling species. We discuss the possible properties underlying the cellular/synaptic mechanisms of the 'novelty detector'.

  12. Nonlinearity and Phase Noise Tolerant 75-110 GHz Signal over Fiber System Using Phase Modulation Technique

    DEFF Research Database (Denmark)

    Deng, Lei; Pang, Xiaodan; Zhang, Xu

    2013-01-01

    We report on the transmission of 8 Gb/s 0 dB PAPR 16QAM-OFDM W-band (75-110 GHz) signals over 22.8km SMF without phase noise compensation by using a phase modulator in the optical heterodyne up-convertor.......We report on the transmission of 8 Gb/s 0 dB PAPR 16QAM-OFDM W-band (75-110 GHz) signals over 22.8km SMF without phase noise compensation by using a phase modulator in the optical heterodyne up-convertor....

  13. The relationship between BOLD signal and autonomic nervous system functions: implications for processing of "physiological noise".

    Science.gov (United States)

    Iacovella, Vittorio; Hasson, Uri

    2011-12-01

    Functional magnetic resonance imaging (fMRI) research has revealed not only important aspects of the neural basis of cognitive and perceptual functions, but also important information on the relation between high-level brain functions and physiology. One of the central outstanding questions, given the features of the blood oxygenation level-dependent (BOLD) signal, is whether and how autonomic nervous system (ANS) functions are related to changes in brain states as measured in the human brain. A straightforward way to address this question has been to acquire external measurements of ANS activity such as cardiac and respiratory data, and examine their relation to the BOLD signal. In this article, we describe two conceptual approaches to the treatment of ANS measures in the context of BOLD fMRI analysis. On the one hand, several research lines have treated ANS activity measures as noise, considering them as nothing but a confounding factor that reduces the power of fMRI analysis or its validity. Work in this line has developed powerful methods to remove ANS effects from the BOLD signal. On the other hand, a different line of work has made important progress in showing that ANS functions such as cardiac pulsation, heart rate variability and breathing rate could be considered as a theoretically meaningful component of the signal that is useful for understanding brain function. Work within this latter framework suggests that caution should be exercised when employing procedures to remove correlations between BOLD data and physiological measures. We discuss these two positions and the reasoning underlying them. Thereafter, we draw on the reviewed literature in presenting practical guidelines for treatment of ANS data, which are based on the premise that ANS data should be considered as theoretically meaningful information. This holds particularly when studying cortical systems involved in regulation, monitoring and/or generation of ANS activity, such as those involved

  14. Neutron Signal and Noise Separation of the {sup 6}Li-ZnS(Ag) scintillator (BC702) Using Flash ADC

    Energy Technology Data Exchange (ETDEWEB)

    Shin, S. G.; Kye, Y. U. [POSTECH, Pohang (Korea, Republic of); Cho, M. H.; Namkung, W. [Pohang Accelerator Laboratory, Pohang (Korea, Republic of); Kim, G. N. [Kyungpook National Univ., Daegu (Korea, Republic of); Lee, M. W. [Dongnam Inst. of radiological and Medical Science, Daejeon (Korea, Republic of)

    2013-10-15

    This study will apply to nuclear data experiments and improve the quality of nuclear data measured at PNF. We also briefly discuss the future plan to apply our research to different kinds of neutron detectors. The parameters to separate the neutron signals and noises of the {sup 6}Li.ZnS(Ag) scintillator are determined through the upper processes. Three kinds of noise are determined by the parameters as shown in figure.5. The signals at the green (pedestal), red (gamma flash), and blue (gamma flash with big signal area) region are subtracted from the total amount of the counted signals. These algorithms will be applied to next neutron TOF experiments. Two additional neutron detectors will be introduced for neutron TOF experiment. These will measure the neutron flux to get the normalization factor. We will also conduct signal and noise separation of these neutron detectors. Neutron total cross-sections have been measured by using the time-of-flight (TOF) method at Pohang Neutron Facility (PNF). A {sup 6}Li.ZnS(Ag) scintillator BC702 from Bicron (Newbury, OH) with a diameter of 127 mm and a thickness of 6.35 mm mounted on an EMI-93090 photomultiplier was used as a detector for the neutron TOF spectrum measurement. This detector is sensitive to thermal and epithermal neutrons and insensitive to gamma radiation. However, it is required to more accurately separate neutron signal and noise. In the present work, we studied neutron signal and noise separation of the BC702 scintillator to measure the accurate neutron TOF data.

  15. Eigenvalues of Random Matrices with Isotropic Gaussian Noise and the Design of Diffusion Tensor Imaging Experiments*

    Science.gov (United States)

    Gasbarra, Dario; Pajevic, Sinisa; Basser, Peter J.

    2017-01-01

    Tensor-valued and matrix-valued measurements of different physical properties are increasingly available in material sciences and medical imaging applications. The eigenvalues and eigenvectors of such multivariate data provide novel and unique information, but at the cost of requiring a more complex statistical analysis. In this work we derive the distributions of eigenvalues and eigenvectors in the special but important case of m×m symmetric random matrices, D, observed with isotropic matrix-variate Gaussian noise. The properties of these distributions depend strongly on the symmetries of the mean tensor/matrix, D̄. When D̄ has repeated eigenvalues, the eigenvalues of D are not asymptotically Gaussian, and repulsion is observed between the eigenvalues corresponding to the same D̄ eigenspaces. We apply these results to diffusion tensor imaging (DTI), with m = 3, addressing an important problem of detecting the symmetries of the diffusion tensor, and seeking an experimental design that could potentially yield an isotropic Gaussian distribution. In the 3-dimensional case, when the mean tensor is spherically symmetric and the noise is Gaussian and isotropic, the asymptotic distribution of the first three eigenvalue central moment statistics is simple and can be used to test for isotropy. In order to apply such tests, we use quadrature rules of order t ≥ 4 with constant weights on the unit sphere to design a DTI-experiment with the property that isotropy of the underlying true tensor implies isotropy of the Fisher information. We also explain the potential implications of the methods using simulated DTI data with a Rician noise model. PMID:28989561

  16. Noise reduction in Lidar signal using correlation-based EMD combined with soft thresholding and roughness penalty

    Science.gov (United States)

    Chang, Jianhua; Zhu, Lingyan; Li, Hongxu; Xu, Fan; Liu, Binggang; Yang, Zhenbo

    2018-01-01

    Empirical mode decomposition (EMD) is widely used to analyze the non-linear and non-stationary signals for noise reduction. In this study, a novel EMD-based denoising method, referred to as EMD with soft thresholding and roughness penalty (EMD-STRP), is proposed for the Lidar signal denoising. With the proposed method, the relevant and irrelevant intrinsic mode functions are first distinguished via a correlation coefficient. Then, the soft thresholding technique is applied to the irrelevant modes, and the roughness penalty technique is applied to the relevant modes to extract as much information as possible. The effectiveness of the proposed method was evaluated using three typical signals contaminated by white Gaussian noise. The denoising performance was then compared to the denoising capabilities of other techniques, such as correlation-based EMD partial reconstruction, correlation-based EMD hard thresholding, and wavelet transform. The use of EMD-STRP on the measured Lidar signal resulted in the noise being efficiently suppressed, with an improved signal to noise ratio of 22.25 dB and an extended detection range of 11 km.

  17. Investigation of signal thresholding to reduce the effects of instrument noise of an EMCCD based micro-CT system.

    Science.gov (United States)

    Podgorsak, Alexander R; Krishnakumar, Sumukh Bysani; Nagesh, Sv Setlur; Bednarek, Daniel R; Rudin, Stephen; Ionita, Ciprian N

    2016-02-27

    This project investigated the signal thresholding effectiveness at reducing the instrument noise of an electron multiplying charged coupled device (EMCCD) based micro-CT system at low x-ray exposure levels. Scans of a mouse spine and an iodine phantom were taken using an EMCCD detector coupled with a micro-CT system. An iodine filter of 4 mg/cm2 area density was placed in the beam. The output signal was thresholded using some multiple of the inherent background noise. For each threshold, 100, 200, and 300 frames were summed for each projection to evaluate the effect on the reconstructed image. The projection images from the scans were compared using line profiles and their SNR. Our results indicate that, as the threshold was increased, the line profiles of the projection images showed less statistical variation, but also lower signal levels, so that the SNR of the projection images decreased as the threshold increased. When the line profile of a projection image obtained using a signal threshold is compared with one obtained using energy integrating mode, the profile obtained using thresholding had less variation than that obtained using energy integration, which indicates less instrument noise. The SNR at the edges of the scan object is higher in the thresholded images when compared with the energy integrated projection images. We conclude that thresholding the output signal from an EMCCD detector at low x-ray exposure levels is an effective method to reduce the instrument noise of an EMCCD detector.

  18. Errors due to random noise in velocity measurement using incoherent-scatter radar

    Directory of Open Access Journals (Sweden)

    P. J. S. Williams

    Full Text Available The random-noise errors involved in measuring the Doppler shift of an 'incoherent-scatter' spectrum are predicted theoretically for all values of Te/Ti from 1.0 to 3.0. After correction has been made for the effects of convolution during transmission and reception and the additional errors introduced by subtracting the average of the background gates, the rms errors can be expressed by a simple semi-empirical formula. The observed errors are determined from a comparison of simultaneous EISCAT measurements using an identical pulse code on several adjacent frequencies. The plot of observed versus predicted error has a slope of 0.991 and a correlation coefficient of 99.3%. The prediction also agrees well with the mean of the error distribution reported by the standard EISCAT analysis programme.

  19. Errors due to random noise in velocity measurement using incoherent-scatter radar

    Directory of Open Access Journals (Sweden)

    P. J. S. Williams

    1996-12-01

    Full Text Available The random-noise errors involved in measuring the Doppler shift of an 'incoherent-scatter' spectrum are predicted theoretically for all values of Te/Ti from 1.0 to 3.0. After correction has been made for the effects of convolution during transmission and reception and the additional errors introduced by subtracting the average of the background gates, the rms errors can be expressed by a simple semi-empirical formula. The observed errors are determined from a comparison of simultaneous EISCAT measurements using an identical pulse code on several adjacent frequencies. The plot of observed versus predicted error has a slope of 0.991 and a correlation coefficient of 99.3%. The prediction also agrees well with the mean of the error distribution reported by the standard EISCAT analysis programme.

  20. Signal-to-noise ratio comparison of encoding methods for hyperpolarized noble gas MRI

    Science.gov (United States)

    Zhao, L.; Venkatesh, A. K.; Albert, M. S.; Panych, L. P.

    2001-01-01

    Some non-Fourier encoding methods such as wavelet and direct encoding use spatially localized bases. The spatial localization feature of these methods enables optimized encoding for improved spatial and temporal resolution during dynamically adaptive MR imaging. These spatially localized bases, however, have inherently reduced image signal-to-noise ratio compared with Fourier or Hadamad encoding for proton imaging. Hyperpolarized noble gases, on the other hand, have quite different MR properties compared to proton, primarily the nonrenewability of the signal. It could be expected, therefore, that the characteristics of image SNR with respect to encoding method will also be very different from hyperpolarized noble gas MRI compared to proton MRI. In this article, hyperpolarized noble gas image SNRs of different encoding methods are compared theoretically using a matrix description of the encoding process. It is shown that image SNR for hyperpolarized noble gas imaging is maximized for any orthonormal encoding method. Methods are then proposed for designing RF pulses to achieve normalized encoding profiles using Fourier, Hadamard, wavelet, and direct encoding methods for hyperpolarized noble gases. Theoretical results are confirmed with hyperpolarized noble gas MRI experiments. Copyright 2001 Academic Press.

  1. Machine Learning on Signal-to-Noise Ratios Improves Peptide Array Design in SAMDI Mass Spectrometry.

    Science.gov (United States)

    Xue, Albert Y; Szymczak, Lindsey C; Mrksich, Milan; Bagheri, Neda

    2017-09-05

    Emerging peptide array technologies are able to profile molecular activities within cell lysates. However, the structural diversity of peptides leads to inherent differences in peptide signal-to-noise ratios (S/N). These complex effects can lead to potentially unrepresentative signal intensities and can bias subsequent analyses. Within mass spectrometry-based peptide technologies, the relation between a peptide's amino acid sequence and S/N remains largely nonquantitative. To address this challenge, we present a method to quantify and analyze mass spectrometry S/N of two peptide arrays, and we use this analysis to portray quality of data and to design future arrays for SAMDI mass spectrometry. Our study demonstrates that S/N varies significantly across peptides within peptide arrays, and variation in S/N is attributable to differences of single amino acids. We apply supervised machine learning to predict peptide S/N based on amino acid sequence, and identify specific physical properties of the amino acids that govern variation of this metric. We find low peptide-S/N concordance between arrays, demonstrating that different arrays require individual characterization and that global peptide-S/N relationships are difficult to identify. However, with proper peptide sampling, this study illustrates how machine learning can accurately predict the S/N of a peptide in an array, allowing for the efficient design of arrays through selection of high S/N peptides.

  2. The signal-to-noise ratio and a hidden symmetry of Hall plates

    Science.gov (United States)

    Ausserlechner, Udo

    2017-09-01

    In a Hall plate with finite size and contacts the Hall output voltage is given by the product of sheet resistance, input current, Hall mobility, magnetic flux density, and Hall geometry factor GH . GH ∈ [ 0, 1 ] accounts for the loss in signal due to the contacts. At weak magnetic field GH →GH0 is a function of geometrical parameters only, which makes it the crucial point for layout optimization. We show how to express GH0 alternatively as a function of electrical parameters only, namely of input and output resistances over sheet resistance. This allows for an analytical optimization of signal-to-noise-ratio (SNR) without getting lost in the multitude of geometrical representations of equivalent Hall plates. In the course of this investigation we notice a hidden symmetry property of GH , which we prove rigorously in the limit of small magnetic fields. The physical meaning of this symmetry in the case of Hall plates with equal input and output resistances is also explained.

  3. Lifting Transit Signals from the Kepler Noise Floor. I. Discovery of a Warm Neptune

    Science.gov (United States)

    Kunimoto, Michelle; Matthews, Jaymie M.; Rowe, Jason F.; Hoffman, Kelsey

    2018-01-01

    Light curves from the 4-year Kepler exoplanet hunting mission have been searched for transits by NASA’s Kepler team and others, but there are still important discoveries to be made. We have searched the light curves of 400 Kepler Objects of Interest (KOIs) to find transit signals down to signal-to-noise ratio (S/N) ∼ 6, which is under the limit of S/N ∼ 7.1 that has been commonly adopted as a strict threshold to distinguish between a transit candidate and false alarm. We detect four new and convincing planet candidates ranging in radius from near-Mercury-size to slightly larger than Neptune. We highlight the discovery of KOI-408.05 (period = 637 days; radius = 4.9 R ⊕ incident flux = 0.6 S ⊕), a planet candidate within its host star’s Habitable Zone. We dub this planet a “warm Neptune,” a likely volatile-rich world that deserves closer inspection. KOI-408.05 joins 21 other confirmed and candidate planets in the current Kepler sample with semimajor axes a > 1.4 au. These discoveries are significant as a demonstration that the S/N threshold for detection used by the Kepler project is open to debate.

  4. Supplementary Appendix for: Constrained Perturbation Regularization Approach for Signal Estimation Using Random Matrix Theory

    KAUST Repository

    Suliman, Mohamed

    2016-01-01

    In this supplementary appendix we provide proofs and additional simulation results that complement the paper (constrained perturbation regularization approach for signal estimation using random matrix theory).

  5. Noise induced changes in the expression of p38/MAPK signaling proteins in the sensory epithelium of the inner ear.

    Science.gov (United States)

    Jamesdaniel, Samson; Hu, Bohua; Kermany, Mohammad Habiby; Jiang, Haiyan; Ding, Dalian; Coling, Donald; Salvi, Richard

    2011-12-21

    Noise exposure is a major cause of hearing loss. Classical methods of studying protein involvement have provided a basis for understanding signaling pathways that mediate hearing loss and damage repair but do not lend themselves to studying large networks of proteins that are likely to increase or decrease during noise trauma. To address this issue, antibody microarrays were used to quantify the very early changes in protein expression in three distinct regions of the chinchilla cochlea 2h after exposure to a 0.5-8 kHz band of noise for 2h at 112 dB SPL. The noise exposure caused significant functional impairment 2h post-exposure which only partially recovered. Distortion product otoacoustic emissions were abolished 2h after the exposure, but at 4 weeks post-exposure, otoacoustic emissions were present, but still greatly depressed. Cochleograms obtained 4 weeks post-exposure demonstrated significant loss of outer hair cells in the basal 60% of the cochlea corresponding to frequencies in the noise spectrum. A comparative analysis of the very early (2h post-exposure) noise-induced proteomic changes indicated that the sensory epithelium, lateral wall and modiolus differ in their biological response to noise. Bioinformatic analysis of the cochlear protein profile using "The Database for Annotation, Visualization and Integrated Discovery 2008" (DAVID - http://david.abcc. ncifcrf.gov) revealed the initiation of the cell death process in sensory epithelium and modiolus. An increase in Fas and phosphorylation of FAK and p38/MAPK in the sensory epithelium suggest that noise-induced stress signals at the cell membrane are transmitted to the nucleus by Fas and focal adhesion signaling through the p38/MAPK signaling pathway. Up-regulation of downstream nuclear proteins E2F3 and WSTF in immunoblots and microarrays along with their immunolocalization in the outer hair cells supported the pivotal role of p38/MAPK signaling in the mechanism underlying noise-induced hearing loss

  6. Characteristics of the Energy-Like Detector of a Gaussian Signal Against the Background of Likhter Noise

    Science.gov (United States)

    Kostylev, V. I.; Gres', I. P.

    2017-10-01

    We propose an energy-like detector of signals and analyze its efficiency by an example of detecting a Gaussian signal with zero mathematical expectation and uncorrelated readouts against the background of Likhter noise with independent readouts. Analytical expressions for the probability of correct detection are obtained and statistical simulation is performed. Using particular examples, we show that the energy-like detection characteristics can be much closer to the optimal ones than those of the energy detection.

  7. Vibroacoustic disease: biological effects of infrasound and low-frequency noise explained by mechanotransduction cellular signalling.

    Science.gov (United States)

    Alves-Pereira, Mariana; Castelo Branco, Nuno A A

    2007-01-01

    At present, infrasound (0-20 Hz) and low-frequency noise (20-500 Hz) (ILFN, 0-500 Hz) are agents of disease that go unchecked. Vibroacoustic disease (VAD) is a whole-body pathology that develops in individuals excessively exposed to ILFN. VAD has been diagnosed within several professional groups employed within the aeronautical industry, and in other heavy industries. However, given the ubiquitous nature of ILFN and the absence of legislation concerning ILFN, VAD is increasingly being diagnosed among members of the general population, including children. VAD is associated with the abnormal growth of extra-cellular matrices (collagen and elastin), in the absence of an inflammatory process. In VAD, the end-product of collagen and elastin growth is reinforcement of structural integrity. This is seen in blood vessels, cardiac structures, trachea, lung, and kidney of both VAD patients and ILFN-exposed animals. VAD is, essentially, a mechanotransduction disease. Inter- and intra-cellular communication is achieved through both biochemical and mechanotranduction signalling. When the structural components of tissue are altered, as is seen in ILFN-exposed specimens, the mechanically mediated signalling is, at best, impaired. Common medical diagnostic tests, such as EKG, EEG, as well as many blood chemistry analyses, are based on the mal-function of biochemical signalling processes. VAD patients typically present normal values for these tests. However, when echocardiography, brain MRI or histological studies are performed, where structural changes can be identified, all consistently show significant changes in VAD patients and ILFN-exposed animals. Frequency-specific effects are not yet known, valid dose-responses have been difficult to identify, and large-scale epidemiological studies are still lacking.

  8. On nanopore DNA sequencing by signal and noise analysis of ionic current.

    Science.gov (United States)

    Wen, Chenyu; Zeng, Shuangshuang; Zhang, Zhen; Hjort, Klas; Scheicher, Ralph; Zhang, Shi-Li

    2016-05-27

    DNA sequencing, i.e., the process of determining the succession of nucleotides on a DNA strand, has become a standard aid in biomedical research and is expected to revolutionize medicine. With the capability of handling single DNA molecules, nanopore technology holds high promises to become speedier in sequencing at lower cost than what are achievable with the commercially available optics- or semiconductor-based massively parallelized technologies. Despite tremendous progress made with biological and solid-state nanopores, high error rates and large uncertainties persist with the sequencing results. Here, we employ a nano-disk model to quantitatively analyze the sequencing process by examining the variations of ionic current when a DNA strand translocates a nanopore. Our focus is placed on signal-boosting and noise-suppressing strategies in order to attain the single-nucleotide resolution. Apart from decreasing pore diameter and thickness, it is crucial to also reduce the translocation speed and facilitate a stepwise translocation. Our best-case scenario analysis points to severe challenges with employing plain nanopore technology, i.e., without recourse to any signal amplification strategy, in achieving sequencing with the desired single-nucleotide resolution. A conceptual approach based on strand synthesis in the nanopore of the translocating DNA from single-stranded to double-stranded is shown to yield a 10-fold signal amplification. Although it involves no advanced physics and is very simple in mathematics, this simple model captures the essence of nanopore sequencing and is useful in guiding the design and operation of nanopore sequencing.

  9. Noise-assisted multivariate empirical mode decomposition for multichannel EMG signals.

    Science.gov (United States)

    Zhang, Yi; Xu, Peng; Li, Peiyang; Duan, Keyi; Wen, Yuexin; Yang, Qin; Zhang, Tao; Yao, Dezhong

    2017-08-23

    Ensemble Empirical Mode Decomposition (EEMD) has been popularised for single-channel Electromyography (EMG) signal processing as it can effectively extract the temporal information of the EMG time series. However, few papers examine the temporal and spatial characteristics across multiple muscle groups in relation to multichannel EMG signals. The experimental data was obtained from the Center for Machine Learning and Intelligent Systems, University of California Irvine (UCI). The data was donated by the Nueva Granada Military University and the Technopark node Manizales in Colombia. The databases of 11 male subjects from the healthy group were taken into the study. The subjects undergo three exercise programs, leg extension from a sitting position (sitting), flexion of the leg up (standing), and gait (walking), while four electrodes were placed on biceps femoris (BF), vastus medialis (VM), rectus femoris (RF), and semitendinosus (ST). Based on the experimental data, a comparative study is provided by assessing the Empirical Mode Decomposition (EMD)-based approaches, EEMD, Multivariate EMD (MEMD), and Noise-Assisted MEMD (NA-MEMD). The outcomes from these approaches are then quantitatively estimated on the basis of three criterions, the number of Intrinsic Mode Functions (IMFs), mode-alignment and mode-mixing. Both MEMD and NA-MEMD methods (except EEMD) can guarantee equal numbers of IMFs. For mode-alignment and mode-mixing, NA-MEMD is optimal compared with MEMD and EEMD, and MEMD is merely better than EEMD. This study proposes the NA-MEMD approach for multichannel EMG signal processing. This finding implies that NA-MEMD is effective for simultaneously analysing IMFs based frequency bands. It has a vital clinical implication in exploring the neuromuscular patterns that enable the multiple muscle groups to coordinate while performing the functional activities of daily living.

  10. Effects of the physiological parameters on the signal-to-noise ratio of single myoelectric channel

    Directory of Open Access Journals (Sweden)

    Zhang YT

    2007-08-01

    Full Text Available Abstract Background An important measure of the performance of a myoelectric (ME control system for powered artificial limbs is the signal-to-noise ratio (SNR at the output of ME channel. However, few studies illustrated the neuron-muscular interactive effects on the SNR at ME control channel output. In order to obtain a comprehensive understanding on the relationship between the physiology of individual motor unit and the ME control performance, this study investigates the effects of physiological factors on the SNR of single ME channel by an analytical and simulation approach, where the SNR is defined as the ratio of the mean squared value estimation at the channel output and the variance of the estimation. Methods Mathematical models are formulated based on three fundamental elements: a motoneuron firing mechanism, motor unit action potential (MUAP module, and signal processor. Myoelectric signals of a motor unit are synthesized with different physiological parameters, and the corresponding SNR of single ME channel is numerically calculated. Effects of physiological multi factors on the SNR are investigated, including properties of the motoneuron, MUAP waveform, recruitment order, and firing pattern, etc. Results The results of the mathematical model, supported by simulation, indicate that the SNR of a single ME channel is associated with the voluntary contraction level. We showed that a model-based approach can provide insight into the key factors and bioprocess in ME control. The results of this modelling work can be potentially used in the improvement of ME control performance and for the training of amputees with powered prostheses. Conclusion The SNR of single ME channel is a force, neuronal and muscular property dependent parameter. The theoretical model provides possible guidance to enhance the SNR of ME channel by controlling physiological variables or conscious contraction level.

  11. Gain and noise properties of small-signal erbium-doped fiber amplifiers pumped in the 980-nm band

    DEFF Research Database (Denmark)

    Pedersen, B.; Chirravuri, J.; Miniscalco, W. J.

    1992-01-01

    The authors have experimentally and theoretically investigated the effects of detuning the pump wavelength on the gain and noise properties of small-signal, erbium-doped fiber amplifiers codirectionally pumped in the 980-nm band. While the pump wavelength can be varied over a wide range with litt...... impact on the gain, a noise penalty is incurred. For amplifiers saturated by amplified spontaneous emission, it is possible to increase the gain by detuning the pump wavelength......The authors have experimentally and theoretically investigated the effects of detuning the pump wavelength on the gain and noise properties of small-signal, erbium-doped fiber amplifiers codirectionally pumped in the 980-nm band. While the pump wavelength can be varied over a wide range with little...

  12. Evaluation of the effectiveness of Gaussian filtering in distinguishing punctate synaptic signals from background noise during image analysis.

    Science.gov (United States)

    Iwabuchi, Sadahiro; Kakazu, Yasuhiro; Koh, Jin-Young; Harata, N Charles

    2014-02-15

    Images in biomedical imaging research are often affected by non-specific background noise. This poses a serious problem when the noise overlaps with specific signals to be quantified, e.g. for their number and intensity. A simple and effective means of removing background noise is to prepare a filtered image that closely reflects background noise and to subtract it from the original unfiltered image. This approach is in common use, but its effectiveness in identifying and quantifying synaptic puncta has not been characterized in detail. We report on our assessment of the effectiveness of isolating punctate signals from diffusely distributed background noise using one variant of this approach, "Difference of Gaussian(s) (DoG)" which is based on a Gaussian filter. We evaluated immunocytochemically stained, cultured mouse hippocampal neurons as an example, and provided the rationale for choosing specific parameter values for individual steps in detecting glutamatergic nerve terminals. The intensity and width of the detected puncta were proportional to those obtained by manual fitting of two-dimensional Gaussian functions to the local information in the original image. DoG was compared with the rolling-ball method, using biological data and numerical simulations. Both methods removed background noise, but differed slightly with respect to their efficiency in discriminating neighboring peaks, as well as their susceptibility to high-frequency noise and variability in object size. DoG will be useful in detecting punctate signals, once its characteristics are examined quantitatively by experimenters. Copyright © 2013 Elsevier B.V. All rights reserved.

  13. Parallel Array Bistable Stochastic Resonance System with Independent Input and Its Signal-to-Noise Ratio Improvement

    Directory of Open Access Journals (Sweden)

    Wei Li

    2014-01-01

    with independent components and averaged output; second, we give a deduction of the output signal-to-noise ratio (SNR for this system to show the performance. Our examples show the enhancement of the system and how different parameters influence the performance of the proposed parallel array.

  14. EEG derivations providing auditory steady-state responses with high signal-to-noise ratios in infants.

    NARCIS (Netherlands)

    Reijden, C.S. van der; Mens, L.H.M.; Snik, A.F.M.

    2005-01-01

    OBJECTIVE: To identify EEG derivations that yield high signal-to-noise ratios (SNRs) of the auditory steady-state response (ASSR) in infants aged 0 to 5 months. DESIGN: The ASSR was recorded simultaneously from 10 EEG derivations in a monopolar montage in 20 sleeping infants. Stimuli were tones of

  15. Comparing signal to noise ratios of amplitude modulation following responses from four EEG derivations in awake normally hearing adults.

    NARCIS (Netherlands)

    Reijden, C.S. van der; Mens, L.H.M.; Snik, A.F.M.

    2001-01-01

    Amplitude modulation following responses (AMFR) or steady-state evoked potentials (SSEPs) can be used for the objective and frequency-specific estimation of hearing thresholds in awake and sleeping subjects. To be useful as a clinical tool, a high signal to noise ratio (SNR) is required for a

  16. Signal-to-noise ratios of the auditory steady-state response from fifty-five EEG derivations in adults.

    NARCIS (Netherlands)

    Reijden, C.S. van der; Mens, L.H.M.; Snik, A.F.M.

    2004-01-01

    The Auditory Steady-State Response (ASSR) was recorded in 20 awake adults with normal hearing on ten EEG channels simultaneously to find derivations with the best signal-to-noise ratios (SNRs). Stimuli were 20% frequency modulated tones of 0.5 and 2 kHz at 20 dB SL, 100% amplitude modulated at 90 or

  17. Theoretical and experimental signal-to-noise ratio assessment in new direction sensing continuous-wave Doppler lidar

    DEFF Research Database (Denmark)

    Pedersen, Anders Tegtmeier; Foroughi Abari, Farzad; Mann, Jakob

    2014-01-01

    A new direction sensing continuous-wave Doppler lidar based on an image-reject homodyne receiver has recently been demonstrated at DTU Wind Energy, Technical University of Denmark. In this contribution we analyse the signal-to-noise ratio resulting from two different data processing methods both...

  18. Active elimination of radio frequency interference for improved signal-to-noise ratio for in-situ NMR experiments in strong magnetic field gradients.

    Science.gov (United States)

    Ibrahim, M; Pardi, C I; Brown, T W C; McDonald, P J

    2018-02-01

    Improvement in the signal-to-noise ratio of Nuclear Magnetic Resonance (NMR) systems may be achieved either by increasing the signal amplitude or by decreasing the noise. The noise has multiple origins - not all of which are strictly "noise": incoherent thermal noise originating in the probe and pre-amplifiers, probe ring down or acoustic noise and coherent externally broadcast radio frequency transmissions. The last cannot always be shielded in open access experiments. In this paper, we show that pulsed, low radio-frequency data communications are a significant source of broadcast interference. We explore two signal processing methods of de-noising short T 2 ∗ NMR experiments corrupted by these communications: Linear Predictive Coding (LPC) and the Discrete Wavelet Transform (DWT). Results are shown for numerical simulations and experiments conducted under controlled conditions with pseudo radio frequency interference. We show that both the LPC and DWT methods have merit. Copyright © 2018 Elsevier Inc. All rights reserved.

  19. Spatial resolution of electrical source localization depends on inter-electrode spacing and signal-to-noise ratio

    Directory of Open Access Journals (Sweden)

    Nguyen Martin

    2017-09-01

    Full Text Available Extracellular recordings of electrical neuronal sources with non-planar multichannel microelectrodes promise a high spatio-temporal resolution. We have developed signal-based algorithms, simulations and models to inversely estimate neuronal source positions and electrical properties by using multi-sensor recorded extracellular action potentials (EAP. Here, we analyse the dependence of electrode configurations on the position estimation by simulations. Estimations were simulated for various inter-electrode spacings, electrode-source distances and signal-to-noise ratios. The results show that inverse estimation depends on the electrode size or rather on the inter-electrode spacing. We find, as a rule, the larger the spacing, the larger the eligible source location area, but estimation quality of sources which are in the proximity of an electrode contact decreases. In addition, noise worsen the estimation and decreases the assessable distance between source and electrode. Thus, multichannel micro-electrodes should be selected towards signal and spatial sensitivity requirements.

  20. An all digital phase locked loop for synchronization of a sinusoidal signal embedded in white Gaussian noise

    Science.gov (United States)

    Reddy, C. P.; Gupta, S. C.

    1973-01-01

    An all digital phase locked loop which tracks the phase of the incoming sinusoidal signal once per carrier cycle is proposed. The different elements and their functions and the phase lock operation are explained in detail. The nonlinear difference equations which govern the operation of the digital loop when the incoming signal is embedded in white Gaussian noise are derived, and a suitable model is specified. The performance of the digital loop is considered for the synchronization of a sinusoidal signal. For this, the noise term is suitably modelled which allows specification of the output probabilities for the two level quantizer in the loop at any given phase error. The loop filter considered increases the probability of proper phase correction. The phase error states in modulo two-pi forms a finite state Markov chain which enables the calculation of steady state probabilities, RMS phase error, transient response and mean time for cycle skipping.

  1. Performance of signal-to-noise ratio estimation for scanning electron microscope using autocorrelation Levinson-Durbin recursion model.

    Science.gov (United States)

    Sim, K S; Lim, M S; Yeap, Z X

    2016-07-01

    A new technique to quantify signal-to-noise ratio (SNR) value of the scanning electron microscope (SEM) images is proposed. This technique is known as autocorrelation Levinson-Durbin recursion (ACLDR) model. To test the performance of this technique, the SEM image is corrupted with noise. The autocorrelation function of the original image and the noisy image are formed. The signal spectrum based on the autocorrelation function of image is formed. ACLDR is then used as an SNR estimator to quantify the signal spectrum of noisy image. The SNR values of the original image and the quantified image are calculated. The ACLDR is then compared with the three existing techniques, which are nearest neighbourhood, first-order linear interpolation and nearest neighbourhood combined with first-order linear interpolation. It is shown that ACLDR model is able to achieve higher accuracy in SNR estimation. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

  2. Optimal signal constellation design for ultra-high-speed optical transport in the presence of nonlinear phase noise.

    Science.gov (United States)

    Liu, Tao; Djordjevic, Ivan B

    2014-12-29

    In this paper, we first describe an optimal signal constellation design algorithm suitable for the coherent optical channels dominated by the linear phase noise. Then, we modify this algorithm to be suitable for the nonlinear phase noise dominated channels. In optimization procedure, the proposed algorithm uses the cumulative log-likelihood function instead of the Euclidian distance. Further, an LDPC coded modulation scheme is proposed to be used in combination with signal constellations obtained by proposed algorithm. Monte Carlo simulations indicate that the LDPC-coded modulation schemes employing the new constellation sets, obtained by our new signal constellation design algorithm, outperform corresponding QAM constellations significantly in terms of transmission distance and have better nonlinearity tolerance.

  3. Design of Flow Systems for Improved Networking and Reduced Noise in Biomolecular Signal Processing in Biocomputing and Biosensing Applications

    Directory of Open Access Journals (Sweden)

    Arjun Verma

    2016-07-01

    Full Text Available We consider flow systems that have been utilized for small-scale biomolecular computing and digital signal processing in binary-operating biosensors. Signal measurement is optimized by designing a flow-reversal cuvette and analyzing the experimental data to theoretically extract the pulse shape, as well as reveal the level of noise it possesses. Noise reduction is then carried out numerically. We conclude that this can be accomplished physically via the addition of properly designed well-mixing flow-reversal cell(s as an integral part of the flow system. This approach should enable improved networking capabilities and potentially not only digital but analog signal-processing in such systems. Possible applications in complex biocomputing networks and various sense-and-act systems are discussed.

  4. Design of Flow Systems for Improved Networking and Reduced Noise in Biomolecular Signal Processing in Biocomputing and Biosensing Applications.

    Science.gov (United States)

    Verma, Arjun; Fratto, Brian E; Privman, Vladimir; Katz, Evgeny

    2016-07-05

    We consider flow systems that have been utilized for small-scale biomolecular computing and digital signal processing in binary-operating biosensors. Signal measurement is optimized by designing a flow-reversal cuvette and analyzing the experimental data to theoretically extract the pulse shape, as well as reveal the level of noise it possesses. Noise reduction is then carried out numerically. We conclude that this can be accomplished physically via the addition of properly designed well-mixing flow-reversal cell(s) as an integral part of the flow system. This approach should enable improved networking capabilities and potentially not only digital but analog signal-processing in such systems. Possible applications in complex biocomputing networks and various sense-and-act systems are discussed.

  5. Signal-to-Noise Enhancement of a Nanospring Redox-Based Sensor by Lock-in Amplification

    Directory of Open Access Journals (Sweden)

    Pavel V. Bakharev

    2015-06-01

    Full Text Available A significant improvement of the response characteristics of a redox chemical gas sensor (chemiresistor constructed with a single ZnO coated silica nanospring has been achieved with the technique of lock-in signal amplification. The comparison of DC and analog lock-in amplifier (LIA AC measurements of the electrical sensor response to toluene vapor, at the ppm level, has been conducted. When operated in the DC detection mode, the sensor exhibits a relatively high sensitivity to the analyte vapor, as well as a low detection limit at the 10 ppm level. However, at 10 ppm the signal-to-noise ratio is 5 dB, which is less than desirable. When operated in the analog LIA mode, the signal-to-noise ratio at 10 ppm increases by 30 dB and extends the detection limit to the ppb range.

  6. Signal to Noise Ratio Maximization in Quiet Zone Acquisitions for Range Assessment at Sub-millimeter Wavelengths

    Directory of Open Access Journals (Sweden)

    A. Muñoz-Acevedo

    2012-06-01

    Full Text Available This paper proposes a quiet zone probing approach which deals with low dynamic range quiet zone acquisitions. Lack of dynamic range is a feature of millimeter and sub-millimeter wavelength technologies. It is consequence of the gradually smaller power generated by the instrumentation, that follows a f^α law with frequency, being α≥1 variable depending on the signal source’s technology. The proposed approach is based on an optimal data reduction scenario which redounds in a maximum signal to noise ratio increase for the signal pattern, with minimum information losses. After theoretical formulation, practical applications of the technique are proposed.

  7. Perception in noise with the Digisonic SP cochlear implant: Clinical trial of Saphyr processor's upgraded signal processing.

    Science.gov (United States)

    Bergeron, F; Hotton, M

    2016-06-01

    In 2012, Bergeron et al. presented the outcomes of a study where speech recognition abilities were compared between the four major cochlear implant manufacturers from comparable samples assessed with the same protocols. At this moment, results showed no significant difference in speech perception between devices in quiet and in different noise conditions. But, while most devices appeared only slightly disturbed by the presence of a low to moderate noise level, the Oticon Medical device appeared significantly more sensitive to a degraded environment. In 2013, the signal processing strategy of this device has been upgraded. This study proposes to assess the benefits derived from this upgrade. The study involves eighteen adults; most were also part of the 2012 study. All were tested before the implementation of the new signal processing strategy, immediately following the implementation of the strategy and after a one-month experience with the strategy. The same speech recognition test and conditions used in the 2012 study were applied, that is the HINT in quiet and in noise at +10, +5 and 0dB signal to noise ratio. Subjective impressions on the upgraded strategy were also gathered. The study evidences similar performance for speech perception in quiet, but significant improvements for speech perception in noise with the new processing strategy compared to the original. Subjective reports confirm this improvement in more challenging conditions. The high sensitivity to a degraded environment observed with the original Oticon Medical device has been significantly reduced by the introduction of more efficient noise reduction processing strategies. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

  8. Optimization of the exposure parameters with signal-to-noise ratios considering human visual characteristics in digital mammography

    Science.gov (United States)

    Yamada, Maki; Kato, Yuri; Fujita, Naotoshi; Kodera, Yoshie

    2010-04-01

    The use of digital mammography systems has become widespread recently. However, the optimal exposure parameters are uncertain in clinical practice. We need to optimize the exposure parameter in digital mammography while maximizing image quality and minimizing patient dose. The purpose of this study was to evaluate the most beneficial exposure variable-tube voltage for each compressed breast thickness-with these indices: noise power spectrum, noise equivalent quanta, detective quantum efficiency, and signal-to-noise ratios (SNR). In this study, the SNRs were derived from the perceived statistical decision theory model with the internal noise of eye-brain system (SNRi), contrived and studied by Loo LN1), Ishida M et al. 2) These image quality indices were obtained under a fixed average glandular dose (AGD) and a fixed image contrast. Our results indicated that when the image contrast and AGD was constant, for phantom thinner than 5 cm, an increase of the tube voltage did not improve the noise property of images very much. The results also showed that image property with the target/filter Mo/Rh was better than that with Mo/Mo for phantom thicker than 4 cm. In general, it is said that high tube voltage delivers improved noise property. Our result indicates that this common theory is not realized with the x-ray energy level for mammography.

  9. Signals and Noises Acting On The Accelerometer Mounted In The Mpo (mercury Planetary Orbiter).

    Science.gov (United States)

    Iafolla, V.; Fiorenza, E.; Lucchesi, D.; Milyukov, V.; Nozzoli, S.

    The RadioScience experiments proposed for the BepiClombo ESA CORNERSTONE are aiming at performing planetary measurements such as: the rotation state of Mer- cury, the global structure of its gravity field and the local gravitational anomalies, but also to test some aspects of the General Relativity, to an unprecedented level of accu- racy. A high sensitivity accelerometer will measure the inertial acceleration acting on the MPO; these data, together with tracking data are used to evaluate the purely gravi- tational trajectory of the MPO, by transforming it to a virtual drag-free satellite system. At the Istituto di Fisica dello Spazio Interplanetario (IFSI) a high sensitive accelerom- eter named ISA (Italian Spring Accelerometer)* and considered for this mission has been studied. The main problems concerning the use of the accelerometer are related to the high dynamics necessary to follow the variation of the acceleration signals, with accuracy equal to 10^-9 g/sqr(Hz), and very high at the MPO orbital period and due to thermal noise introduced at the sidereal period of Mercury. The description of the accelerometer will be presented, with particular attention to the thermal problems and to the analysis regarding the choice of the mounting position on the MPO. *Project funded by the Italian Space Agency (ASI).

  10. Statistical process control: separating signal from noise in emergency department operations.

    Science.gov (United States)

    Pimentel, Laura; Barrueto, Fermin

    2015-05-01

    Statistical process control (SPC) is a visually appealing and statistically rigorous methodology very suitable to the analysis of emergency department (ED) operations. We demonstrate that the control chart is the primary tool of SPC; it is constructed by plotting data measuring the key quality indicators of operational processes in rationally ordered subgroups such as units of time. Control limits are calculated using formulas reflecting the variation in the data points from one another and from the mean. SPC allows managers to determine whether operational processes are controlled and predictable. We review why the moving range chart is most appropriate for use in the complex ED milieu, how to apply SPC to ED operations, and how to determine when performance improvement is needed. SPC is an excellent tool for operational analysis and quality improvement for these reasons: 1) control charts make large data sets intuitively coherent by integrating statistical and visual descriptions; 2) SPC provides analysis of process stability and capability rather than simple comparison with a benchmark; 3) SPC allows distinction between special cause variation (signal), indicating an unstable process requiring action, and common cause variation (noise), reflecting a stable process; and 4) SPC keeps the focus of quality improvement on process rather than individual performance. Because data have no meaning apart from their context, and every process generates information that can be used to improve it, we contend that SPC should be seriously considered for driving quality improvement in emergency medicine. Copyright © 2015 Elsevier Inc. All rights reserved.

  11. The flat fielding and achievable signal-to-noise of the MAMA detectors

    Science.gov (United States)

    Kaiser, Mary Elizabeth; Lindler, Don J.; Bohlin, Ralph C.

    1997-01-01

    The Space Telescope Imaging Spectrograph (STIS) was designed to achieve a signal-to-noise (S/N) of at least 100:1 per resolution element. Multi-Anode Microchannel Arrays (MAMA) observations during Servicing Mission Orbital Verification (SMOV) confirm that this specification can be met. From analysis of a single spectrum of GD153, with counting statistics of approximately 165 a S/N of approximately 125 is achieved per spectral resolution element in the far ultraviolet (FUV) over the spectral range of 1280A to 1455A. Co-adding spectra of GRW+7OD5824 to increase the counting statistics to approximately 300 yields a S/N of approximately 190 per spectral resolution element over the region extending from 1347A to 1480A in the FUV. In the near ultraviolet (NUV), a single spectrum of GRW+7OD5824 with counting statistics of approximately 200 yields a S/N of approximately 150 per spectral resolution element over the spectral region extending from 2167 to 2520A. Details of the flat field construction, the spectral extraction, and the definition of a spectral resolution element will be described in the text.

  12. The Ultimate Signal-to-Noise Ratio in Realistic Body Models

    Science.gov (United States)

    Guérin, Bastien; Villena, Jorge F.; Polimeridis, Athanasios G.; Adalsteinsson, Elfar; Daniel, Luca; White, Jacob K.; Wald, Lawrence L.

    2017-01-01

    Purpose We compute the ultimate signal-to-noise ratio (uSNR) and G-factor (uGF) in a realistic head model from 0.5 to 21 Tesla. Methods We excite the head model and a uniform sphere with a large number of electric and magnetic dipoles placed at 3 cm from the object. The resulting electromagnetic fields are computed using an ultrafast volume integral solver, which are used as basis functions for the uSNR and uGF computations. Results Our generalized uSNR calculation shows good convergence in the sphere and the head and is in close agreement with the dyadic Green’s function approach in the uniform sphere. In both models, the uSNR versus B0 trend was linear at shallow depths and supralinear at deeper locations. At equivalent positions, the rate of increase of the uSNR with B0 was greater in the sphere than in the head model. The uGFs were lower in the realistic head than in the sphere for acceleration in the anterior-posterior direction, but similar for the left-right direction. Conclusion The uSNR and uGFs are computable in nonuniform body models and provide fundamental performance limits for human imaging with close-fitting MRI array coils. PMID:27917528

  13. Weighting analysis of pellet quality attributes using Multi Response Signal to Noise (MRSN) method

    Science.gov (United States)

    Parkhan, A.; Widodo, I. D.; Amin, F. N.

    2017-12-01

    Quality of pellets, one form of animal feed, is not only measured by the nutritional content but also by its physical form. The physical strength of the pellet is determined from crushing and not easily moldy. Both quality characteristics are measured by reliability (pellet durability index) and resistance (water content percentage). In order to improve the quality of pellet, this study applied Multi Response Signal to Noise (MRSN) method. The weight of product quality attributes used will influence the method in determining the selected alternatives. To accommodate the weighting of dynamic product quality attributes, this study also ran weighting sensitivity analysis of product quality attributes. The results showed that the combination of factor level that produced the optimal pellet is A2, B1, C1, D1, E1, F1, G2 or combination of production process run with vapor pressure 1.9 bar, temperature conditioner 80 ° C, 3.5mm pellet diameter mold, cooler temperature 30 ° C, time in cooler 2 minutes, roller distance 1.5 cm, mixing time 175 seconds. This optimum combination can increase PDI percentage by 2.132% and decrease difference to target of water content by 0.234%. The optimum factor level combination will change if the weight for % PDI rises to be more than 0.77228 or decreases to be less than 0.00561, or in other words, the optimum combination will not change if the weight for % PDI is in the range 0.00561 - 0.77228.

  14. Sparse Signal Inversion with Impulsive Noise by Dual Spectral Projected Gradient Method

    Directory of Open Access Journals (Sweden)

    Liang Ding

    2017-01-01

    Full Text Available We consider sparse signal inversion with impulsive noise. There are three major ingredients. The first is regularizing properties; we discuss convergence rate of regularized solutions. The second is devoted to the numerical solutions. It is challenging due to the fact that both fidelity and regularization term lack differentiability. Moreover, for ill-conditioned problems, sparsity regularization is often unstable. We propose a novel dual spectral projected gradient (DSPG method which combines the dual problem of multiparameter regularization with spectral projection gradient method to solve the nonsmooth l1+l1 optimization functional. We show that one can overcome the nondifferentiability and instability by adding a smooth l2 regularization term to the original optimization functional. The advantage of the proposed functional is that its convex duality reduced to a constraint smooth functional. Moreover, it is stable even for ill-conditioned problems. Spectral projected gradient algorithm is used to compute the minimizers and we prove the convergence. The third is numerical simulation. Some experiments are performed, using compressed sensing and image inpainting, to demonstrate the efficiency of the proposed approach.

  15. Quantification of the accuracy limits of image registration using peak signal-to-noise ratio.

    Science.gov (United States)

    Tanabe, Yoshinori; Ishida, Takayuki

    2017-03-01

    A new method was developed for quantifying the accuracy limits of image registration devices and the distortion of anatomical structures in verification images without image registration. A correlation was found between peak signal-to-noise ratio (PSNR) and the amount of parallel movement (1-10 mm at 1-mm intervals) of a rectangular parallelepiped phantom [correlation coefficient (CC) -0.91, contribution ratio (CR) 0.83]. Rotating the phantom from 1° to 10° at 1° intervals produced a similar correlation with PSNR (CC -0.91, CR 0.83). To allow for manual registration, the grid pattern of the Mylar top plate was extracted from 455 pelvic portal images of 21 patients using a band-pass filtering technique. This revealed a different correlation between the original data (CC -0.62, CR 0.38) and averaged data (CC -0.96, CR 0.92), but this is considered to have been caused by structural distortion and manual matching errors. Thus, PSNR can be used to evaluate the accuracy limits of image registration and provide a judgment index that can be used in re-planning or re-setup in adaptive radiotherapy.

  16. The differential Howland current source with high signal to noise ratio for bioimpedance measurement system

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Jinzhen; Li, Gang; Lin, Ling, E-mail: linling@tju.edu.cn [State Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin, People' s Republic of China, and Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, Tianjin University, Tianjin (China); Qiao, Xiaoyan [College of Physics and Electronic Engineering, Shanxi University, Shanxi (China); Wang, Mengjun [School of Information Engineering, Hebei University of Technology, Tianjin (China); Zhang, Weibo [Institute of Acupuncture and Moxibustion China Academy of Chinese Medical Sciences, Beijing (China)

    2014-05-15

    The stability and signal to noise ratio (SNR) of the current source circuit are the important factors contributing to enhance the accuracy and sensitivity in bioimpedance measurement system. In this paper we propose a new differential Howland topology current source and evaluate its output characters by simulation and actual measurement. The results include (1) the output current and impedance in high frequencies are stabilized after compensation methods. And the stability of output current in the differential current source circuit (DCSC) is 0.2%. (2) The output impedance of two current circuits below the frequency of 200 KHz is above 1 MΩ, and below 1 MHz the output impedance can arrive to 200 KΩ. Then in total the output impedance of the DCSC is higher than that of the Howland current source circuit (HCSC). (3) The SNR of the DCSC are 85.64 dB and 65 dB in the simulation and actual measurement with 10 KHz, which illustrates that the DCSC effectively eliminates the common mode interference. (4) The maximum load in the DCSC is twice as much as that of the HCSC. Lastly a two-dimensional phantom electrical impedance tomography is well reconstructed with the proposed HCSC. Therefore, the measured performance shows that the DCSC can significantly improve the output impedance, the stability, the maximum load, and the SNR of the measurement system.

  17. Approaching ultimate intrinsic signal-to-noise ratio with loop and dipole antennas.

    Science.gov (United States)

    Lattanzi, Riccardo; Wiggins, Graham C; Zhang, Bei; Duan, Qi; Brown, Ryan; Sodickson, Daniel K

    2017-07-04

    Previous work with body-size objects suggested that loops are optimal MR detectors at low fields, whereas electric dipoles are required to maximize signal-to-noise ratio (SNR) at ultrahigh fields ( ≥ 7 T). Here we investigated how many loops and/or dipoles are needed to approach the ultimate intrinsic SNR (UISNR) at various field strengths. We calculated the UISNR inside dielectric cylinders mimicking different anatomical regions. We assessed the performance of various arrays with respect to the UISNR. We validated our results by comparing simulated and experimental coil performance maps. Arrays with an increasing number of loops can rapidly approach the UISNR at fields up to 3 T, but are suboptimal at ultrahigh fields for body-size objects. The opposite is true for dipole arrays. At 7 T and above, 16 dipoles provide considerably larger central SNR than any possible loop array, and minimal g factor penalty for parallel imaging. Electric dipoles can be advantageous at ultrahigh fields because they can produce both curl-free and divergence-free currents, whereas loops are limited to divergence-free contributions only. Combining loops and dipoles may be optimal for body imaging at 3 T, whereas arrays of loops or dipoles alone may perform better at lower or higher field strengths, respectively. Magn Reson Med, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

  18. The differential Howland current source with high signal to noise ratio for bioimpedance measurement system

    Science.gov (United States)

    Liu, Jinzhen; Qiao, Xiaoyan; Wang, Mengjun; Zhang, Weibo; Li, Gang; Lin, Ling

    2014-05-01

    The stability and signal to noise ratio (SNR) of the current source circuit are the important factors contributing to enhance the accuracy and sensitivity in bioimpedance measurement system. In this paper we propose a new differential Howland topology current source and evaluate its output characters by simulation and actual measurement. The results include (1) the output current and impedance in high frequencies are stabilized after compensation methods. And the stability of output current in the differential current source circuit (DCSC) is 0.2%. (2) The output impedance of two current circuits below the frequency of 200 KHz is above 1 MΩ, and below 1 MHz the output impedance can arrive to 200 KΩ. Then in total the output impedance of the DCSC is higher than that of the Howland current source circuit (HCSC). (3) The SNR of the DCSC are 85.64 dB and 65 dB in the simulation and actual measurement with 10 KHz, which illustrates that the DCSC effectively eliminates the common mode interference. (4) The maximum load in the DCSC is twice as much as that of the HCSC. Lastly a two-dimensional phantom electrical impedance tomography is well reconstructed with the proposed HCSC. Therefore, the measured performance shows that the DCSC can significantly improve the output impedance, the stability, the maximum load, and the SNR of the measurement system.

  19. Efficient algorithm for baseline wander and powerline noise removal from ECG signals based on discrete Fourier series.

    Science.gov (United States)

    Bahaz, Mohamed; Benzid, Redha

    2018-02-05

    Electrocardiogram (ECG) signals are often contaminated with artefacts and noises which can lead to incorrect diagnosis when they are visually inspected by cardiologists. In this paper, the well-known discrete Fourier series (DFS) is re-explored and an efficient DFS-based method is proposed to reduce contribution of both baseline wander (BW) and powerline interference (PLI) noises in ECG records. In the first step, the determination of the exact number of low frequency harmonics contributing in BW is achieved. Next, the baseline drift is estimated by the sum of all associated Fourier sinusoids components. Then, the baseline shift is discarded efficiently by a subtraction of its approximated version from the original biased ECG signal. Concerning the PLI, the subtraction of the contributing harmonics calculated in the same manner reduces efficiently such type of noise. In addition of visual quality results, the proposed algorithm shows superior performance in terms of higher signal-to-noise ratio and smaller mean square error when faced to the DCT-based algorithm.

  20. Signal vs. Noise: Obtaining a representative δ18O record in a low-accumulation region

    Science.gov (United States)

    Münch, Thomas; Kipfstuhl, Sepp; Freitag, Johannes; Meyer, Hanno; Laepple, Thomas

    2015-04-01

    Single ice cores have been proven to be a key archive to reconstruct climate changes on glacial to interglacial time scales in temperature as well as in greenhouse gases and many other climate parameters. In contrast, for the Holocene climate evolution single ice cores are likely less reliable recorders. The small amplitude of Holocene climate changes, together with the goal to reconstruct high-temporal resolution records down to subannual timescales, poses a significant challenge to the interpretation of ice core signals, especially in low-accumulation regions as the Antarctic plateau. In order to learn about the representativity of single firn cores and to optimize future ice-core based climate reconstructions, we undertook an extensive study of replicate firn coring and surface snow sampling at Kohnen station on Dronning Maud Land, Antarctica. For the first time - to our knowledge - two-dimensional images of the water isotope and density structure of the upper firn have been obtained from two 45 m long and 1.2 m deep firn trenches separated at a distance of 500 m, yielding a climate proxy archive spanning roughly the last five years. In this contribution, we present the results of the stable water isotope compositions obtained from the two firn trenches. Seasonal layering of the isotopes is following an absolute depth scale likely caused by an annual reorganization of the snow surface directly related to the local dune scale. Local surface winds cause highly variable isotopic signals of the surface snow, featuring a similar range as the seasonal cycle. However, even in deeper layers, strong perturbations of the isotopic stratigraphy are found, resulting in a low representativity of single firn cores. On the contrary, the mean trench profiles are highly correlated, giving a representative climate signal over a spatial scale of at least 500 m. The decorrelation length of the stratigraphic noise is ~10 m, yielding an estimate of an optimal sampling strategy for