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).

Ultrasonic correlator versus signal averager as a signal to noise enhancement instrument

Science.gov (United States)

Kishoni, Doron; Pietsch, Benjamin E.

1989-01-01

Ultrasonic inspection of thick and attenuating materials is hampered by the reduced amplitudes of the propagated waves to a degree that the noise is too high to enable meaningful interpretation of the data. In order to overcome the low Signal to Noise (S/N) ratio, a correlation technique has been developed. In this method, a continuous pseudo-random pattern generated digitally is transmitted and detected by piezoelectric transducers. A correlation is performed in the instrument between the received signal and a variable delayed image of the transmitted one. The result is shown to be proportional to the impulse response of the investigated material, analogous to a signal received from a pulsed system, with an improved S/N ratio. The degree of S/N enhancement depends on the sweep rate. This paper describes the correlator, and compares it to the method of enhancing S/N ratio by averaging the signals. The similarities and differences between the two are highlighted and the potential advantage of the correlator system is explained.

Regional improvement of signal-to-noise and contrast-to-noise ratios in dual-screen CR chest imaging - a phantom study

International Nuclear Information System (INIS)

Liu Xinming; Shaw, Chris C.

2001-01-01

The improvement of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in dual-screen computed radiography (CR) has been investigated for various regions in images of an anthropomorphic chest phantom. With the dual-screen CR technique, two image plates are placed in a cassette and exposed together during imaging. The exposed plates are separately scanned to form a front image and a back image, which are then registered and superimposed to form a composite image with improved SNRs and CNRs. The improvement can be optimized by applying specifically selected weighting factors during superimposition. In this study, dual-screen CR images of an anthropomorphic chest phantom were acquired and formed with four different combinations of standard resolution (ST) and high-resolution (HR) screens: ST-ST, ST-HR, HR-ST, and HR-HR. SNRs and their improvements were measured and compared over twelve representative regions-of-interest (ROIs) in these images. A 19.1%-45.7% increase of the SNR was observed, depending on the ROI and screen combination used. The optimal weighting factors were found to vary by only 4.5%-12.4%. Largest improvement was found in the lung field for all screen combinations. Improvement of CNRs was investigated over two ROIs in the lung field using the rib bones as the contrast objects and a 29.2%-43.9% improvement of the CNR was observed. Among the four screen combinations, ST-ST resulted in the most SNR and CNR improvement, followed in order by HR-ST, HR-HR, and ST-HR. The HR-ST combination yielded the lowest spatial variation of the optimal weighting factors with improved SNRs and CNRs close to those of the ST-ST combination

Signal-to-noise ratio application to seismic marker analysis and fracture detection

Science.gov (United States)

Xu, Hui-Qun; Gui, Zhi-Xian

2014-03-01

Seismic data with high signal-to-noise ratios (SNRs) are useful in reservoir exploration. To obtain high SNR seismic data, significant effort is required to achieve noise attenuation in seismic data processing, which is costly in materials, and human and financial resources. We introduce a method for improving the SNR of seismic data. The SNR is calculated by using the frequency domain method. Furthermore, we optimize and discuss the critical parameters and calculation procedure. We applied the proposed method on real data and found that the SNR is high in the seismic marker and low in the fracture zone. Consequently, this can be used to extract detailed information about fracture zones that are inferred by structural analysis but not observed in conventional seismic data.

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.

Imaging resolution signal-to-noise ratio in transverse phase amplification from classical information theory

International Nuclear Information System (INIS)

French, Doug; Huang Zun; Pao, H.-Y.; Jovanovic, Igor

2009-01-01

A quantum phase amplifier operated in the spatial domain can improve the signal-to-noise ratio in imaging beyond the classical limit. The scaling of the signal-to-noise ratio with the gain of the quantum phase amplifier is derived from classical information theory

MIMO Radar Transceiver Design for High Signal-to-Interference-Plus-Noise Ratio

KAUST Repository

Lipor, John

2013-05-12

into subvectors and then multiplying each subvector with its corresponding weight vector can improve performance and reduce the length of the data vector. Simulation results show that all methods are capable of matching a desired beampattern. Signal-to-interference- plus-noise ratio (SINR) calculations demonstrate a significant improvement over the unaltered MIMO case.

Using optical fibers with different modes to improve the signal-to-noise ratio of diffuse correlation spectroscopy flow-oximeter measurements

OpenAIRE

He, Lian; Lin, Yu; Shang, Yu; Shelton, Brent J.; Yu, Guoqiang

2013-01-01

The dual-wavelength diffuse correlation spectroscopy (DCS) flow-oximeter is an emerging technique enabling simultaneous measurements of blood flow and blood oxygenation changes in deep tissues. High signal-to-noise ratio (SNR) is crucial when applying DCS technologies in the study of human tissues where the detected signals are usually very weak. In this study, single-mode, few-mode, and multimode fibers are compared to explore the possibility of improving the SNR of DCS flow-oximeter measure...

Low noise signal-to-noise ratio enhancing readout circuit for current-mediated active pixel sensors

International Nuclear Information System (INIS)

Ottaviani, Tony; Karim, Karim S.; Nathan, Arokia; Rowlands, John A.

2006-01-01

Diagnostic digital fluoroscopic applications continuously expose patients to low doses of x-ray radiation, posing a challenge to both the digital imaging pixel and readout electronics when amplifying small signal x-ray inputs. Traditional switch-based amorphous silicon imaging solutions, for instance, have produced poor signal-to-noise ratios (SNRs) at low exposure levels owing to noise sources from the pixel readout circuitry. Current-mediated amorphous silicon pixels are an improvement over conventional pixel amplifiers with an enhanced SNR across the same low-exposure range, but whose output also becomes nonlinear with increasing dosage. A low-noise SNR enhancing readout circuit has been developed that enhances the charge gain of the current-mediated active pixel sensor (C-APS). The solution takes advantage of the current-mediated approach, primarily integrating the signal input at the desired frequency necessary for large-area imaging, while adding minimal noise to the signal readout. Experimental data indicates that the readout circuit can detect pixel outputs over a large bandwidth suitable for real-time digital diagnostic x-ray fluoroscopy. Results from hardware testing indicate that the minimum achievable C-APS output current that can be discerned at the digital fluoroscopic output from the enhanced SNR readout circuit is 0.341 nA. The results serve to highlight the applicability of amorphous silicon current-mediated pixel amplifiers for large-area flat panel x-ray imagers

Signal processing method for Johnson noise thermometry

International Nuclear Information System (INIS)

Hwang, I. G.; Moon, B. S.; Kinser, Rpger

2003-01-01

The development of Johnson Noise Thermometry requires a high sensitive preamplifier circuit to pick up the temperature-related noise on the sensing element. However, the random noise generated in this amplification circuit causes a significant erroneous influence to the measurement. This paper describes signal processing mechanism of the Johnson Noise Thermometry system which is underway of development in collaboration between KAERI and ORNL. It adopts two identical amplifier channels and utilizes a digital signal processing technique to remove the independent noise of each channel. The CPSD(Cross Power Spectral Density) function is used to cancel the independent noise and the differentiation of narrow or single frequency peak from the CPSD data separates the common mode electromagnetic interference noise

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

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.

Improving the signal-to-noise ratio in mass and ion kinetic energy spectrometers

International Nuclear Information System (INIS)

Brenton, A.G.; Beynon, J.H.; Morgan, R.P.

1979-01-01

The signal-to-noise ratio in mass and ion kinetic energy spectrometers is limited by noise generated from the presence of scattered ions and neutrals. Methods of eliminating this are illustrated with reference to the ZAB-2F instrument manufactured by VG-Micromass Ltd. It is estimated that after the modifications the instrument is capable, on a routine basis, of measuring peaks corresponding to the arrival of ions at a rate of the order of 1 ion s -1 . (Auth.)

Enhancing scatterometry CD signal-to-noise ratio for 1x logic and memory challenges

Science.gov (United States)

Shaughnessy, Derrick; Krishnan, Shankar; Wei, Lanhua; Shchegrov, Andrei V.

2013-04-01

The ongoing transition from 2D to 3D structures in logic and memory has led to an increased adoption of scatterometry CD (SCD) for inline metrology. However, shrinking device dimensions in logic and high aspect ratios in memory represent primary challenges for SCD and require a significant breakthrough in improving signal-to-noise performance. We present a report on the new generation of SCD technology, enabled by a new laser-driven plasma source. The developed light source provides several key advantages over conventional arc lamps typically used in SCD applications. The plasma color temperature of the laser driven source is considerably higher than available with arc lamps resulting in >5X increase in radiance in the visible and >10X increase in radiance in the DUV when compared to sources on previous generation SCD tools while maintaining or improving source intensity noise. This high radiance across such a broad spectrum allows for the use of a single light source from 190-1700nm. When combined with other optical design changes, the higher source radiance enables reduction of measurement box size of our spectroscopic ellipsometer from 45×45um box to 25×25um box without compromising signal to noise ratio. The benefits for 1×nm SCD metrology of the additional photons across the DUV to IR spectrum have been found to be greater than the increase in source signal to noise ratio would suggest. Better light penetration in Si and poly-Si has resulted in improved sensitivity and correlation breaking for critical parameters in 1xnm FinFET and HAR flash memory structures.

Signal-to-noise ratios of multiplexing spectrometers in high backgrounds

Science.gov (United States)

Knacke, R. F.

1978-01-01

Signal-to-noise ratios and the amount of multiplexing gain achieved with a Michelson spectrometer during detector and background noise are studied. Noise caused by the warm background is found in 10 and 20-micron atmospheric windows in high resolution Fourier spectroscopy. An equation is derived for the signal-to-noise ratio based on the number of channels, total time to obtain the complete spectrum, the signal power in one spectral element, and the detector noise equivalent power in the presence of negligible background. Similar expressions are derived for backgrounds yielding a noise equivalent power to a spectral element, and backgrounds having flat spectra in the frequency range under investigation.

Structural Parameters of Star Clusters: Signal to Noise Effects

Directory of Open Access Journals (Sweden)

Narbutis D.

2015-09-01

Full Text Available We study the impact of photometric signal to noise on the accuracy of derived structural parameters of unresolved star clusters using MCMC model fitting techniques. Star cluster images were simulated as a smooth surface brightness distribution following a King profile convolved with a point spread function. The simulation grid was constructed by varying the levels of sky background and adjusting the cluster’s flux to a specified signal to noise. Poisson noise was introduced to a set of cluster images with the same input parameters at each node of the grid. Model fitting was performed using “emcee” algorithm. The presented posterior distributions of the parameters illustrate their uncertainty and degeneracies as a function of signal to noise. By defining the photometric aperture containing 80% of the cluster’s flux, we find that in all realistic sky background level conditions a signal to noise ratio of ~50 is necessary to constrain the cluster’s half-light radius to an accuracy better than ~20%. The presented technique can be applied to synthetic images simulating various observations of extragalactic star clusters.

Novel Signal Noise Reduction Method through Cluster Analysis, Applied to Photoplethysmography.

Science.gov (United States)

Waugh, William; Allen, John; Wightman, James; Sims, Andrew J; Beale, Thomas A W

2018-01-01

Physiological signals can often become contaminated by noise from a variety of origins. In this paper, an algorithm is described for the reduction of sporadic noise from a continuous periodic signal. The design can be used where a sample of a periodic signal is required, for example, when an average pulse is needed for pulse wave analysis and characterization. The algorithm is based on cluster analysis for selecting similar repetitions or pulses from a periodic single. This method selects individual pulses without noise, returns a clean pulse signal, and terminates when a sufficiently clean and representative signal is received. The algorithm is designed to be sufficiently compact to be implemented on a microcontroller embedded within a medical device. It has been validated through the removal of noise from an exemplar photoplethysmography (PPG) signal, showing increasing benefit as the noise contamination of the signal increases. The algorithm design is generalised to be applicable for a wide range of physiological (physical) signals.

Novel Oversampling Technique for Improving Signal-to-Quantization Noise Ratio on Accelerometer-Based Smart Jerk Sensors in CNC Applications.

Science.gov (United States)

Rangel-Magdaleno, Jose J; Romero-Troncoso, Rene J; Osornio-Rios, Roque A; Cabal-Yepez, Eduardo

2009-01-01

Jerk monitoring, defined as the first derivative of acceleration, has become a major issue in computerized numeric controlled (CNC) machines. Several works highlight the necessity of measuring jerk in a reliable way for improving production processes. Nowadays, the computation of jerk is done by finite differences of the acceleration signal, computed at the Nyquist rate, which leads to low signal-to-quantization noise ratio (SQNR) during the estimation. The novelty of this work is the development of a smart sensor for jerk monitoring from a standard accelerometer, which has improved SQNR. The proposal is based on oversampling techniques that give a better estimation of jerk than that produced by a Nyquist-rate differentiator. Simulations and experimental results are presented to show the overall methodology performance.

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.

Digital signal processing for the Johnson noise thermometry: a time series analysis of the Johnson noise

International Nuclear Information System (INIS)

Moon, Byung Soo; Hwang, In Koo; Chung, Chong Eun; Kwon, Kee Choon; David, E. H.; Kisner, R.A.

2004-06-01

In this report, we first proved that a random signal obtained by taking the sum of a set of signal frequency signals generates a continuous Markov process. We used this random signal to simulate the Johnson noise and verified that the Johnson noise thermometry can be used to improve the measurements of the reactor coolant temperature within an accuracy of below 0.14%. Secondly, by using this random signal we determined the optimal sampling rate when the frequency band of the Johnson noise signal is given. Also the results of our examination on how good the linearity of the Johnson noise is and how large the relative error of the temperature could become when the temperature increases are described. Thirdly, the results of our analysis on a set of the Johnson noise signal blocks taken from a simple electric circuit are described. We showed that the properties of the continuous Markov process are satisfied even when some channel noises are present. Finally, we describe the algorithm we devised to handle the problem of the time lag in the long-term average or the moving average in a transient state. The algorithm is based on the Haar wavelet and is to estimate the transient temperature that has much smaller time delay. We have shown that the algorithm can track the transient temperature successfully

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.

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

Image restoration by Wiener filtering in the presence of signal-dependent noise.

Science.gov (United States)

Kondo, K; Ichioka, Y; Suzuki, T

1977-09-01

An optimum filter to restore the degraded image due to blurring and the signal-dependent noise is obtained on the basis of the theory of Wiener filtering. Computer simulations of image restoration using signal-dependent noise models are carried out. It becomes clear that the optimum filter, which makes use of a priori information on the signal-dependent nature of the noise and the spectral density of the signal and the noise showing significant spatial correlation, is potentially advantageous.

Audibility of modulation noise in stationary signals

NARCIS (Netherlands)

Neelen, J.J.M.

1970-01-01

Recordings of an acoustic signal on magnetic tape often show noise, which may be divided into two main classes: additive noise and multiplicative noise. A characteristic of the latter is that it is weak with weak signals and strong with strong signals. This modulation noise has been subjected to a

Analysis on frequency response of trans-impedance amplifier (TIA) for signal-to-noise ratio (SNR) enhancement in optical signal detection system using lock-in amplifier (LIA)

Science.gov (United States)

Kim, Ji-Hoon; Jeon, Su-Jin; Ji, Myung-Gi; Park, Jun-Hee; Choi, Young-Wan

2017-02-01

Lock-in amplifier (LIA) has been widely used in optical signal detection systems because it can measure small signal under high noise level. Generally, The LIA used in optical signal detection system is composed of transimpedance amplifier (TIA), phase sensitive detector (PSD) and low pass filter (LPF). But commercial LIA using LPF is affected by flicker noise. To avoid flicker noise, there is 2ω detection LIA using BPF. To improve the dynamic reserve (DR) of the 2ω LIA, the signal to noise ratio (SNR) of the TIA should be improved. According to the analysis of frequency response of the TIA, the noise gain can be minimized by proper choices of input capacitor (Ci) and feed-back network in the TIA in a specific frequency range. In this work, we have studied how the SNR of the TIA can be improved by a proper choice of frequency range. We have analyzed the way to control this frequency range through the change of passive component in the TIA. The result shows that the variance of the passive component in the TIA can change the specific frequency range where the noise gain is minimized in the uniform gain region of the TIA.

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

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......Existing convex relaxation-based approaches to reconstruction in compressed sensing assume that noise in the measurements is independent of the signal of interest. We consider the case of noise being linearly correlated with the signal and introduce a simple technique for improving compressed...... sensing reconstruction from such measurements. The technique is based on a linear model of the correlation of additive noise with the signal. The modification of the reconstruction algorithm based on this model is very simple and has negligible additional computational cost compared to standard...

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

This paper introduces a nonlinear feature extraction method based on kernels for remote sensing data analysis. The proposed approach is based on the minimum noise fraction (MNF) transform, which maximizes the signal variance while also minimizing the estimated noise variance. We here propose...... 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...

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

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.

Improvement of intelligibility of ideal binary-masked noisy speech by adding background noise.

Science.gov (United States)

Cao, Shuyang; Li, Liang; Wu, Xihong

2011-04-01

When a target-speech/masker mixture is processed with the signal-separation technique, ideal binary mask (IBM), intelligibility of target speech is remarkably improved in both normal-hearing listeners and hearing-impaired listeners. Intelligibility of speech can also be improved by filling in speech gaps with un-modulated broadband noise. This study investigated whether intelligibility of target speech in the IBM-treated target-speech/masker mixture can be further improved by adding a broadband-noise background. The results of this study show that following the IBM manipulation, which remarkably released target speech from speech-spectrum noise, foreign-speech, or native-speech masking (experiment 1), adding a broadband-noise background with the signal-to-noise ratio no less than 4 dB significantly improved intelligibility of target speech when the masker was either noise (experiment 2) or speech (experiment 3). The results suggest that since adding the noise background shallows the areas of silence in the time-frequency domain of the IBM-treated target-speech/masker mixture, the abruption of transient changes in the mixture is smoothed and the perceived continuity of target-speech components becomes enhanced, leading to improved target-speech intelligibility. The findings are useful for advancing computational auditory scene analysis, hearing-aid/cochlear-implant designs, and understanding of speech perception under "cocktail-party" conditions.

Training to Improve Hearing Speech in Noise: Biological Mechanisms

Science.gov (United States)

Song, Judy H.; Skoe, Erika; Banai, Karen

2012-01-01

We investigated training-related improvements in listening in noise and the biological mechanisms mediating these improvements. Training-related malleability was examined using a program that incorporates cognitively based listening exercises to improve speech-in-noise perception. Before and after training, auditory brainstem responses to a speech syllable were recorded in quiet and multitalker noise from adults who ranged in their speech-in-noise perceptual ability. Controls did not undergo training but were tested at intervals equivalent to the trained subjects. Trained subjects exhibited significant improvements in speech-in-noise perception that were retained 6 months later. Subcortical responses in noise demonstrated training-related enhancements in the encoding of pitch-related cues (the fundamental frequency and the second harmonic), particularly for the time-varying portion of the syllable that is most vulnerable to perceptual disruption (the formant transition region). Subjects with the largest strength of pitch encoding at pretest showed the greatest perceptual improvement. Controls exhibited neither neurophysiological nor perceptual changes. We provide the first demonstration that short-term training can improve the neural representation of cues important for speech-in-noise perception. These results implicate and delineate biological mechanisms contributing to learning success, and they provide a conceptual advance to our understanding of the kind of training experiences that can influence sensory processing in adulthood. PMID:21799207

Noise in Neural Networks: Thresholds, Hysteresis, and Neuromodulation of Signal-To-Noise

Science.gov (United States)

Keeler, James D.; Pichler, Elgar E.; Ross, John

1989-03-01

We study a neural-network model including Gaussian noise, higher-order neuronal interactions, and neuromodulation. For a first-order network, there is a threshold in the noise level (phase transition) above which the network displays only disorganized behavior and critical slowing down near the noise threshold. The network can tolerate more noise if it has higher-order feedback interactions, which also lead to hysteresis and multistability in the network dynamics. The signal-to-noise ratio can be adjusted in a biological neural network by neuromodulators such as norepinephrine. Comparisons are made to experimental results and further investigations are suggested to test the effects of hysteresis and neuromodulation in pattern recognition and learning. We propose that norepinephrine may ``quench'' the neural patterns of activity to enhance the ability to learn details.

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.

Downhole microseismic signal-to-noise ratio enhancement via strip matching shearlet transform

Science.gov (United States)

Li, Juan; Ji, Shuo; Li, Yue; Qian, Zhihong; Lu, Weili

2018-04-01

Shearlet transform has been proved effective in noise attenuation. However, because of the low magnitude and high frequency of downhole microseismic signals, the coefficient values of valid signals and noise are similar in the shearlet domain. As a result, it is hard to suppress the noise. In this paper, we present a novel signal-to-noise ratio enhancement scheme called strip matching shearlet transform. The method takes into account the directivity of microseismic events and shearlets. Through strip matching, the matching degree in direction between them has been promoted. Then the coefficient values of valid signals are much larger than those of the noise. Consequently, we can separate them well with the help of thresholding. The experimental results on both synthetic records and field data illustrate that our proposed method preserves the useful components and attenuates the noise well.

Real-time photonic sampling with improved signal-to-noise and distortion ratio using polarization-dependent modulators

Science.gov (United States)

Liang, Dong; Zhang, Zhiyao; Liu, Yong; Li, Xiaojun; Jiang, Wei; Tan, Qinggui

2018-04-01

A real-time photonic sampling structure with effective nonlinearity suppression and excellent signal-to-noise ratio (SNR) performance is proposed. The key points of this scheme are the polarization-dependent modulators (P-DMZMs) and the sagnac loop structure. Thanks to the polarization sensitive characteristic of P-DMZMs, the differences between transfer functions of the fundamental signal and the distortion become visible. Meanwhile, the selection of specific biases in P-DMZMs is helpful to achieve a preferable linearized performance with a low noise level for real-time photonic sampling. Compared with the quadrature-biased scheme, the proposed scheme is capable of valid nonlinearity suppression and is able to provide a better SNR performance even in a large frequency range. The proposed scheme is proved to be effective and easily implemented for real time photonic applications.

Multiplane wave imaging increases signal-to-noise ratio in ultrafast ultrasound imaging

International Nuclear Information System (INIS)

Tiran, Elodie; Deffieux, Thomas; Correia, Mafalda; Maresca, David; Osmanski, Bruno-Felix; Pernot, Mathieu; Tanter, Mickael; Sieu, Lim-Anna; Bergel, Antoine; Cohen, Ivan

2015-01-01

Ultrafast imaging using plane or diverging waves has recently enabled new ultrasound imaging modes with improved sensitivity and very high frame rates. Some of these new imaging modalities include shear wave elastography, ultrafast Doppler, ultrafast contrast-enhanced imaging and functional ultrasound imaging. Even though ultrafast imaging already encounters clinical success, increasing even more its penetration depth and signal-to-noise ratio for dedicated applications would be valuable.Ultrafast imaging relies on the coherent compounding of backscattered echoes resulting from successive tilted plane waves emissions; this produces high-resolution ultrasound images with a trade-off between final frame rate, contrast and resolution. In this work, we introduce multiplane wave imaging, a new method that strongly improves ultrafast images signal-to-noise ratio by virtually increasing the emission signal amplitude without compromising the frame rate. This method relies on the successive transmissions of multiple plane waves with differently coded amplitudes and emission angles in a single transmit event. Data from each single plane wave of increased amplitude can then be obtained, by recombining the received data of successive events with the proper coefficients.The benefits of multiplane wave for B-mode, shear wave elastography and ultrafast Doppler imaging are experimentally demonstrated. Multiplane wave with 4 plane waves emissions yields a 5.8  ±  0.5 dB increase in signal-to-noise ratio and approximately 10 mm in penetration in a calibrated ultrasound phantom (0.7 d MHz −1 cm −1 ). In shear wave elastography, the same multiplane wave configuration yields a 2.07  ±  0.05 fold reduction of the particle velocity standard deviation and a two-fold reduction of the shear wave velocity maps standard deviation. In functional ultrasound imaging, the mapping of cerebral blood volume results in a 3 to 6 dB increase of the contrast-to-noise ratio in

Detection of Noise in Composite Step Signal Pattern by Visualizing Signal Waveforms

Directory of Open Access Journals (Sweden)

Chaman Verma

2018-03-01

Full Text Available The Step Composite Signals is the combination of vital informative signals that are compressed and coded to produce a predefined test image on a display device. It carries the desired sequence of information from source to destination. This information may be transmitted as digital signal, video information or data signal required as an input for the destination module. For testing of display panels, Composite Test Signals are the most important attribute of test signal transmission system. In the current research paper we present an approach for the noise detection in Composite Step Signal by analysing Composite Step Signal waveforms. The analysis of the signal waveforms reveals that the noise affected components of the signal and subsequently noise reduction process is initiated which targets noisy signal component only. Thus the quality of signal is not compromised during noise reduction process.

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....

The deterioration of signal to noise ratio due to baseline restoration

International Nuclear Information System (INIS)

Henein, K.L.

1976-02-01

The deterioration of signal to noise ratio due to baseline restoration is theoretically studied. This study brings to the conclusion that a restorer has negligible influence on the signal to noise ratio when its time constant is ten times greater than that of the main amplifier filter, and that the rapid restorers prevail over the slow ones when the time constant of the filter is increased by at least 50% of its optimal value [fr

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…

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.

An Application of Reassigned Time-Frequency Representations for Seismic Noise/Signal Decomposition

Science.gov (United States)

Mousavi, S. M.; Langston, C. A.

2016-12-01

Seismic data recorded by surface arrays are often strongly contaminated by unwanted noise. This background noise makes the detection of small magnitude events difficult. An automatic method for seismic noise/signal decomposition is presented based upon an enhanced time-frequency representation. Synchrosqueezing is a time-frequency reassignment method aimed at sharpening a time-frequency picture. Noise can be distinguished from the signal and suppressed more easily in this reassigned domain. The threshold level is estimated using a general cross validation approach that does not rely on any prior knowledge about the noise level. Efficiency of thresholding has been improved by adding a pre-processing step based on higher order statistics and a post-processing step based on adaptive hard-thresholding. In doing so, both accuracy and speed of the denoising have been improved compared to our previous algorithms (Mousavi and Langston, 2016a, 2016b; Mousavi et al., 2016). The proposed algorithm can either kill the noise (either white or colored) and keep the signal or kill the signal and keep the noise. Hence, It can be used in either normal denoising applications or in ambient noise studies. Application of the proposed method on synthetic and real seismic data shows the effectiveness of the method for denoising/designaling of local microseismic, and ocean bottom seismic data. References: Mousavi, S.M., C. A. Langston., and S. P. Horton (2016), Automatic Microseismic Denoising and Onset Detection Using the Synchrosqueezed-Continuous Wavelet Transform. Geophysics. 81, V341-V355, doi: 10.1190/GEO2015-0598.1. Mousavi, S.M., and C. A. Langston (2016a), Hybrid Seismic Denoising Using Higher-Order Statistics and Improved Wavelet Block Thresholding. Bull. Seismol. Soc. Am., 106, doi: 10.1785/0120150345. Mousavi, S.M., and C.A. Langston (2016b), Adaptive noise estimation and suppression for improving microseismic event detection, Journal of Applied Geophysics., doi: http

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.

Signal noise/interferer combiner unit programmable (SINCUP)

Science.gov (United States)

Martinezdepison, Emilio

1988-12-01

The Signal Noise Interferer Combiner Unit Programmable (SINCUP) has been developed to facilitate laboratory performance testing of Very Low Frequency (VLF/Low Frequency (LF) receivers. To accomplish this, the unit allows the combining in controlled amounts of various real-world environmental and manmade interference with an information carrying signal. The externally modulated signal is combined with internally/externally generated Gaussian noise and/or with an internally/externally generated interferer. In order to test modern digital processing techniques, such as Adaptive Null Steering, Eigenvector Sorting, and Widrow-Hoff adaptive filters, SINCUP is capable of generating and meeting much higher signal-to-noise plus interference ratios than earlier channel simulators. The present software has been written to accommodate a dynamic signal-to-noise ratio (SNR) range from -60 to +60 dB. Higher dynamic range units could be implemented.

Removal of Stationary Sinusoidal Noise from Random Vibration Signals.

Energy Technology Data Exchange (ETDEWEB)

Johnson, Brian; Cap, Jerome S.

2018-02-01

In random vibration environments, sinusoidal line noise may appear in the vibration signal and can affect analysis of the resulting data. We studied two methods which remove stationary sine tones from random noise: a matrix inversion algorithm and a chirp-z transform algorithm. In addition, we developed new methods to determine the frequency of the tonal noise. The results show that both of the removal methods can eliminate sine tones in prefabricated random vibration data when the sine-to-random ratio is at least 0.25. For smaller ratios down to 0.02 only the matrix inversion technique can remove the tones, but the metrics to evaluate its effectiveness also degrade. We also found that using fast Fourier transforms best identified the tonal noise, and determined that band-pass-filtering the signals prior to the process improved sine removal. When applied to actual vibration test data, the methods were not as effective at removing harmonic tones, which we believe to be a result of mixed-phase sinusoidal noise.

Working memory training to improve speech perception in noise across languages.

Science.gov (United States)

Ingvalson, Erin M; Dhar, Sumitrajit; Wong, Patrick C M; Liu, Hanjun

2015-06-01

Working memory capacity has been linked to performance on many higher cognitive tasks, including the ability to perceive speech in noise. Current efforts to train working memory have demonstrated that working memory performance can be improved, suggesting that working memory training may lead to improved speech perception in noise. A further advantage of working memory training to improve speech perception in noise is that working memory training materials are often simple, such as letters or digits, making them easily translatable across languages. The current effort tested the hypothesis that working memory training would be associated with improved speech perception in noise and that materials would easily translate across languages. Native Mandarin Chinese and native English speakers completed ten days of reversed digit span training. Reading span and speech perception in noise both significantly improved following training, whereas untrained controls showed no gains. These data suggest that working memory training may be used to improve listeners' speech perception in noise and that the materials may be quickly adapted to a wide variety of listeners.

Optimal Noise Enhanced Signal Detection in a Unified Framework

Directory of Open Access Journals (Sweden)

Ting Yang

2016-06-01

Full Text Available In this paper, a new framework for variable detectors is formulated in order to solve different noise enhanced signal detection optimal problems, where six different disjoint sets of detector and discrete vector pairs are defined according to the two inequality-constraints on detection and false-alarm probabilities. Then theorems and algorithms constructed based on the new framework are presented to search the optimal noise enhanced solutions to maximize the relative improvements of the detection and the false-alarm probabilities, respectively. Further, the optimal noise enhanced solution of the maximum overall improvement is obtained based on the new framework and the relationship among the three maximums is presented. In addition, the sufficient conditions for improvability or non-improvability under the two certain constraints are given. Finally, numerous examples are presented to illustrate the theoretical results and the proofs of the main theorems are given in the Appendix.

An efficient optimization method to improve the measuring accuracy of oxygen saturation by using triangular wave optical signal

Science.gov (United States)

Li, Gang; Yu, Yue; Zhang, Cui; Lin, Ling

2017-09-01

The oxygen saturation is one of the important parameters to evaluate human health. This paper presents an efficient optimization method that can improve the accuracy of oxygen saturation measurement, which employs an optical frequency division triangular wave signal as the excitation signal to obtain dynamic spectrum and calculate oxygen saturation. In comparison to the traditional method measured RMSE (root mean square error) of SpO2 which is 0.1705, this proposed method significantly reduced the measured RMSE which is 0.0965. It is notable that the accuracy of oxygen saturation measurement has been improved significantly. The method can simplify the circuit and bring down the demand of elements. Furthermore, it has a great reference value on improving the signal to noise ratio of other physiological signals.

Comparison of methods for removing electromagnetic noise from electromyographic signals.

Science.gov (United States)

Defreitas, Jason M; Beck, Travis W; Stock, Matt S

2012-02-01

The purpose of this investigation was to compare three different methods of removing noise from monopolar electromyographic (EMG) signals: (a) electrical shielding with a Faraday cage, (b) denoising with a digital notch-filter and (c) applying a bipolar differentiation with another monopolar EMG signal. Ten men and ten women (mean age = 24.0 years) performed isometric muscle actions of the leg extensors at 10-100% of their maximal voluntary contraction on two separate occasions. One trial was performed inside a Faraday tent (a flexible Faraday cage made from conductive material), and the other was performed outside the Faraday tent. The EMG signals collected outside the Faraday tent were analyzed three separate ways: as a raw signal, as a bipolar signal, and as a signal digitally notch filtered to remove 60 Hz noise and its harmonics. The signal-to-noise ratios were greatest after notch-filtering (range: 3.0-33.8), and lowest for the bipolar arrangement (1.6-10.2). Linear slope coefficients for the EMG amplitude versus force relationship were also used to compare the methods of noise removal. The results showed that a bipolar arrangement had a significantly lower linear slope coefficient when compared to the three other conditions (raw, notch and tent). These results suggested that an appropriately filtered monopolar EMG signal can be useful in situations that require a large pick-up area. Furthermore, although it is helpful, a Faraday tent (or cage) is not required to achieve an appropriate signal-to-noise ratio, as long as the correct filters are applied.

Comparison of methods for removing electromagnetic noise from electromyographic signals

International Nuclear Information System (INIS)

DeFreitas, Jason M; Beck, Travis W; Stock, Matt S

2012-01-01

The purpose of this investigation was to compare three different methods of removing noise from monopolar electromyographic (EMG) signals: (a) electrical shielding with a Faraday cage, (b) denoising with a digital notch-filter and (c) applying a bipolar differentiation with another monopolar EMG signal. Ten men and ten women (mean age = 24.0 years) performed isometric muscle actions of the leg extensors at 10–100% of their maximal voluntary contraction on two separate occasions. One trial was performed inside a Faraday tent (a flexible Faraday cage made from conductive material), and the other was performed outside the Faraday tent. The EMG signals collected outside the Faraday tent were analyzed three separate ways: as a raw signal, as a bipolar signal, and as a signal digitally notch filtered to remove 60 Hz noise and its harmonics. The signal-to-noise ratios were greatest after notch-filtering (range: 3.0–33.8), and lowest for the bipolar arrangement (1.6–10.2). Linear slope coefficients for the EMG amplitude versus force relationship were also used to compare the methods of noise removal. The results showed that a bipolar arrangement had a significantly lower linear slope coefficient when compared to the three other conditions (raw, notch and tent). These results suggested that an appropriately filtered monopolar EMG signal can be useful in situations that require a large pick-up area. Furthermore, although it is helpful, a Faraday tent (or cage) is not required to achieve an appropriate signal-to-noise ratio, as long as the correct filters are applied. (paper)

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.

Time-frequency peak filtering for random noise attenuation of magnetic resonance sounding signal

Science.gov (United States)

Lin, Tingting; Zhang, Yang; Yi, Xiaofeng; Fan, Tiehu; Wan, Ling

2018-05-01

When measuring in a geomagnetic field, the method of magnetic resonance sounding (MRS) is often limited because of the notably low signal-to-noise ratio (SNR). Most current studies focus on discarding spiky noise and power-line harmonic noise cancellation. However, the effects of random noise should not be underestimated. The common method for random noise attenuation is stacking, but collecting multiple recordings merely to suppress random noise is time-consuming. Moreover, stacking is insufficient to suppress high-level random noise. Here, we propose the use of time-frequency peak filtering for random noise attenuation, which is performed after the traditional de-spiking and power-line harmonic removal method. By encoding the noisy signal with frequency modulation and estimating the instantaneous frequency using the peak of the time-frequency representation of the encoded signal, the desired MRS signal can be acquired from only one stack. The performance of the proposed method is tested on synthetic envelope signals and field data from different surveys. Good estimations of the signal parameters are obtained at different SNRs. Moreover, an attempt to use the proposed method to handle a single recording provides better results compared to 16 stacks. Our results suggest that the number of stacks can be appropriately reduced to shorten the measurement time and improve the measurement efficiency.

Developmental Mechanisms Underlying Improved Contrast Thresholds for Discriminations of Orientation Signals Embedded in Noise

Directory of Open Access Journals (Sweden)

Seong Taek eJeon

2014-09-01

Full Text Available We combined an external noise paradigm with an efficient procedure for obtaining contrast thresholds (Lesmes et al., 2006 in order to model developmental changes during childhood. Specifically, we measured the contrast thresholds of 5-, 7-, 9-year-olds and adults (n = 20/age in a two alternative forced-choice orientation discrimination task over a wide range of external noise levels and at three levels of accuracy. Overall, as age increased, contrast thresholds decreased over the entire range of external noise levels tested. The decrease was greatest between 5 and 7 years of age. The reduction in threshold after age 5 was greater in the high than the low external noise region, a pattern implying greater tolerance to the irrelevant background noise as children became older. To model the mechanisms underlying these developmental changes in terms of internal noise components, we adapted the original perceptual template model (Lu and Dosher, 1998 and normalized the magnitude of performance changes against the performance of 5-year-olds. The resulting model provided an excellent fit (r2 = 0.985 to the contrast thresholds at multiple levels of accuracy (60, 75, and 90% across a wide range of external noise levels. The improvements in contrast thresholds with age were best modelled by a combination of reductions in internal additive noise, reductions in internal multiplicative noise, and improvements in excluding external noise by template retuning. In line with the data, the improvement was greatest between 5 and 7 years of age, accompanied by a 39% reduction in additive noise, 71% reduction in multiplicative noise, and 45% improvement in external noise exclusion. The modelled improvements likely reflect developmental changes at the cortical level, rather than changes in front-end structural properties (Kiorpes et al., 2003.

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.

Yesterday's noise - today's signal

International Nuclear Information System (INIS)

Serdula, K.J.

1978-01-01

Plant performance can be improved by noise analysis. This paper describes noise characteristics, imposed noise and response functions, a case history of cost benefits derived from application of noise analysis techniques, areas for application of noise analysis techniques with special reference to the Gentilly-1 nuclear generating station, and the validity of noise measurement results. (E.C.B.)

Measurement of signal-to-noise ratio performance of TV fluoroscopy systems

International Nuclear Information System (INIS)

Geluk, R.J.

1985-01-01

A method has been developed for direct measurement of Signal-to-Noise ratio performance on X-ray TV systems. To this end the TV signal resulting from a calibrated test object, is compared with the noise level in the image. The method is objective and produces instantaneous readout, which makes it very suitable for system evaluation under dynamic conditions. (author)

Signal-noise separation based on self-similarity testing in 1D-timeseries data

Science.gov (United States)

Bourdin, Philippe A.

2015-08-01

The continuous improvement of the resolution delivered by modern instrumentation is a cost-intensive part of any new space- or ground-based observatory. Typically, scientists later reduce the resolution of the obtained raw-data, for example in the spatial, spectral, or temporal domain, in order to suppress the effects of noise in the measurements. In practice, only simple methods are used that just smear out the noise, instead of trying to remove it, so that the noise can nomore be seen. In high-precision 1D-timeseries data, this usually results in an unwanted quality-loss and corruption of power spectra at selected frequency ranges. Novel methods exist that are based on non-local averaging, which would conserve much of the initial resolution, but these methods are so far focusing on 2D or 3D data. We present here a method specialized for 1D-timeseries, e.g. as obtained by magnetic field measurements from the recently launched MMS satellites. To identify the noise, we use a self-similarity testing and non-local averaging method in order to separate different types of noise and signals, like the instrument noise, non-correlated fluctuations in the signal from heliospheric sources, and correlated fluctuations such as harmonic waves or shock fronts. In power spectra of test data, we are able to restore significant parts of a previously know signal from a noisy measurement. This method also works for high frequencies, where the background noise may have a larger contribution to the spectral power than the signal itself. We offer an easy-to-use software tools set, which enables scientists to use this novel technique on their own noisy data. This allows to use the maximum possible capacity of the instrumental hardware and helps to enhance the quality of the obtained scientific results.

Theory of signal and noise in double-gated nanoscale electronic pH sensors

Energy Technology Data Exchange (ETDEWEB)

Go, Jonghyun; Nair, Pradeep R.; Alam, Muhammad A. [School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana 47907 (United States)

2012-08-01

The maximum sensitivity of classical nanowire (NW)-based pH sensors is defined by the Nernst limit of 59 mV/pH. For typical noise levels in ultra-small single-gated nanowire sensors, the signal-to-noise ratio is often not sufficient to resolve pH changes necessary for a broad range of applications. Recently, a new class of double-gated devices was demonstrated to offer apparent 'super-Nernstian' response (>59 mV/pH) by amplifying the original pH signal through innovative biasing schemes. However, the pH-sensitivity of these nanoscale devices as a function of biasing configurations, number of electrodes, and signal-to-noise ratio (SNR) remains poorly understood. Even the basic question such as 'Do double-gated sensors actually resolve smaller changes in pH compared to conventional single-gated sensors in the presence of various sources of noise?' remains unanswered. In this article, we provide a comprehensive numerical and analytical theory of signal and noise of double-gated pH sensors to conclude that, while the theoretical lower limit of pH-resolution does not improve for double-gated sensors, this new class of sensors does improve the (instrument-limited) pH resolution.

Noise removal in extended depth of field microscope images through nonlinear signal processing.

Science.gov (United States)

Zahreddine, Ramzi N; Cormack, Robert H; Cogswell, Carol J

2013-04-01

Extended depth of field (EDF) microscopy, achieved through computational optics, allows for real-time 3D imaging of live cell dynamics. EDF is achieved through a combination of point spread function engineering and digital image processing. A linear Wiener filter has been conventionally used to deconvolve the image, but it suffers from high frequency noise amplification and processing artifacts. A nonlinear processing scheme is proposed which extends the depth of field while minimizing background noise. The nonlinear filter is generated via a training algorithm and an iterative optimizer. Biological microscope images processed with the nonlinear filter show a significant improvement in image quality and signal-to-noise ratio over the conventional linear filter.

Exponential signaling gain at the receptor level enhances signal-to-noise ratio in bacterial chemotaxis.

Directory of Open Access Journals (Sweden)

Silke Neumann

Full Text Available Cellular signaling systems show astonishing precision in their response to external stimuli despite strong fluctuations in the molecular components that determine pathway activity. To control the effects of noise on signaling most efficiently, living cells employ compensatory mechanisms that reach from simple negative feedback loops to robustly designed signaling architectures. Here, we report on a novel control mechanism that allows living cells to keep precision in their signaling characteristics - stationary pathway output, response amplitude, and relaxation time - in the presence of strong intracellular perturbations. The concept relies on the surprising fact that for systems showing perfect adaptation an exponential signal amplification at the receptor level suffices to eliminate slowly varying multiplicative noise. To show this mechanism at work in living systems, we quantified the response dynamics of the E. coli chemotaxis network after genetically perturbing the information flux between upstream and downstream signaling components. We give strong evidence that this signaling system results in dynamic invariance of the activated response regulator against multiplicative intracellular noise. We further demonstrate that for environmental conditions, for which precision in chemosensing is crucial, the invariant response behavior results in highest chemotactic efficiency. Our results resolve several puzzling features of the chemotaxis pathway that are widely conserved across prokaryotes but so far could not be attributed any functional role.

Benchmarking the Algorithms to Detect Seasonal Signals Under Different Noise Conditions

Science.gov (United States)

Klos, A.; Bogusz, J.; Bos, M. S.

2017-12-01

Global Positioning System (GPS) position time series contain seasonal signals. Among the others, annual and semi-annual are the most powerful. Widely, these oscillations are modelled as curves with constant amplitudes, using the Weighted Least-Squares (WLS) algorithm. However, in reality, the seasonal signatures vary over time, as their geophysical causes are not constant. Different algorithms have been already used to cover this time-variability, as Wavelet Decomposition (WD), Singular Spectrum Analysis (SSA), Chebyshev Polynomial (CP) or Kalman Filter (KF). In this research, we employed 376 globally distributed GPS stations which time series contributed to the newest International Terrestrial Reference Frame (ITRF2014). We show that for c.a. 20% of stations the amplitudes of seasonal signal varies over time of more than 1.0 mm. Then, we compare the WD, SSA, CP and KF algorithms for a set of synthetic time series to quantify them under different noise conditions. We show that when variations of seasonal signals are ignored, the power-law character is biased towards flicker noise. The most reliable estimates of the variations were found to be given by SSA and KF. These methods also perform the best for other noise levels while WD, and to a lesser extend also CP, have trouble in separating the seasonal signal from the noise which leads to an underestimation in the spectral index of power-law noise of around 0.1. For real ITRF2014 GPS data we discovered, that SSA and KF are capable to model 49-84% and 77-90% of the variance of the true varying seasonal signals, respectively.

Traffic background level and signal duration effects on aircraft noise judgment

Energy Technology Data Exchange (ETDEWEB)

Johnston, G W; Haasz, A A

1977-04-22

The effects of background traffic noise level and signal duration on perceived aircraft noise levels during a flyover event are investigated. Tapes of traffic noise at different levels on which aircraft flyover noise events of different durations were superimposed were played to groups of observers in a room simulating indoor conditions. It is found that the presence of steady background traffic noise reduces the perceived noisiness of aircraft flyovers provided that the duration of the flyover event is sufficiently short in relation to flyover time. For a given event level, a reduction of 21 dB(A) in background noise level leads to the perception of a 5.5 dB(A) increase in peak event level. Regressions of observer response with the noise pollution index show a lower correlation than those with variables based on background noise level and peak signal level, although the data are found to exhibit a number of significant trends associated with noise pollution index variations.

Combination of highly nonlinear fiber, an optical bandpass filter, and a Fabry-Perot filter to improve the signal-to-noise ratio of a supercontinuum continuous-wave optical source.

Science.gov (United States)

Nan, Yinbo; Huo, Li; Lou, Caiyun

2005-05-20

We present a theoretical study of a supercontinuum (SC) continuous-wave (cw) optical source generation in highly nonlinear fiber and its noise properties through numerical simulations based on the nonlinear Schrödinger equation. Fluctuations of pump pulses generate substructures between the longitudinal modes that result in the generation of white noise and then in degradation of coherence and in a decrease of the modulation depths and the signal-to-noise ratio (SNR). A scheme for improvement of the SNR of a multiwavelength cw optical source based on a SC by use of the combination of a highly nonlinear fiber (HNLF), an optical bandpass filter, and a Fabry-Perot (FP) filter is presented. Numerical simulations show that the improvement in modulation depth is relative to the HNLF's length, the 3-dB bandwidth of the optical bandpass filter, and the reflection ratio of the FP filter and that the average improvement in modulation depth is 13.7 dB under specified conditions.

Using hyperentanglement to enhance resolution, signal-to-noise ratio, and measurement time

Science.gov (United States)

Smith, James F.

2017-03-01

A hyperentanglement-based atmospheric imaging/detection system involving only a signal and an ancilla photon will be considered for optical and infrared frequencies. Only the signal photon will propagate in the atmosphere and its loss will be classical. The ancilla photon will remain within the sensor experiencing low loss. Closed form expressions for the wave function, normalization, density operator, reduced density operator, symmetrized logarithmic derivative, quantum Fisher information, quantum Cramer-Rao lower bound, coincidence probabilities, probability of detection, probability of false alarm, probability of error after M measurements, signal-to-noise ratio, quantum Chernoff bound, time-on-target expressions related to probability of error, and resolution will be provided. The effect of noise in every mode will be included as well as loss. The system will provide the basic design for an imaging/detection system functioning at optical or infrared frequencies that offers better than classical angular and range resolution. Optimization for enhanced resolution will be included. The signal-to-noise ratio will be increased by a factor equal to the number of modes employed during the hyperentanglement process. Likewise, the measurement time can be reduced by the same factor. The hyperentanglement generator will typically make use of entanglement in polarization, energy-time, orbital angular momentum and so on. Mathematical results will be provided describing the system's performance as a function of loss mechanisms and noise.

Fractal characterization for noise signal validation in power reactors

International Nuclear Information System (INIS)

Aguilar Martinez, Omar

2003-01-01

Up to now, a great variety of methods is used for the dynamical characterization of different components of Nuclear Power Plants (NPPs). With this aim, time and spectral analysis are usually considered, and different tools of non-stationary and non-gaussian analysis are also presented. When applying non-lineal dynamics theory for noise signal validation purposes in power reactors, the extraction of fractal echoes plays a main role. Fractal characterization for noise signal validation purposes can be integrated to the task of processing and acquisition of time signals in noise (fluctuation parameters) analysis systems. The possibility of discrimination between deterministic chaotic signals and pure noise signals has been incorporated, as a complement; to noise signals analysis in normal and anomalous operational conditions in NPPs using a fractal approach. In this work the detailed analysis of a neutronic sensor response is considered and the fractal characterization of its dynamics state (i.e. sensor line) for noise signal classification, it is presented. The experiment from where the time series (signals) were obtained, was carried out at the Research Reactor of the Technical University of Budapest, Hungary, during a model experiment for ageing process study of in-core neutron detectors (author)

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.

Voltage fluctuations in neurons: signal or noise?

DEFF Research Database (Denmark)

Yarom, Yosef; Hounsgaard, Jorn

2011-01-01

, we discuss noise-free neuronal signaling and detrimental and beneficial forms of noise in large-scale functional neural networks. Evidence that noise and variability in some cases go hand in hand with behavioral variability and increase behavioral choice, richness, and adaptability opens new avenues......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...... that allows and facilitates complex adaptive behavior in an unpredictable world. Here we review the growing experimental evidence that functional network activity is associated with intense fluctuations in membrane potential and spike timing. We trace origins and consequences of noise and variability. Finally...

Radiometric and signal-to-noise ratio properties of multiplex dispersive spectrometry

International Nuclear Information System (INIS)

Barducci, Alessandro; Guzzi, Donatella; Lastri, Cinzia; Nardino, Vanni; Marcoionni, Paolo; Pippi, Ivan

2010-01-01

Recent theoretical investigations have shown important radiometric disadvantages of interferential multiplexing in Fourier transform spectrometry that apparently can be applied even to coded aperture spectrometers. We have reexamined the methods of noninterferential multiplexing in order to assess their signal-to-noise ratio (SNR) performance, relying on a theoretical modeling of the multiplexed signals. We are able to show that quite similar SNR and radiometric disadvantages affect multiplex dispersive spectrometry. The effect of noise on spectral estimations is discussed.

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.

Study on the ratio of signal to noise for single photon resolution time spectrometer

International Nuclear Information System (INIS)

Wang Zhaomin; Huang Shengli; Xu Zizong; Wu Chong

2001-01-01

The ratio of signal to noise for single photon resolution time spectrometer and their influence factors were studied. A method to depress the background, to shorten the measurement time and to increase the ratio of signal to noise was discussed. Results show that ratio of signal to noise is proportional to solid angle of detector to source and detection efficiency, and inverse proportional to electronics noise. Choose the activity of the source was important for decreasing of random coincidence counting. To use a coincidence gate and a discriminator of single photon were an effective way of increasing measurement accuracy and detection efficiency

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

Variability of signal-to-noise ratio and the network analysis of gravitational wave burst signals

International Nuclear Information System (INIS)

Mohanty, S D; Rakhmanov, M; Klimenko, S; Mitselmakher, G

2006-01-01

The detection and estimation of gravitational wave burst signals, with a priori unknown polarization waveforms, requires the use of data from a network of detectors. Maximizing the network likelihood functional over all waveforms and sky positions yields point estimates for them as well as a detection statistic. However, the transformation from the data to estimates can become ill-conditioned over parts of the sky, resulting in significant errors in estimation. We modify the likelihood procedure by introducing a penalty functional which suppresses candidate solutions that display large signal-to-noise ratio (SNR) variability as the source is displaced on the sky. Simulations show that the resulting network analysis method performs significantly better in estimating the sky position of a source. Further, this method can be applied to any network, irrespective of the number or mutual alignment of detectors

Signal Detection with Criterion Noise: Applications to Recognition Memory

Science.gov (United States)

Benjamin, Aaron S.; Diaz, Michael; Wee, Serena

2009-01-01

A tacit but fundamental assumption of the theory of signal detection is that criterion placement is a noise-free process. This article challenges that assumption on theoretical and empirical grounds and presents the noisy decision theory of signal detection (ND-TSD). Generalized equations for the isosensitivity function and for measures of…

Improving signal to noise in labeled biological specimens using energy-filtered TEM of sections with a drift correction strategy and a direct detection device.

Science.gov (United States)

Ramachandra, Ranjan; Bouwer, James C; Mackey, Mason R; Bushong, Eric; Peltier, Steven T; Xuong, Nguyen-Huu; Ellisman, Mark H

2014-06-01

Energy filtered transmission electron microscopy techniques are regularly used to build elemental maps of spatially distributed nanoparticles in materials and biological specimens. When working with thick biological sections, electron energy loss spectroscopy techniques involving core-loss electrons often require exposures exceeding several minutes to provide sufficient signal to noise. Image quality with these long exposures is often compromised by specimen drift, which results in blurring and reduced resolution. To mitigate drift artifacts, a series of short exposure images can be acquired, aligned, and merged to form a single image. For samples where the target elements have extremely low signal yields, the use of charge coupled device (CCD)-based detectors for this purpose can be problematic. At short acquisition times, the images produced by CCDs can be noisy and may contain fixed pattern artifacts that impact subsequent correlative alignment. Here we report on the use of direct electron detection devices (DDD's) to increase the signal to noise as compared with CCD's. A 3× improvement in signal is reported with a DDD versus a comparably formatted CCD, with equivalent dose on each detector. With the fast rolling-readout design of the DDD, the duty cycle provides a major benefit, as there is no dead time between successive frames.

Approximations to camera sensor noise

Science.gov (United States)

Jin, Xiaodan; Hirakawa, Keigo

2013-02-01

Noise is present in all image sensor data. Poisson distribution is said to model the stochastic nature of the photon arrival process, while it is common to approximate readout/thermal noise by additive white Gaussian noise (AWGN). Other sources of signal-dependent noise such as Fano and quantization also contribute to the overall noise profile. Question remains, however, about how best to model the combined sensor noise. Though additive Gaussian noise with signal-dependent noise variance (SD-AWGN) and Poisson corruption are two widely used models to approximate the actual sensor noise distribution, the justification given to these types of models are based on limited evidence. The goal of this paper is to provide a more comprehensive characterization of random noise. We concluded by presenting concrete evidence that Poisson model is a better approximation to real camera model than SD-AWGN. We suggest further modification to Poisson that may improve the noise model.

Feasibility of Johnson Noise Thermometry based on Digital Signal Processing Techniques

International Nuclear Information System (INIS)

Hwang, In Koo; Kim, Yang Mo

2014-01-01

This paper presents an implementation strategy of noise thermometry based on a digital signal processing technique and demonstrates its feasibilities. A key factor in its development is how to extract the small thermal noise signal from other noises, for example, random noise from amplifiers and continuous electromagnetic interference from the environment. The proposed system consists of two identical amplifiers and uses a cross correlation function to cancel the random noise of the amplifiers. Then, the external interference noises are eliminated by discriminating the difference in the peaks between the thermal signal and external noise. The gain of the amplifiers is estimated by injecting an already known pilot signal. The experimental simulation results of signal processing methods have demonstrated that the proposed approach is an effective method in eliminating an external noise signal and performing gain correction for development of the thermometry

a Universal De-Noising Algorithm for Ground-Based LIDAR Signal

Science.gov (United States)

Ma, Xin; Xiang, Chengzhi; Gong, Wei

2016-06-01

Ground-based lidar, working as an effective remote sensing tool, plays an irreplaceable role in the study of atmosphere, since it has the ability to provide the atmospheric vertical profile. However, the appearance of noise in a lidar signal is unavoidable, which leads to difficulties and complexities when searching for more information. Every de-noising method has its own characteristic but with a certain limitation, since the lidar signal will vary with the atmosphere changes. In this paper, a universal de-noising algorithm is proposed to enhance the SNR of a ground-based lidar signal, which is based on signal segmentation and reconstruction. The signal segmentation serving as the keystone of the algorithm, segments the lidar signal into three different parts, which are processed by different de-noising method according to their own characteristics. The signal reconstruction is a relatively simple procedure that is to splice the signal sections end to end. Finally, a series of simulation signal tests and real dual field-of-view lidar signal shows the feasibility of the universal de-noising algorithm.

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.

Detecting modulated signals in modulated noise: (II) neural thresholds in the songbird forebrain.

Science.gov (United States)

Bee, Mark A; Buschermöhle, Michael; Klump, Georg M

2007-10-01

Sounds in the real world fluctuate in amplitude. The vertebrate auditory system exploits patterns of amplitude fluctuations to improve signal detection in noise. One experimental paradigm demonstrating these general effects has been used in psychophysical studies of 'comodulation detection difference' (CDD). The CDD effect refers to the fact that thresholds for detecting a modulated, narrowband noise signal are lower when the envelopes of flanking bands of modulated noise are comodulated with each other, but fluctuate independently of the signal compared with conditions in which the envelopes of the signal and flanking bands are all comodulated. Here, we report results from a study of the neural correlates of CDD in European starlings (Sturnus vulgaris). We manipulated: (i) the envelope correlations between a narrowband noise signal and a masker comprised of six flanking bands of noise; (ii) the signal onset delay relative to masker onset; (iii) signal duration; and (iv) masker spectrum level. Masked detection thresholds were determined from neural responses using signal detection theory. Across conditions, the magnitude of neural CDD ranged between 2 and 8 dB, which is similar to that reported in a companion psychophysical study of starlings [U. Langemann & G.M. Klump (2007) Eur. J. Neurosci., 26, 1969-1978]. We found little evidence to suggest that neural CDD resulted from the across-channel processing of auditory grouping cues related to common envelope fluctuations and synchronous onsets between the signal and flanking bands. We discuss a within-channel model of peripheral processing that explains many of our results.

Improved CEEMDAN-wavelet transform de-noising method and its application in well logging noise reduction

Science.gov (United States)

Zhang, Jingxia; Guo, Yinghai; Shen, Yulin; Zhao, Difei; Li, Mi

2018-06-01

The use of geophysical logging data to identify lithology is an important groundwork in logging interpretation. Inevitably, noise is mixed in during data collection due to the equipment and other external factors and this will affect the further lithological identification and other logging interpretation. Therefore, to get a more accurate lithological identification it is necessary to adopt de-noising methods. In this study, a new de-noising method, namely improved complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN)-wavelet transform, is proposed, which integrates the superiorities of improved CEEMDAN and wavelet transform. Improved CEEMDAN, an effective self-adaptive multi-scale analysis method, is used to decompose non-stationary signals as the logging data to obtain the intrinsic mode function (IMF) of N different scales and one residual. Moreover, one self-adaptive scale selection method is used to determine the reconstruction scale k. Simultaneously, given the possible frequency aliasing problem between adjacent IMFs, a wavelet transform threshold de-noising method is used to reduce the noise of the (k-1)th IMF. Subsequently, the de-noised logging data are reconstructed by the de-noised (k-1)th IMF and the remaining low-frequency IMFs and the residual. Finally, empirical mode decomposition, improved CEEMDAN, wavelet transform and the proposed method are applied for analysis of the simulation and the actual data. Results show diverse performance of these de-noising methods with regard to accuracy for lithological identification. Compared with the other methods, the proposed method has the best self-adaptability and accuracy in lithological identification.

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

A high signal-to-noise ratio composite quasar spectrum

International Nuclear Information System (INIS)

Francis, P.J.; Hewett, P.C.; Foltz, C.B.; Chaffee, F.H.; Weymann, R.J.

1991-01-01

A very high signal-to-noise ratio (S/N of about 400) composite spectrum of the rest-frame ultraviolet and optical region of high luminosity quasars is presented. The spectrum is derived from 718 individual spectra obtained as part of the Large Bright Quasar Survey. The moderate resolution, 4A or less, and high signal-to-noise ratio allow numerous weak emission features to be identified. Of particular note is the large equivalent-width of the Fe II emission in the rest-frame ultraviolet and the blue continuum slope of the composite. The primary aim of this paper is to provide a reference spectrum for use in line identifications, and a series of large-scale representations of the composite spectrum are shown. A measure of the standard deviation of the individual quasar spectra from the composite spectrum is also presented. 12 refs

Semi-automated identification of artefact and noise signals in MEG sensors

International Nuclear Information System (INIS)

Rettich, E.

2006-09-01

Magnetic encephalography (MEG) is a noninvasive method of measuring cerebral activity. It is based on the registration of magnetic fields that are induced by synaptic ion currents as the brain processes information. These magnetic fields are of a very small magnitude, ranging from a few femto Tesla (1 fT = 10 15 T) to several thousand fT (1 pT). This is equivalent to a ten thousandth to a billionth of the Earth's magnetic field. When applied with a time resolution in the range of milliseconds this technique permits research on time-critical neurophysiological processes. A meaningful analysis of MEG data presupposes that signals have been measured at low noise levels. This in turn requires magnetic shielding, normally in the form of a shielded cabin, and low-noise detectors. Data input from high-noise channels impairs the result of the measurement, possibly rendering it useless. To prevent this it is necessary to identify high-noise channels and remove them from the measurement data. At Juelich Research Center, like at most MEG laboratories, this is done by visual inspection. However, being dependent on the individual observer, this method does not yield objective results. Furthermore, visual inspection presupposes a high degree of experience and is time-consuming. This situation could be significantly improved by automated identification of high-noise channels. The purpose of the present study was to develop an algorithm that analyses measurement signals in a given time and frequency interval on the basis of statistical traits. Using a suitably designed user interface this permits searching MEG data for high-noise channel data below or above statistical threshold values on the basis of predetermined decision criteria. The identified high-noise channels are then output in a selection list, and the measurement data and results of the statistical analysis are displayed. This information enables the user to make changes and decide which high-noise channels to extract

Empirical mode decomposition of the ECG signal for noise removal

Science.gov (United States)

Khan, Jesmin; Bhuiyan, Sharif; Murphy, Gregory; Alam, Mohammad

2011-04-01

Electrocardiography is a diagnostic procedure for the detection and diagnosis of heart abnormalities. The electrocardiogram (ECG) signal contains important information that is utilized by physicians for the diagnosis and analysis of heart diseases. So good quality ECG signal plays a vital role for the interpretation and identification of pathological, anatomical and physiological aspects of the whole cardiac muscle. However, the ECG signals are corrupted by noise which severely limit the utility of the recorded ECG signal for medical evaluation. The most common noise presents in the ECG signal is the high frequency noise caused by the forces acting on the electrodes. In this paper, we propose a new ECG denoising method based on the empirical mode decomposition (EMD). The proposed method is able to enhance the ECG signal upon removing the noise with minimum signal distortion. Simulation is done on the MIT-BIH database to verify the efficacy of the proposed algorithm. Experiments show that the presented method offers very good results to remove noise from the ECG signal.

Kernel-based noise filtering of neutron detector signals

International Nuclear Information System (INIS)

Park, Moon Ghu; Shin, Ho Cheol; Lee, Eun Ki

2007-01-01

This paper describes recently developed techniques for effective filtering of neutron detector signal noise. In this paper, three kinds of noise filters are proposed and their performance is demonstrated for the estimation of reactivity. The tested filters are based on the unilateral kernel filter, unilateral kernel filter with adaptive bandwidth and bilateral filter to show their effectiveness in edge preservation. Filtering performance is compared with conventional low-pass and wavelet filters. The bilateral filter shows a remarkable improvement compared with unilateral kernel and wavelet filters. The effectiveness and simplicity of the unilateral kernel filter with adaptive bandwidth is also demonstrated by applying it to the reactivity measurement performed during reactor start-up physics tests

Phase noise mitigation of QPSK signal utilizing phase-locked multiplexing of signal harmonics and amplitude saturation.

Science.gov (United States)

Mohajerin-Ariaei, Amirhossein; Ziyadi, Morteza; Chitgarha, Mohammad Reza; Almaiman, Ahmed; Cao, Yinwen; Shamee, Bishara; Yang, Jeng-Yuan; Akasaka, Youichi; Sekiya, Motoyoshi; Takasaka, Shigehiro; Sugizaki, Ryuichi; Touch, Joseph D; Tur, Moshe; Langrock, Carsten; Fejer, Martin M; Willner, Alan E

2015-07-15

We demonstrate an all-optical phase noise mitigation scheme based on the generation, delay, and coherent summation of higher order signal harmonics. The signal, its third-order harmonic, and their corresponding delayed variant conjugates create a staircase phase-transfer function that quantizes the phase of quadrature-phase-shift-keying (QPSK) signal to mitigate phase noise. The signal and the harmonics are automatically phase-locked multiplexed, avoiding the need for phase-based feedback loop and injection locking to maintain coherency. The residual phase noise converts to amplitude noise in the quantizer stage, which is suppressed by parametric amplification in the saturation regime. Phase noise reduction of ∼40% and OSNR-gain of ∼3  dB at BER 10(-3) are experimentally demonstrated for 20- and 30-Gbaud QPSK input signals.

Signal-to-noise based local decorrelation compensation for speckle interferometry applications

International Nuclear Information System (INIS)

Molimard, Jerome; Cordero, Raul; Vautrin, Alain

2008-01-01

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

Flow measurements using noise signals of axially displaced thermocouples

Energy Technology Data Exchange (ETDEWEB)

Kozma, R.; Hoogenboom, J.E. (Interuniversitair Reactor Inst., Delft (Netherlands))

1990-01-01

Determination of the flow rate of the coolant in the cooling channels of nuclear reactors is an important aspect of core monitoring. It is usually impossible to measure the flow by flowmeters in the individual channels due to the lack of space and safety reasons. An alternative method is based on the analysis of noise signals of the available in-core detectors. In such a noise method, a transit time which characterises the propagation of thermohydraulic fluctuations (density or temperature fluctuations) in the coolant is determined from the correlation between the noise signals of axially displaced detectors. In this paper, the results of flow measurements using axially displaced thermocouples in the channel wall will be presented. The experiments have been performed in a simulated MRT-type fuel assembly located in the research reactor HOR of the Interfaculty Reactor Institute, Delft. It was found that the velocities obtained via temperature noise correlation methods are significantly larger than the area-averaged velocity in the single-phase coolant flow. Model calculations show that the observed phenomenon can be explained by effects due to the radial velocity distribution in the channel. (author).

Statistical Angles on the Lattice QCD Signal-to-Noise Problem

Science.gov (United States)

Wagman, Michael L.

The theory of quantum chromodynamics (QCD) encodes the strong interactions that bind quarks and gluons into nucleons and that bind nucleons into nuclei. Predictive control of QCD would allow nuclear structure and reactions as well as properties of supernovae and neutron stars to be theoretically studied from first principles. Lattice QCD (LQCD) can represent generic QCD predictions in terms of well-defined path integrals, but the sign and signal-to-noise problems have obstructed LQCD calculations of large nuclei and nuclear matter in practice. This thesis presents a statistical study of LQCD correlation functions, with a particular focus on characterizing the structure of the noise associated with quantum fluctuations. The signal-to-noise problem in baryon correlation functions is demonstrated to arise from a sign problem associated with Monte Carlo sampling of complex correlation functions. Properties of circular statistics are used to understand the emergence of a large time noise region where standard energy measurements are unreliable. Power-law tails associated with stable distributions and Levy flights are found to play a central role in the time evolution of baryon correlation functions. Building on these observations, a new statistical analysis technique called phase reweighting is introduced that allow energy levels to be extracted from large-time correlation functions with time-independent signal-to-noise ratios. Phase reweighting effectively includes dynamical refinement of source magnitudes but introduces a bias associated with the phase. This bias can be removed by performing an extrapolation, but at the expense of re-introducing a signal-to-noise problem. Lattice QCD calculations of the ρ+ and nucleon masses and of the ΞΞ(1S0) binding energy show consistency between standard results obtained using smaller-time correlation functions and phase-reweighted results using large-time correlation functions inaccessible to standard statistical analysis

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.

A study on the method for cancelling the background noise of the impact signal

International Nuclear Information System (INIS)

Kim, J. S.; Ham, C. S.; Park, J. H.

1998-01-01

In this paper, we compared the noise canceller (time domain analysis method) to the spectral subtraction (frequency domain analysis method) for cancelling background noise when the Loose Part Monitoring System's accelerometers combined the noise signal with the impact signal if the impact signal exists. In the operation of a nuclear power plant monitoring, alarm triggering occurs due to a peak signal in the background noise, an amplitude increase by component operation such as control rod movement or abrupt pump operation. This operation causes the background noise in LPMS. Thus this noise inputs to LPMS together with the impact signal. In case that this noise amplitude is very large comparing to that of the impact signal, we may not analyze the impact position and mass estimation. We analyzed two methods for cancelling background noise. First, we evaluate the signal to noise ratio utilizing the noise canceller. Second, we evaluate the signal to noise ratio utilizing the spectral subtraction. The evaluation resulted superior the noise canceller to the spectral subtraction on the signal to noise ratio

High signal to noise ratio THz spectroscopy with ASOPS and signal processing schemes for mapping and controlling molecular and bulk relaxation processes

International Nuclear Information System (INIS)

Hadjiloucas, S; Walker, G C; Bowen, J W; Becerra, V M; Zafiropoulos, A; Galvao, R K H

2009-01-01

Asynchronous Optical Sampling has the potential to improve signal to noise ratio in THz transient sperctrometry. The design of an inexpensive control scheme for synchronising two femtosecond pulse frequency comb generators at an offset frequency of 20 kHz is discussed. The suitability of a range of signal processing schemes adopted from the Systems Identification and Control Theory community for further processing recorded THz transients in the time and frequency domain are outlined. Finally, possibilities for femtosecond pulse shaping using genetic algorithms are mentioned.

High signal to noise ratio THz spectroscopy with ASOPS and signal processing schemes for mapping and controlling molecular and bulk relaxation processes

Energy Technology Data Exchange (ETDEWEB)

Hadjiloucas, S; Walker, G C; Bowen, J W; Becerra, V M [Cybernetics, School of Systems Engineering, University of Reading, RG6 6AY (United Kingdom); Zafiropoulos, A [Biosystems Engineering Department, School of Agricultural Technology, Technological Educational Institute of Larissa, 411 10, Larissa (Greece); Galvao, R K H, E-mail: s.hadjiloucas@reading.ac.u [Divisao de Engenharia Eletronica, Instituto Tecnologico de Aeronautica, Sao Jose dos Campos, SP, 12228-900 Brazil (Brazil)

2009-08-01

Asynchronous Optical Sampling has the potential to improve signal to noise ratio in THz transient sperctrometry. The design of an inexpensive control scheme for synchronising two femtosecond pulse frequency comb generators at an offset frequency of 20 kHz is discussed. The suitability of a range of signal processing schemes adopted from the Systems Identification and Control Theory community for further processing recorded THz transients in the time and frequency domain are outlined. Finally, possibilities for femtosecond pulse shaping using genetic algorithms are mentioned.

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.

Electrocardiogram signal denoising based on a new improved wavelet thresholding

Science.gov (United States)

Han, Guoqiang; Xu, Zhijun

2016-08-01

Good quality electrocardiogram (ECG) is utilized by physicians for the interpretation and identification of physiological and pathological phenomena. In general, ECG signals may mix various noises such as baseline wander, power line interference, and electromagnetic interference in gathering and recording process. As ECG signals are non-stationary physiological signals, wavelet transform is investigated to be an effective tool to discard noises from corrupted signals. A new compromising threshold function called sigmoid function-based thresholding scheme is adopted in processing ECG signals. Compared with other methods such as hard/soft thresholding or other existing thresholding functions, the new algorithm has many advantages in the noise reduction of ECG signals. It perfectly overcomes the discontinuity at ±T of hard thresholding and reduces the fixed deviation of soft thresholding. The improved wavelet thresholding denoising can be proved to be more efficient than existing algorithms in ECG signal denoising. The signal to noise ratio, mean square error, and percent root mean square difference are calculated to verify the denoising performance as quantitative tools. The experimental results reveal that the waves including P, Q, R, and S waves of ECG signals after denoising coincide with the original ECG signals by employing the new proposed method.

Increasing signal-to-noise ratio of swept-source optical coherence tomography by oversampling in k-space

Science.gov (United States)

Nagib, Karim; Mezgebo, Biniyam; Thakur, Rahul; Fernando, Namal; Kordi, Behzad; Sherif, Sherif

2018-03-01

Optical coherence tomography systems suffer from noise that could reduce ability to interpret reconstructed images correctly. We describe a method to increase the signal-to-noise ratio of swept-source optical coherence tomography (SSOCT) using oversampling in k-space. Due to this oversampling, information redundancy would be introduced in the measured interferogram that could be used to reduce white noise in the reconstructed A-scan. We applied our novel scaled nonuniform discrete Fourier transform to oversampled SS-OCT interferograms to reconstruct images of a salamander egg. The peak-signal-to-noise (PSNR) between the reconstructed images using interferograms sampled at 250MS/s andz50MS/s demonstrate that this oversampling increased the signal-to-noise ratio by 25.22 dB.

Signal-to-noise ratio of bilateral nonimaging transcranial Doppler recordings of the middle cerebral artery is not affected by age and sex.

Science.gov (United States)

Katsogridakis, Emmanuel; Dineen, Nicky E; Brodie, Fiona G; Robinson, Thompson G; Panerai, Ronney B

2011-04-01

Differences between transcranial Doppler ultrasonography (TCD) recordings of symmetrical vessels can show true physiologic differences, but can also be caused by measurement error and other sources of noise. The aim of this project was to assess the influence of noise on estimates of dynamic cerebral autoregulation (dCA), and of age, sex and breathing manoeuvres on the signal-to-noise ratio (SNR). Cerebral blood flow (CBF) was monitored in 30 young (60 years) during baseline conditions, breath-holding and hyperventilation. Noise was defined as the difference between beat-to-beat values of the two mean CBF velocity (CBFV) signals. Magnitude squared coherence estimates of noise vs. ABP and ABP vs. CBFV were obtained and averaged. A similar approach was adopted for the CBFV step response. The effect of age and breathing manoeuvre on the SNR was assessed using a two-way analysis of variance (ANOVA), whilst the effect of sex was investigated using a Student's t test. No significant differences were observed in SNR (baseline 6.07 ± 3.07 dB and 7.33 ± 3.84 dB, breath-hold: 13.53 ± 3.93 dB and 14.64 ± 4.52 dB, and hyperventilation: 14.69 ± 4.04 dB and 14.84 ± 4.05 dB) estimates between young and old groups, respectively. The use of breathing manoeuvres significantly improved the SNR (p < 10(-4)) without a significant difference between manoeuvres. Sex does not appear to have an effect on SNR (p = 0.365). Coherence estimates were not influenced by the SNR, but significant differences were found in the amplitude of the CBFV step response. Copyright © 2011 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Elimination of noise peak for signal processing in Johnson noise thermometry development

International Nuclear Information System (INIS)

Hwang, I. G.; Moon, B. S.; Jeong, J. E.; Jeo, Y. H.; Kisner, Roger A.

2003-01-01

The internal and external noise is the most considering obstacle in development of Johnson Noise Thermometry system. This paper addresses an external noise elimination issue of the Johnson Noise Thermometry system which is underway of development in collaboration between KAERI and ORNL. Although internal random noise is canceled by Cross Power Spectral Density function, a continuous wave penetrating into the electronic circuit is eliminated by the difference of peaks between Johnson signal and external noise. The elimination logic using standard deviation of CPSD and energy leakage problem in discrete CPSD function are discussed in this paper

Diversity combining in laser Doppler vibrometry for improved signal reliability

International Nuclear Information System (INIS)

Dräbenstedt, Alexander

2014-01-01

Because of the speckle nature of the light reflected from rough surfaces the signal quality of a vibrometer suffers from varying signal power. Deep signal outages manifest themselves as noise bursts and spikes in the demodulated velocity signal. Here we show that the signal quality of a single point vibrometer can be substantially improved by diversity reception. This concept is widely used in RF communication and can be transferred into optical interferometry. When two statistically independent measurement channels are available which measure the same motion on the same spot, the probability for both channels to see a signal drop-out at the same time is very low. We built a prototype instrument that uses polarization diversity to constitute two independent reception channels that are separately demodulated into velocity signals. Send and receive beams go through different parts of the aperture so that the beams can be spatially separated. The two velocity channels are mixed into one more reliable signal by a PC program in real time with the help of the signal power information. An algorithm has been developed that ensures a mixing of two or more channels with minimum resulting variance. The combination algorithm delivers also an equivalent signal power for the combined signal. The combined signal lacks the vast majority of spikes that are present in the raw signals and it extracts the true vibration information present in both channels. A statistical analysis shows that the probability for deep signal outages is largely decreased. A 60 fold improvement can be shown. The reduction of spikes and noise bursts reduces the noise in the spectral analysis of vibrations too. Over certain frequency bands a reduction of the noise density by a factor above 10 can be shown

Sensitivity of PPI analysis to differences in noise reduction strategies.

Science.gov (United States)

Barton, M; Marecek, R; Rektor, I; Filip, P; Janousova, E; Mikl, M

2015-09-30

In some fields of fMRI data analysis, using correct methods for dealing with noise is crucial for achieving meaningful results. This paper provides a quantitative assessment of the effects of different preprocessing and noise filtering strategies on psychophysiological interactions (PPI) methods for analyzing fMRI data where noise management has not yet been established. Both real and simulated fMRI data were used to assess these effects. Four regions of interest (ROIs) were chosen for the PPI analysis on the basis of their engagement during two tasks. PPI analysis was performed for 32 different preprocessing and analysis settings, which included data filtering with RETROICOR or no such filtering; different filtering of the ROI "seed" signal with a nuisance data-driven time series; and the involvement of these data-driven time series in the subsequent PPI GLM analysis. The extent of the statistically significant results was quantified at the group level using simple descriptive statistics. Simulated data were generated to assess statistical improvement of different filtering strategies. We observed that different approaches for dealing with noise in PPI analysis yield differing results in real data. In simulated data, we found RETROICOR, seed signal filtering and the addition of data-driven covariates to the PPI design matrix significantly improves results. We recommend the use of RETROICOR, and data-driven filtering of the whole data, or alternatively, seed signal filtering with data-driven signals and the addition of data-driven covariates to the PPI design matrix. Copyright © 2015 Elsevier B.V. All rights reserved.

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

DEFF Research Database (Denmark)

Bak, J.; Clausen, Sønnik

1999-01-01

in emission and transmission spectrometry, an investigation of the SNR in CO gas spectra as a function of spectral resolution has been carried out. We present a method to (1) determine experimentally the SNR at constant throughput, (2) determine the SNR on the basis of measured noise levels and Hitran......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...... simulated signals, and (3) determine the SNR of CO from high to low spectral resolutions related to the molecular linewidth and vibrational-rotational lines spacing. In addition, SNR values representing different spectral resolutions but scaled to equal measurement times were compared. It was found...

Performance Improvement of Raman Distributed Temperature System by Using Noise Suppression

Science.gov (United States)

Li, Jian; Li, Yunting; Zhang, Mingjiang; Liu, Yi; Zhang, Jianzhong; Yan, Baoqiang; Wang, Dong; Jin, Baoquan

2018-06-01

In Raman distributed temperature system, the key factor for performance improvement is noise suppression, which seriously affects the sensing distance and temperature accuracy. Therefore, we propose and experimentally demonstrate dynamic noise difference algorithm and wavelet transform modulus maximum (WTMM) to de-noising Raman anti-Stokes signal. Experimental results show that the sensing distance can increase from 3 km to 11.5 km and the temperature accuracy increases to 1.58 °C at the sensing distance of 10.4 km.

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.

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.

The dependence of signal-to-noise ratio on number of scans in covariance spectroscopy.

Science.gov (United States)

Qian, Yi; Shen, Ming; Amoureux, Jean-Paul; Noda, Isao; Hu, Bingwen

2014-01-01

The dependence of signal-to-noise ratio on the number of scans in covariance spectroscopy has been systematically analyzed for the first time with the intriguing relationship of SNRcov∝n/2, which is different from that in FT2D spectrum with SNRFT∝n. This relationship guarantees the signal-to-noise ratio when increasing the number of scans. Copyright © 2014 Elsevier Inc. All rights reserved.

Techniques and software tools for estimating ultrasonic signal-to-noise ratios

Science.gov (United States)

Chiou, Chien-Ping; Margetan, Frank J.; McKillip, Matthew; Engle, Brady J.; Roberts, Ronald A.

2016-02-01

At Iowa State University's Center for Nondestructive Evaluation (ISU CNDE), the use of models to simulate ultrasonic inspections has played a key role in R&D efforts for over 30 years. To this end a series of wave propagation models, flaw response models, and microstructural backscatter models have been developed to address inspection problems of interest. One use of the combined models is the estimation of signal-to-noise ratios (S/N) in circumstances where backscatter from the microstructure (grain noise) acts to mask sonic echoes from internal defects. Such S/N models have been used in the past to address questions of inspection optimization and reliability. Under the sponsorship of the National Science Foundation's Industry/University Cooperative Research Center at ISU, an effort was recently initiated to improve existing research-grade software by adding graphical user interface (GUI) to become user friendly tools for the rapid estimation of S/N for ultrasonic inspections of metals. The software combines: (1) a Python-based GUI for specifying an inspection scenario and displaying results; and (2) a Fortran-based engine for computing defect signal and backscattered grain noise characteristics. The latter makes use of several models including: the Multi-Gaussian Beam Model for computing sonic fields radiated by commercial transducers; the Thompson-Gray Model for the response from an internal defect; the Independent Scatterer Model for backscattered grain noise; and the Stanke-Kino Unified Model for attenuation. The initial emphasis was on reformulating the research-grade code into a suitable modular form, adding the graphical user interface and performing computations rapidly and robustly. Thus the initial inspection problem being addressed is relatively simple. A normal-incidence pulse/echo immersion inspection is simulated for a curved metal component having a non-uniform microstructure, specifically an equiaxed, untextured microstructure in which the average

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

Directory of Open Access Journals (Sweden)

S. N. Kale

2009-01-01

Full Text Available 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 developed an optimal FTLRNN model, which removes the noise from the EMG signal. Results show that the proposed optimal FTLRNN model has an MSE (Mean Square Error as low as 0.000067 and 0.000048, correlation coefficient as high as 0.99950 and 0.99939 for noise signal and EMG signal, respectively, when validated on the test dataset. It is also noticed that the output of the estimated FTLRNN model closely follows the real one. This network is indeed robust as EMG signal tolerates the noise variance from 0.1 to 0.4 for uniform noise and 0.30 for Gaussian noise. It is clear that the training of the network is independent of specific partitioning of dataset. It is seen that the performance of the proposed FTLRNN model clearly outperforms the best Multilayer perceptron (MLP and Radial Basis Function NN (RBF models. The simple NN model such as the FTLRNN with single-hidden layer can be employed to remove noise from EMG signal.

Signal-to-noise limitations in white light holography.

Science.gov (United States)

Ribak, E; Roddier, C; Roddier, F; Breckinridge, J B

1988-03-15

A simple derivation is given for the signal-to-noise ratio (SNR) in images reconstructed from incoherent holograms. Dependence is shown to be on the hologram SNR, object complexity, and the number of pixels in the detector. Reconstruction of involved objects becomes possible with high dynamic range detectors such as charge coupled devices. We have produced such white light holograms by means of a rotational shear interferometer combined with a chromatic corrector. A digital inverse transform recreated the object.

Speckle noise reduction technique for Lidar echo signal based on self-adaptive pulse-matching independent component analysis

Science.gov (United States)

Xu, Fan; Wang, Jiaxing; Zhu, Daiyin; Tu, Qi

2018-04-01

Speckle noise has always been a particularly tricky problem in improving the ranging capability and accuracy of Lidar system especially in harsh environment. Currently, effective speckle de-noising techniques are extremely scarce and should be further developed. In this study, a speckle noise reduction technique has been proposed based on independent component analysis (ICA). Since normally few changes happen in the shape of laser pulse itself, the authors employed the laser source as a reference pulse and executed the ICA decomposition to find the optimal matching position. In order to achieve the self-adaptability of algorithm, local Mean Square Error (MSE) has been defined as an appropriate criterion for investigating the iteration results. The obtained experimental results demonstrated that the self-adaptive pulse-matching ICA (PM-ICA) method could effectively decrease the speckle noise and recover the useful Lidar echo signal component with high quality. Especially, the proposed method achieves 4 dB more improvement of signal-to-noise ratio (SNR) than a traditional homomorphic wavelet method.

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.

Maximizing signal-to-noise ratio (SNR) in 3-D large bandgap semiconductor pixelated detectors in optimal and non-optimal filtering conditions

International Nuclear Information System (INIS)

Rodrigues, Miesher L.; Serra, Andre da S.; He, Zhong; Zhu, Yuefeng

2009-01-01

3-D pixelated semiconductor detectors are used in radiation detection applications requiring spectroscopic and imaging information from radiation sources. Reconstruction algorithms used to determine direction and energy of incoming gamma rays can be improved by reducing electronic noise and using optimum filtering techniques. Position information can be improved by achieving sub-pixel resolution. Electronic noise is the limiting factor. Achieving sub-pixel resolution - position of the interaction better than one pixel pitch - in 3-D pixelated semiconductor detectors is a challenging task due to the fast transient characteristics of these signals. This work addresses two fundamental questions: the first is to determine the optimum filter, while the second is to estimate the achievable sub-pixel resolution using this filter. It is shown that the matched filter is the optimum filter when applying the signal-to-noise ratio criteria. Also, non-optimum filters are studied. The framework of 3-D waveform simulation using the Shockley-Ramo Theorem and the Hecht Equation for electron and hole trapping is presented in this work. This waveform simulator can be used to analyze current detectors as well as explore new ideas and concepts in future work. Numerical simulations show that assuming an electronic noise of 3.3 keV it is possible to subdivide the pixel region into 5x5 sub-pixels. After analyzing these results, it is suggested that sub-pixel information can also improve energy resolution. Current noise levels present the major drawback to both achieve sub-pixel resolution as well as improve energy resolution below the current limits. (author)

Improved Denoising via Poisson Mixture Modeling of Image Sensor Noise.

Science.gov (United States)

Zhang, Jiachao; Hirakawa, Keigo

2017-04-01

This paper describes a study aimed at comparing the real image sensor noise distribution to the models of noise often assumed in image denoising designs. A quantile analysis in pixel, wavelet transform, and variance stabilization domains reveal that the tails of Poisson, signal-dependent Gaussian, and Poisson-Gaussian models are too short to capture real sensor noise behavior. A new Poisson mixture noise model is proposed to correct the mismatch of tail behavior. Based on the fact that noise model mismatch results in image denoising that undersmoothes real sensor data, we propose a mixture of Poisson denoising method to remove the denoising artifacts without affecting image details, such as edge and textures. Experiments with real sensor data verify that denoising for real image sensor data is indeed improved by this new technique.

Modeling speech intelligibility based on the signal-to-noise envelope power ratio

DEFF Research Database (Denmark)

Jørgensen, Søren

of modulation frequency selectivity in the auditory processing of sound with a decision metric for intelligibility that is based on the signal-to-noise envelope power ratio (SNRenv). The proposed speech-based envelope power spectrum model (sEPSM) is demonstrated to account for the effects of stationary...... through three commercially available mobile phones. The model successfully accounts for the performance across the phones in conditions with a stationary speech-shaped background noise, whereas deviations were observed in conditions with “Traffic” and “Pub” noise. Overall, the results of this thesis...

Stochastic resonance for signal-modulated pump noise in a single-mode laser

Institute of Scientific and Technical Information of China (English)

Liangying Zhang; Li Cao; Fahui Zhu

2006-01-01

By adopting the gain-noise model of the single-mode laser in which with bias and periodical signals serve as inputs, combining with the effect of coloured pump noise, we use the linear approximation method to calculate the power spectrum and signal-to-noise ratio (SNR) of the laser intensity under the condition of pump noise and quantum noise cross-related in the form of δ function. It is found that with the change of pump noise correlation time, both SNR and the output power will occur stochastic resonance (SR). If the bias signal α is very small, changing the intensities of pump noise and quantum noise respectively does not lead to the appearance of SR in the SNR; while α increases to a certain number, SR appears.

How to improve a critical performance for an ExoMars 2020 Scientific Instrument (RLS). Raman Laser Spectrometer Signal to Noise Ratio (SNR) Optimization

Science.gov (United States)

Canora, C. P.; Moral, A. G.; Rull, F.; Maurice, S.; Hutchinson, I.; Ramos, G.; López-Reyes, G.; Belenguer, T.; Canchal, R.; Prieto, J. A. R.; Rodriguez, P.; Santamaria, P.; Berrocal, A.; Colombo, M.; Gallago, P.; Seoane, L.; Quintana, C.; Ibarmia, S.; Zafra, J.; Saiz, J.; Santiago, A.; Marin, A.; Gordillo, C.; Escribano, D.; Sanz-Palominoa, M.

2017-09-01

The Raman Laser Spectrometer (RLS) is one of the Pasteur Payload instruments, within the ESA's Aurora Exploration Programme, ExoMars mission. Raman spectroscopy is based on the analysis of spectral fingerprints due to the inelastic scattering of light when interacting with matter. RLS is composed by Units: SPU (Spectrometer Unit), iOH (Internal Optical Head), and ICEU (Instrument Control and Excitation Unit) and the harnesses (EH and OH). The iOH focuses the excitation laser on the samples and collects the Raman emission from the sample via SPU (CCD) and the video data (analog) is received, digitalizing it and transmiting it to the processor module (ICEU). The main sources of noise arise from the sample, the background, and the instrument (Laser, CCD, focuss, acquisition parameters, operation control). In this last case the sources are mainly perturbations from the optics, dark signal and readout noise. Also flicker noise arising from laser emission fluctuations can be considered as instrument noise. In order to evaluate the SNR of a Raman instrument in a practical manner it is useful to perform end-to-end measurements on given standards samples. These measurements have to be compared with radiometric simulations using Raman efficiency values from literature and taking into account the different instrumental contributions to the SNR. The RLS EQM instrument performances results and its functionalities have been demonstrated in accordance with the science expectations. The Instrument obtained SNR performances in the RLS EQM will be compared experimentally and via analysis, with the Instrument Radiometric Model tool. The characterization process for SNR optimization is still on going. The operational parameters and RLS algorithms (fluorescence removal and acquisition parameters estimation) will be improved in future models (EQM-2) until FM Model delivery.

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

Signal de-noising methods for fault diagnosis and troubleshooting at CANDU{sup ®} stations

Energy Technology Data Exchange (ETDEWEB)

Nasimi, Elnara; Gabbar, Hossam A., E-mail: hossam.gabbar@uoit.ca

2014-12-15

Highlights: • Fault modelling using a Fault Semantic Network (FSN). • Intelligent filtering techniques for signal de-noise in NPP. • Signal feature extraction is applied as integrated with FSN. • Increase signal-to-noise ratio (SNR). - Abstract: Over the past several years a number of domestic CANDU{sup ®} stations have experienced issues with neutron detection systems that challenged safety and operation. Intelligent troubleshooting methodology is required to aid in making risk-informed decisions related to design and operational activities, which can aid current stations and be used for the future generation of CANDU{sup ®} designs. Fault modelling approach using Fault Semantic Network (FSN) with risk estimation is proposed for this purpose. One major challenge in troubleshooting is the determination of accurate data. It is typical to have missing, incomplete or corrupted data points in large process data sets from dynamically changing systems. Therefore, it is expected that quality of obtained data will have a direct impact on the system's ability to recognize developing trends in the process upset situations. In order to enable fault detection process, intelligent filtering techniques are required to de-noise process data and extract valuable signal features in the presence of background noise. In this study, the impact of applying an optimized and intelligent filtering of process signals prior to data analysis is discussed. This is particularly important for neutronic signals in order to increase signal-to-noise ratio (SNR) which suffers the most during start-ups and low power operation. This work is complimentary to the previously published studies on FSN-based fault modelling in CANDU stations. The main objective of this work is to explore the potential research methods using a specific case study and, based on the results and outcomes from this work, to note the possible future improvements and innovation areas.

Improving signal-to-noise in the direct imaging of exoplanets and circumstellar disks with MLOCI

Science.gov (United States)

Wahhaj, Zahed; Cieza, Lucas A.; Mawet, Dimitri; Yang, Bin; Canovas, Hector; de Boer, Jozua; Casassus, Simon; Ménard, François; Schreiber, Matthias R.; Liu, Michael C.; Biller, Beth A.; Nielsen, Eric L.; Hayward, Thomas L.

2015-09-01

We present a new algorithm designed to improve the signal-to-noise ratio (S/N) of point and extended source detections around bright stars in direct imaging data.One of our innovations is that we insert simulated point sources into the science images, which we then try to recover with maximum S/N. This improves the S/N of real point sources elsewhere in the field. The algorithm, based on the locally optimized combination of images (LOCI) method, is called Matched LOCI or MLOCI. We show with Gemini Planet Imager (GPI) data on HD 135344 B and Near-Infrared Coronagraphic Imager (NICI) data on several stars that the new algorithm can improve the S/N of point source detections by 30-400% over past methods. We also find no increase in false detections rates. No prior knowledge of candidate companion locations is required to use MLOCI. On the other hand, while non-blind applications may yield linear combinations of science images that seem to increase the S/N of true sources by a factor >2, they can also yield false detections at high rates. This is a potential pitfall when trying to confirm marginal detections or to redetect point sources found in previous epochs. These findings are relevant to any method where the coefficients of the linear combination are considered tunable, e.g., LOCI and principal component analysis (PCA). Thus we recommend that false detection rates be analyzed when using these techniques. Based on observations obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (USA), the Science and Technology Facilities Council (UK), the National Research Council (Canada), CONICYT (Chile), the Australian Research Council (Australia), Ministério da Ciência e Tecnologia (Brazil) and Ministerio de Ciencia, Tecnología e Innovación Productiva (Argentina).

Background noise exerts diverse effects on the cortical encoding of foreground sounds.

Science.gov (United States)

Malone, B J; Heiser, Marc A; Beitel, Ralph E; Schreiner, Christoph E

2017-08-01

In natural listening conditions, many sounds must be detected and identified in the context of competing sound sources, which function as background noise. Traditionally, noise is thought to degrade the cortical representation of sounds by suppressing responses and increasing response variability. However, recent studies of neural network models and brain slices have shown that background synaptic noise can improve the detection of signals. Because acoustic noise affects the synaptic background activity of cortical networks, it may improve the cortical responses to signals. We used spike train decoding techniques to determine the functional effects of a continuous white noise background on the responses of clusters of neurons in auditory cortex to foreground signals, specifically frequency-modulated sweeps (FMs) of different velocities, directions, and amplitudes. Whereas the addition of noise progressively suppressed the FM responses of some cortical sites in the core fields with decreasing signal-to-noise ratios (SNRs), the stimulus representation remained robust or was even significantly enhanced at specific SNRs in many others. Even though the background noise level was typically not explicitly encoded in cortical responses, significant information about noise context could be decoded from cortical responses on the basis of how the neural representation of the foreground sweeps was affected. These findings demonstrate significant diversity in signal in noise processing even within the core auditory fields that could support noise-robust hearing across a wide range of listening conditions. NEW & NOTEWORTHY The ability to detect and discriminate sounds in background noise is critical for our ability to communicate. The neural basis of robust perceptual performance in noise is not well understood. We identified neuronal populations in core auditory cortex of squirrel monkeys that differ in how they process foreground signals in background noise and that may

Comparison of the signal-to-noise characteristics of quantum versus thermal ghost imaging

International Nuclear Information System (INIS)

O'Sullivan, Malcolm N.; Chan, Kam Wai Clifford; Boyd, Robert W.

2010-01-01

We present a theoretical comparison of the signal-to-noise characteristics of quantum versus thermal ghost imaging. We first calculate the signal-to-noise ratio of each process in terms of its controllable experimental conditions. We show that a key distinction is that a thermal ghost image always resides on top of a large background; the fluctuations in this background constitutes an intrinsic noise source for thermal ghost imaging. In contrast, there is a negligible intrinsic background to a quantum ghost image. However, for practical reasons involving achievable illumination levels, acquisition times for thermal ghost images are often much shorter than those for quantum ghost images. We provide quantitative predictions for the conditions under which each process provides superior performance. Our conclusion is that each process can provide useful functionality, although under complementary conditions.

Signal-to-noise characterization of time-gated intensifiers used for wide-field time-domain FLIM

Energy Technology Data Exchange (ETDEWEB)

McGinty, J; Requejo-Isidro, J; Munro, I; Talbot, C B; Dunsby, C; Neil, M A A; French, P M W [Photonics Group, Blackett Laboratory, Imperial College London, Prince Consort Road, London, SW7 2BW (United Kingdom); Kellett, P A; Hares, J D, E-mail: james.mcginty@imperial.ac.u [Kentech Instruments Ltd, Isis Building, Howbery Park, Wallingford, OX10 8BA (United Kingdom)

2009-07-07

Time-gated imaging using gated optical intensifiers provides a means to realize high speed fluorescence lifetime imaging (FLIM) for the study of fast events and for high throughput imaging. We present a signal-to-noise characterization of CCD-coupled micro-channel plate gated intensifiers used with this technique and determine the optimal acquisition parameters (intensifier gain voltage, CCD integration time and frame averaging) for measuring mono-exponential fluorescence lifetimes in the shortest image acquisition time for a given signal flux. We explore the use of unequal CCD integration times for different gate delays and show that this can improve the lifetime accuracy for a given total acquisition time.

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 (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.

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...... leading to the direction sensing capability. It is found that using the auto spectrum of the complex signal to determine the wind speed leads to a signal-to-noise ratio equivalent to that of a standard self-heterodyne receiver. Using the imaginary part of the cross spectrum to estimate the Doppler shift...... has the benefit of a zero-mean background spectrum, but comes at the expense of a decrease in the signal-to noise ratio by a factor of √2....

Simulation of range imaging-based estimation of respiratory lung motion. Influence of noise, signal dimensionality and sampling patterns.

Science.gov (United States)

Wilms, M; Werner, R; Blendowski, M; Ortmüller, J; Handels, H

2014-01-01

A major problem associated with the irradiation of thoracic and abdominal tumors is respiratory motion. In clinical practice, motion compensation approaches are frequently steered by low-dimensional breathing signals (e.g., spirometry) and patient-specific correspondence models, which are used to estimate the sought internal motion given a signal measurement. Recently, the use of multidimensional signals derived from range images of the moving skin surface has been proposed to better account for complex motion patterns. In this work, a simulation study is carried out to investigate the motion estimation accuracy of such multidimensional signals and the influence of noise, the signal dimensionality, and different sampling patterns (points, lines, regions). A diffeomorphic correspondence modeling framework is employed to relate multidimensional breathing signals derived from simulated range images to internal motion patterns represented by diffeomorphic non-linear transformations. Furthermore, an automatic approach for the selection of optimal signal combinations/patterns within this framework is presented. This simulation study focuses on lung motion estimation and is based on 28 4D CT data sets. The results show that the use of multidimensional signals instead of one-dimensional signals significantly improves the motion estimation accuracy, which is, however, highly affected by noise. Only small differences exist between different multidimensional sampling patterns (lines and regions). Automatically determined optimal combinations of points and lines do not lead to accuracy improvements compared to results obtained by using all points or lines. Our results show the potential of multidimensional breathing signals derived from range images for the model-based estimation of respiratory motion in radiation therapy.

Stochastic resonance in a stochastic bistable system with additive noises and square–wave signal

International Nuclear Information System (INIS)

Feng, Guo; Xiang-Dong, Luo; Shao-Fu, Li; Yu-Rong, Zhou

2010-01-01

This paper considers the stochastic resonance in a stochastic bistable system driven by a periodic square-wave signal and a static force as well as by additive white noise and dichotomous noise from the viewpoint of signal-to-noise ratio. It finds that the signal-to-noise ratio appears as stochastic resonance behaviour when it is plotted as a function of the noise strength of the white noise and dichotomous noise, as a function of the system parameters, or as a function of the static force. Moreover, the influence of the strength of the stochastic potential force and the correlation rate of the dichotomous noise on the signal-to-noise ratio is investigated. (general)

Filtering Performance Comparison of Kernel and Wavelet Filters for Reactivity Signal Noise

International Nuclear Information System (INIS)

Park, Moon Ghu; Shin, Ho Cheol; Lee, Yong Kwan; You, Skin

2006-01-01

Nuclear reactor power deviation from the critical state is a parameter of specific interest defined by the reactivity measuring neutron population. Reactivity is an extremely important quantity used to define many of the reactor startup physics parameters. The time dependent reactivity is normally determined by solving the using inverse neutron kinetics equation. The reactivity computer is a device to provide an on-line solution of the inverse kinetics equation. The measurement signal of the neutron density is normally noise corrupted and the control rods movement typically gives reactivity variation with edge signals like saw teeth. Those edge regions should be precisely preserved since the measured signal is used to estimate the reactivity wroth which is a crucial parameter to assure the safety of the nuclear reactors. In this paper, three kind of edge preserving noise filters are proposed and their performance is demonstrated using stepwise signals. The tested filters are based on the unilateral, bilateral kernel and wavelet filters which are known to be effective in edge preservation. The bilateral filter shows a remarkable improvement compared with unilateral kernel and wavelet filters

Mitigating Wind Induced Noise in Outdoor Microphone Signals Using a Singular Spectral Subspace Method

Directory of Open Access Journals (Sweden)

Omar Eldwaik

2018-01-01

Full Text Available Wind induced noise is one of the major concerns of outdoor acoustic signal acquisition. It affects many field measurement and audio recording scenarios. Filtering such noise is known to be difficult due to its broadband and time varying nature. In this paper, a new method to mitigate wind induced noise in microphone signals is developed. Instead of applying filtering techniques, wind induced noise is statistically separated from wanted signals in a singular spectral subspace. The paper is presented in the context of handling microphone signals acquired outdoor for acoustic sensing and environmental noise monitoring or soundscapes sampling. The method includes two complementary stages, namely decomposition and reconstruction. The first stage decomposes mixed signals in eigen-subspaces, selects and groups the principal components according to their contributions to wind noise and wanted signals in the singular spectrum domain. The second stage reconstructs the signals in the time domain, resulting in the separation of wind noise and wanted signals. Results show that microphone wind noise is separable in the singular spectrum domain evidenced by the weighted correlation. The new method might be generalized to other outdoor sound acquisition applications.

Agatha: Disentangling period signals from correlated noise in a periodogram framework

Science.gov (United States)

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

2018-04-01

Agatha is a framework of periodograms 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. Agatha can be used to select the optimal noise model and to test the consistency of signals in time and can be applied to time series analyses in other astronomical and scientific disciplines. An interactive web implementation of the software is also available at http://agatha.herts.ac.uk/.

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.

The signal-to-noise analysis of the Little-Hopfield model revisited

International Nuclear Information System (INIS)

Bolle, D; Blanco, J Busquets; Verbeiren, T

2004-01-01

Using the generating functional analysis an exact recursion relation is derived for the time evolution of the effective local field of the fully connected Little-Hopfield model. It is shown that, by leaving out the feedback correlations arising from earlier times in this effective dynamics, one precisely finds the recursion relations usually employed in the signal-to-noise approach. The consequences of this approximation as well as the physics behind it are discussed. In particular, it is pointed out why it is hard to notice the effects, especially for model parameters corresponding to retrieval. Numerical simulations confirm these findings. The signal-to-noise analysis is then extended to include all correlations, making it a full theory for dynamics at the level of the generating functional analysis. The results are applied to the frequently employed extremely diluted (a)symmetric architectures and to sequence processing networks

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 modulation frequencies is presented. Compared to other models in the field, this model takes into account the fibre loss, pump depletion as well as the gain ...

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.

Determination of signal intensity affected by Gaussian noise

International Nuclear Information System (INIS)

Blostein, Jeronimo J.; Bennun, Leonardo

1999-01-01

A methodology based on maximum likelihood criteria, to identify and quantify an arbitrary signal affected by Gaussian noise is shown. To use this methodology it is necessary to know the position in the spectrum where the signal of interest should appear, and the shape of the signal when the background is null or unappreciable. (author)

Noise-assisted data processing with empirical mode decomposition in biomedical signals.

Science.gov (United States)

Karagiannis, Alexandros; Constantinou, Philip

2011-01-01

In this paper, a methodology is described in order to investigate the performance of empirical mode decomposition (EMD) in biomedical signals, and especially in the case of electrocardiogram (ECG). Synthetic ECG signals corrupted with white Gaussian noise are employed and time series of various lengths are processed with EMD in order to extract the intrinsic mode functions (IMFs). A statistical significance test is implemented for the identification of IMFs with high-level noise components and their exclusion from denoising procedures. Simulation campaign results reveal that a decrease of processing time is accomplished with the introduction of preprocessing stage, prior to the application of EMD in biomedical time series. Furthermore, the variation in the number of IMFs according to the type of the preprocessing stage is studied as a function of SNR and time-series length. The application of the methodology in MIT-BIH ECG records is also presented in order to verify the findings in real ECG signals.

Limits of visual communication: the effect of signal-to-noise ratio on the intelligibility of American Sign Language.

Science.gov (United States)

Pavel, M; Sperling, G; Riedl, T; Vanderbeek, A

1987-12-01

To determine the limits of human observers' ability to identify visually presented American Sign Language (ASL), the contrast s and the amount of additive noise n in dynamic ASL images were varied independently. Contrast was tested over a 4:1 range; the rms signal-to-noise ratios (s/n) investigated were s/n = 1/4, 1/2, 1, and infinity (which is used to designate the original, uncontaminated images). Fourteen deaf subjects were tested with an intelligibility test composed of 85 isolated ASL signs, each 2-3 sec in length. For these ASL signs (64 x 96 pixels, 30 frames/sec), subjects' performance asymptotes between s/n = 0.5 and 1.0; further increases in s/n do not improve intelligibility. Intelligibility was found to depend only on s/n and not on contrast. A formulation in terms of logistic functions was proposed to derive intelligibility of ASL signs from s/n, sign familiarity, and sign difficulty. Familiarity (ignorance) is represented by additive signal-correlated noise; it represents the likelihood of a subject's knowing a particular ASL sign, and it adds to s/n. Difficulty is represented by a multiplicative difficulty coefficient; it represents the perceptual vulnerability of an ASL sign to noise and it adds to log(s/n).

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.

Deep Learning-Based Noise Reduction Approach to Improve Speech Intelligibility for Cochlear Implant Recipients.

Science.gov (United States)

Lai, Ying-Hui; Tsao, Yu; Lu, Xugang; Chen, Fei; Su, Yu-Ting; Chen, Kuang-Chao; Chen, Yu-Hsuan; Chen, Li-Ching; Po-Hung Li, Lieber; Lee, Chin-Hui

2018-01-20

for the key speech envelope information, thus, improving speech recognition more effectively for Mandarin CI recipients. The results suggest that the proposed deep learning-based NR approach can potentially be integrated into existing CI signal processors to overcome the degradation of speech perception caused by noise.

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 ...

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.

Investigation of signal models and methods for evaluating structures of processing telecommunication information exchange systems under acoustic noise conditions

Science.gov (United States)

Kropotov, Y. A.; Belov, A. A.; Proskuryakov, A. Y.; Kolpakov, A. A.

2018-05-01

The paper considers models and methods for estimating signals during the transmission of information messages in telecommunication systems of audio exchange. One-dimensional probability distribution functions that can be used to isolate useful signals, and acoustic noise interference are presented. An approach to the estimation of the correlation and spectral functions of the parameters of acoustic signals is proposed, based on the parametric representation of acoustic signals and the components of the noise components. The paper suggests an approach to improving the efficiency of interference cancellation and highlighting the necessary information when processing signals from telecommunications systems. In this case, the suppression of acoustic noise is based on the methods of adaptive filtering and adaptive compensation. The work also describes the models of echo signals and the structure of subscriber devices in operational command telecommunications systems.

Remote vibrotactile noise improves light touch sensation in stroke survivors' fingertips via stochastic resonance.

Science.gov (United States)

Enders, Leah R; Hur, Pilwon; Johnson, Michelle J; Seo, Na Jin

2013-10-11

Stroke rehabilitation does not often integrate both sensory and motor recovery. While subthreshold noise was shown to enhance sensory signal detection at the site of noise application, having a noise-generating device at the fingertip to enhance fingertip sensation and potentially enhance dexterity for stroke survivors is impractical, since the device would interfere with object manipulation. This study determined if remote application of subthreshold vibrotactile noise (away from the fingertips) improves fingertip tactile sensation with potential to enhance dexterity for stroke survivors. Index finger and thumb pad sensation was measured for ten stroke survivors with fingertip sensory deficit using the Semmes-Weinstein Monofilament and Two-Point Discrimination Tests. Sensation scores were measured with noise applied at one of three intensities (40%, 60%, 80% of the sensory threshold) to one of four locations of the paretic upper extremity (dorsal hand proximal to the index finger knuckle, dorsal hand proximal to the thumb knuckle, dorsal wrist, volar wrist) in a random order, as well as without noise at beginning (Pre) and end (Post) of the testing session. Vibrotactile noise of all intensities and locations instantaneously and significantly improved Monofilament scores of the index fingertip and thumb tip (p sensation, independent of noise location and intensity. Vibrotactile noise at the wrist and dorsal hand may have enhanced the fingertips' light touch sensation via stochastic resonance and interneuronal connections. While long-term benefits of noise in stroke patients warrants further investigation, this result demonstrates potential that a wearable device applying vibrotactile noise at the wrist could enhance sensation and grip ability without interfering with object manipulation in everyday tasks.

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.

Investigation on phase noise of the signal from a singly resonant optical parametric oscillator

Science.gov (United States)

Jinxia, Feng; Yuanji, Li; Kuanshou, Zhang

2018-04-01

The phase noise of the signal from a singly resonant optical parametric oscillator (SRO) is investigated theoretically and experimentally. An SRO based on periodically poled lithium niobate is built up that generates the signal with a maximum power of 5.2 W at 1.5 µm. The intensity noise of the signal reaches the shot noise level for frequencies above 5 MHz. The phase noise of the signal oscillates depending on the analysis frequency, and there are phase noise peaks above the shot noise level at the peak frequencies. To explain the phase noise feature of the signal, a semi-classical theoretical model of SROs including the guided acoustic wave Brillouin scattering effect within the nonlinear crystal is developed. The theoretical predictions are in good agreement with the experimental results.

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.

Suitable or optimal noise benefits in signal detection

International Nuclear Information System (INIS)

Liu, Shujun; Yang, Ting; Tang, Mingchun; Wang, Pin; Zhang, Xinzheng

2016-01-01

Highlights: • Six intervals of additive noises divided according to the two constraints. • Derivation of the suitable additive noise to meet the two constraints. • Formulation of the suitable noise for improvability or nonimprovability. • Optimal noises to minimize P FA , maximize P D and maximize the overall improvement. - Abstract: We present an effective way to generate the suitable or the optimal additive noises which can achieve the three goals of the noise enhanced detectability, i.e., the maximum detection probability (P D ), the minimum false alarm probability (P FA ) and the maximum overall improvement of P D and P FA , without increasing P FA and decreasing P D in a binary hypothesis testing problem. The mechanism of our method is that we divide the discrete vectors into six intervals and choose the useful or partial useful vectors from these intervals to form the additive noise according to different requirements. The form of the optimal noise is derived and proven as a randomization of no more than two discrete vectors in our way. Moreover, how to choose suitable and optimal noises from the six intervals are given. Finally, numerous examples are presented to illustrate the theoretical analysis, where the background noises are Gaussian, symmetric and asymmetric Gaussian mixture noise, respectively.

Reducing Brain Signal Noise in the Prediction of Economic Choices: A Case Study in Neuroeconomics

Directory of Open Access Journals (Sweden)

Raanju R. Sundararajan

2017-12-01

Full Text Available In order to reduce the noise of brain signals, neuroeconomic experiments typically aggregate data from hundreds of trials collected from a few individuals. This contrasts with the principle of simple and controlled designs in experimental and behavioral economics. We use a frequency domain variant of the stationary subspace analysis (SSA technique, denoted as DSSA, to filter out the noise (nonstationary sources in EEG brain signals. The nonstationary sources in the brain signal are associated with variations in the mental state that are unrelated to the experimental task. DSSA is a powerful tool for reducing the number of trials needed from each participant in neuroeconomic experiments and also for improving the prediction performance of an economic choice task. For a single trial, when DSSA is used as a noise reduction technique, the prediction model in a food snack choice experiment has an increase in overall accuracy by around 10% and in sensitivity and specificity by around 20% and in AUC by around 30%, respectively.

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.

Improvement of Source Number Estimation Method for Single Channel Signal.

Directory of Open Access Journals (Sweden)

Zhi Dong

Full Text Available Source number estimation methods for single channel signal have been investigated and the improvements for each method are suggested in this work. Firstly, the single channel data is converted to multi-channel form by delay process. Then, algorithms used in the array signal processing, such as Gerschgorin's disk estimation (GDE and minimum description length (MDL, are introduced to estimate the source number of the received signal. The previous results have shown that the MDL based on information theoretic criteria (ITC obtains a superior performance than GDE at low SNR. However it has no ability to handle the signals containing colored noise. On the contrary, the GDE method can eliminate the influence of colored noise. Nevertheless, its performance at low SNR is not satisfactory. In order to solve these problems and contradictions, the work makes remarkable improvements on these two methods on account of the above consideration. A diagonal loading technique is employed to ameliorate the MDL method and a jackknife technique is referenced to optimize the data covariance matrix in order to improve the performance of the GDE method. The results of simulation have illustrated that the performance of original methods have been promoted largely.

Noise Suppression in ECG Signals through Efficient One-Step Wavelet Processing Techniques

Directory of Open Access Journals (Sweden)

E. Castillo

2013-01-01

Full Text Available This paper illustrates the application of the discrete wavelet transform (DWT for wandering and noise suppression in electrocardiographic (ECG signals. A novel one-step implementation is presented, which allows improving the overall denoising process. In addition an exhaustive study is carried out, defining threshold limits and thresholding rules for optimal wavelet denoising using this presented technique. The system has been tested using synthetic ECG signals, which allow accurately measuring the effect of the proposed processing. Moreover, results from real abdominal ECG signals acquired from pregnant women are presented in order to validate the presented approach.

Signal discrimination of ULF electromagnetic data with using singular spectrum analysis – an attempt to detect train noise

Directory of Open Access Journals (Sweden)

S. Saito

2011-07-01

Full Text Available Electromagnetic phenomena associated with crustal activities have been reported in a wide frequency range (DC-HF. In particular, ULF electromagnetic phenomena are the most promising among them because of the deeper skin depth. However, ULF geoelctromagnetic data are a superposition of signals of different origins. They originated from interactions between the geomagnetic field and the solar wind, leak current by a DC-driven train (train noise, precipitation, and so on. In general, the intensity of electromagnetic signals associated with crustal activity is smaller than the above variations. Therefore, in order to detect a smaller signal, signal discrimination such as noise reduction or identification of noises is very important. In this paper, the singular spectrum analysis (SSA has been performed to detect the DC-driven train noise in geoelectric potential difference data. The aim of this paper is to develop an effective algorithm for the DC-driven train noise detection.

Background noise of acoustic emission signals in sodium piping loop

International Nuclear Information System (INIS)

Mori, Y.; Aoki, K.; Kuribayashi, K.; Kishi, T.; Sakakibara, Y.

1985-01-01

Background noise measurement in the frequency range of acoustic emission (AE) signals was made on the sodium piping loops of a 50 MW steam generator test facility in the Power Reactor and Nuclear Fuel Development Corporation (PNC). During the dynamic characteristics test of the steam generator over a wide range of operating conditions, the background noise generated on the pipe surface was measured using wideband AE sensor externally mounted with waveguide. Data were obtained for the effect of power loads of steam generator on both amplitude and frequency spectra of background noise signals. Source and nature of background noise were established

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.

Detection of oscillatory components in noise signals and its application to fast detection of sodium boiling in LMFBR's

International Nuclear Information System (INIS)

Ehrhardt, J.

1975-09-01

In general, the surveillance of technical plants is performed by observating the mean value of measured signals. In this method not all information included in these signals is used. On the other hand - for example in a reactor - disturbances are possible which generate small oscillatory components in the measured signals. In general, these oscillatory components do not influence the mean value of the signals and consequently do not activate the conventional control system; however they can be found by analysis of the signal's noise component. For the detection of these oscillatory signals the observation of the frequency spectra of the noise signals is particularly advantageous because they produce peaks at the oscillation frequencies. In this paper a new detection system for the fast detection of suddenly appearing peaks in the frequency spectra of noise signals is presented. The prototype of a compact detection unit was developed which continuously computes the power spectral density (PSD) of noise signals and simultaneously supervises the PSD for peaks in the relevant frequency range. The detection method is not affected by the frequency dependance of the PSD and is applicable to any noise signal. General criteria were developed to enable the determination of the optimal detection system and its sensitivity. The upper limits of false alarm rate and detection time were taken into account. The detection criteria are applicable to all noise signals with approximately normally distributed amplitudes. Theoretical results were confirmed in a number of experiments; special experimental and theoretical parameter studies were done for the optimal detection of sodium boiling in LMFBR's. Computations based on these results showed that local and integral sodium boiling can be detected in a wide core range of SNR 300 by observing fluctuations of the neutron flux. In this connection it is important to point out that no additional core instrumentation is necessary because the

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

International Nuclear Information System (INIS)

Mainprize, James G.; Yaffe, Martin J.

2010-01-01

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.

The curious case of HD 41248. A pair of static signals buried behind red noise

Energy Technology Data Exchange (ETDEWEB)

Jenkins, J. S.; Tuomi, M., E-mail: jjenkins@das.uchile.cl [Departamento de Astronomia, Universidad de Chile, Camino el Observatorio 1515, Las Condes, Santiago, Casilla 36-D (Chile)

2014-10-20

Gaining a better understanding of the effects of stellar-induced radial velocity noise is critical for the future of exoplanet studies since the discovery of the lowest-mass planets using this method will require us to go below the intrinsic stellar noise limit. An interesting test case in this respect is that of the southern solar analog HD 41248. The radial velocity time series of this star has been proposed to contain either a pair of signals with periods of around 18 and 25 days, which could be due to a pair of resonant super-Earths, or a single and varying 25 day signal that could arise due to a complex interplay between differential rotation and modulated activity. In this work, we build up more evidence for the former scenario, showing that the signals are still clearly significant, even after more than 10 yr of observations, and they likely do not change in period, amplitude, or phase as a function of time, the hallmarks of static Doppler signals. We show that over the last two observing seasons, this star was more intrinsically active and the noise reddened, highlighting why better noise models are needed to find the lowest amplitude signals, in particular, models that consider noise correlations. This analysis shows that there is still sufficient evidence for the existence of two super-Earths on the edge of, or locked into, a 7:5 mean motion resonance orbiting HD 41248.

Assessment of uniformity and signal-to-noise ratio in radiological image intensifier TV systems

International Nuclear Information System (INIS)

Malone, J.F.; O'Connor, M.K.; Maher, K.P.

1985-01-01

A method of measuring the uniformity of radiological Image Intensifier-TV systems is described. Large non-uniformities were observed in the systems tested. A method of estimating the Signal-to-Noise Ratio in such systems is also presented and applied to characterise the effectiveness of the noise reduction techniques used in digital fluoroscopy. (author)

Signal processing techniques for sodium boiling noise detection

International Nuclear Information System (INIS)

1989-05-01

At the Specialists' Meeting on Sodium Boiling Detection organized by the International Working Group on Fast Reactors (IWGFR) of the International Atomic Energy Agency at Chester in the United Kingdom in 1981 various methods of detecting sodium boiling were reported. But, it was not possible to make a comparative assessment of these methods because the signal condition in each experiment was different from others. That is why participants of this meeting recommended that a benchmark test should be carried out in order to evaluate and compare signal processing methods for boiling detection. Organization of the Co-ordinated Research Programme (CRP) on signal processing techniques for sodium boiling noise detection was also recommended at the 16th meeting of the IWGFR. The CRP on Signal Processing Techniques for Sodium Boiling Noise Detection was set up in 1984. Eight laboratories from six countries have agreed to participate in this CRP. The overall objective of the programme was the development of reliable on-line signal processing techniques which could be used for the detection of sodium boiling in an LMFBR core. During the first stage of the programme a number of existing processing techniques used by different countries have been compared and evaluated. In the course of further work, an algorithm for implementation of this sodium boiling detection system in the nuclear reactor will be developed. It was also considered that the acoustic signal processing techniques developed for boiling detection could well make a useful contribution to other acoustic applications in the reactor. This publication consists of two parts. Part I is the final report of the co-ordinated research programme on signal processing techniques for sodium boiling noise detection. Part II contains two introductory papers and 20 papers presented at four research co-ordination meetings since 1985. A separate abstract was prepared for each of these 22 papers. Refs, figs and tabs

Accuracy of signal-to-noise ratio measurement method for magnetic resonance images

International Nuclear Information System (INIS)

Ogura, Akio; Miyai, Akira; Maeda, Fumie; Fukutake, Hiroyuki; Kikumoto, Rikiya

2003-01-01

The signal-to-noise ratio (SNR) of a magnetic resonance image is a common measure of imager performance. However, evaluations for the calculation of the SNR use various methods. A problem with measuring SNR is caused by the distortion of noise statistics in commonly used magnitude images. In this study, measurement accuracy was compared among four methods of evaluating SNR according to the size and position of regions of interest (ROIs). The results indicated that the method that used the difference between two images showed the best agreement with the theoretical value. In the method that used a single image, the SNR calculated by using a small size of ROI showed better agreement with the theoretical value because of noise bias and image artifacts. However, in the method that used the difference between two images, a large size of ROI was better in reducing statistical errors. In the same way, the methods that used air noise and air signal were better when applied to a large ROI. In addition, the image subtraction process used to calculate pixel-by-pixel differences in images may reach zero on a minus pixel value when using an image processor with the MRI system and apparatuses associated with it. A revised equation is presented for this case. It is important to understand the characteristics of each method and to choose a suitable method carefully according to the purpose of the study. (author)

Signal-to-noise contribution of principal component loads in reconstructed near-infrared Raman tissue spectra.

Science.gov (United States)

Grimbergen, M C M; van Swol, C F P; Kendall, C; Verdaasdonk, R M; Stone, N; Bosch, J L H R

2010-01-01

The overall quality of Raman spectra in the near-infrared region, where biological samples are often studied, has benefited from various improvements to optical instrumentation over the past decade. However, obtaining ample spectral quality for analysis is still challenging due to device requirements and short integration times required for (in vivo) clinical applications of Raman spectroscopy. Multivariate analytical methods, such as principal component analysis (PCA) and linear discriminant analysis (LDA), are routinely applied to Raman spectral datasets to develop classification models. Data compression is necessary prior to discriminant analysis to prevent or decrease the degree of over-fitting. The logical threshold for the selection of principal components (PCs) to be used in discriminant analysis is likely to be at a point before the PCs begin to introduce equivalent signal and noise and, hence, include no additional value. Assessment of the signal-to-noise ratio (SNR) at a certain peak or over a specific spectral region will depend on the sample measured. Therefore, the mean SNR over the whole spectral region (SNR(msr)) is determined in the original spectrum as well as for spectra reconstructed from an increasing number of principal components. This paper introduces a method of assessing the influence of signal and noise from individual PC loads and indicates a method of selection of PCs for LDA. To evaluate this method, two data sets with different SNRs were used. The sets were obtained with the same Raman system and the same measurement parameters on bladder tissue collected during white light cystoscopy (set A) and fluorescence-guided cystoscopy (set B). This method shows that the mean SNR over the spectral range in the original Raman spectra of these two data sets is related to the signal and noise contribution of principal component loads. The difference in mean SNR over the spectral range can also be appreciated since fewer principal components can

Influence of Signal and Noise on Statistical Fluctuation of Single-Mode Laser System

International Nuclear Information System (INIS)

Xu Dahai; Cheng Qinghua; Cao Li; Wu Dajin

2006-01-01

On the basis of calculating the steady-state mean normalized intensity fluctuation of a signal-mode laser system driven by both colored pump noise with signal modulation and the quantum noise with cross-correlation between its real and imaginary parts, we analyze the influence of modulation signal, noise, and its correlation form on the statistical fluctuation of the laser system. We have found that when the amplitude of modulation signal weakens and its frequency quickens, the statistical fluctuation will reduce rapidly. The statistical fluctuation of the laser system can be restrained by reducing the intensity of pump noise and quantum noise. Moreover, with prolonging of colored cross-correlation time, the statistical fluctuation of laser system experiences a repeated changing process, that is, from decreasing to augmenting, then to decreasing, and finally to augmenting again. With the decreasing of the value of cross-correlation coefficient, the statistical fluctuation will decrease too. When the cross-correlation form between the real part and imaginary part of quantum noise is zero correlation, the statistical fluctuation of laser system has a minimum. Compared with the influence of intensity of pump noise, the influence of intensity of quantum noise on the statistical fluctuation is smaller.

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.

Seismic signal and noise on Europa and how to use it

Science.gov (United States)

Panning, M. P.; Stähler, S. C.; Bills, B. G.; Castillo, J.; Huang, H. H.; Husker, A. L.; Kedar, S.; Lorenz, R. D.; Pike, W. T.; Schmerr, N. C.; Tsai, V. C.; Vance, S.

2017-12-01

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 a potential 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 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 predicted seismic observations using 2D numerical seismic simulations. We also show some of the key seismic observations to determine interior properties of Europa (Stähler et al., 2017). 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. S. C. Stähler, M. P. Panning, S. D. Vance, R. D. Lorenz, M. van Driel, T. Nissen-Meyer, S. Kedar, "Seismic wave propagation in icy ocean worlds," J. Geophys. Res., in revision, 2017.

Stochastic resonance in a single-mode laser driven by frequency modulated signal and coloured noises

Institute of Scientific and Technical Information of China (English)

Jin Guo-Xiang; Zhang Liang-Ying; Cao Li

2009-01-01

By adding frequency modulated signals to the intensity equation of gain-noise model of the single-mode laser driven by two coloured noises which are correlated, this paper uses the linear approximation method to calculate the power spectrum and signal-to-noise ratio (SNR) of the laser intensity. The results show that the SNR appears typical stochastic resonance with the variation of intensity of the pump noise and quantum noise. As the amplitude of a modulated signal has effects on the SNR, it shows suppression, monotone increasing, stochastic resonance, and multiple stochastic resonance with the variation of the frequency of a carrier signal and modulated signal.

Evaluation and comparison of contrast to noise ratio and signal to noise ratio according to change of reconstruction on breast PET/CT

Energy Technology Data Exchange (ETDEWEB)

Lee, Young Jae [Dept. of Nuclear Medicine, Seoul National University Hospital, Seoul (Korea, Republic of); Lee, Eul Kyu [Dept. of Radiology, Inje Paik University Hospital Jeo-dong, Seoul (Korea, Republic of); Kim, Ki Won [Dept. of Radiology, Kyung Hee University Hospital at Gang-dong, Seoul (Korea, Republic of); Jeong, Hoi Woun [Dept. of Radiological Technology, The Baekseok Culture University, Cheonan (Korea, Republic of); Lyu, Kwang Yeul; Park, Hoon Hee; Son, Jin Hyun; Min, Jung Whan [Dept. of Radiological Technology, The Shingu University, Sungnam (Korea, Republic of)

2017-03-15

The purpose of this study was to measure contrast to noise ratio (CNR) and signal to noise ratio (SNR) according to change of reconstruction from region of interest (ROI) in breast positron emission tomography- computed tomography (PET-CT), and to analyze the CNR and SNR statically. We examined images of breast PET-CT of 100 patients in a University-affiliated hospital, Seoul, Korea. Each patient's image of breast PET-CT were calculated by using Image J. Differences of CNR and SNR among four reconstruction algorithms were tested by SPSS Statistics21 ANOVA test for there was statistical significance (p<0.05). We have analysis socio-demographical variables, CNR and SNR according to reconstruction images, 95% confidence according to CNR and SNR of reconstruction and difference in a mean of CNR and SNR. SNR results, with the quality of distributions in the order of PSF{sub T}OF, Iterative and Iterative-TOF, FBP-TOF. CNR, with the quality of distributions in the order of PSF{sub T}OF, Iterative and Iterative-TOF, FBP-TOF. CNR and SNR of PET-CT reconstruction methods of the breast would be useful to evaluate breast diseases.

Realistic camera noise modeling with application to improved HDR synthesis

Science.gov (United States)

Goossens, Bart; Luong, Hiêp; Aelterman, Jan; Pižurica, Aleksandra; Philips, Wilfried

2012-12-01

Due to the ongoing miniaturization of digital camera sensors and the steady increase of the "number of megapixels", individual sensor elements of the camera become more sensitive to noise, even deteriorating the final image quality. To go around this problem, sophisticated processing algorithms in the devices, can help to maximally exploit the knowledge on the sensor characteristics (e.g., in terms of noise), and offer a better image reconstruction. Although a lot of research focuses on rather simplistic noise models, such as stationary additive white Gaussian noise, only limited attention has gone to more realistic digital camera noise models. In this article, we first present a digital camera noise model that takes several processing steps in the camera into account, such as sensor signal amplification, clipping, post-processing,.. We then apply this noise model to the reconstruction problem of high dynamic range (HDR) images from a small set of low dynamic range (LDR) exposures of a static scene. In literature, HDR reconstruction is mostly performed by computing a weighted average, in which the weights are directly related to the observer pixel intensities of the LDR image. In this work, we derive a Bayesian probabilistic formulation of a weighting function that is near-optimal in the MSE sense (or SNR sense) of the reconstructed HDR image, by assuming exponentially distributed irradiance values. We define the weighting function as the probability that the observed pixel intensity is approximately unbiased. The weighting function can be directly computed based on the noise model parameters, which gives rise to different symmetric and asymmetric shapes when electronic noise or photon noise is dominant. We also explain how to deal with the case that some of the noise model parameters are unknown and explain how the camera response function can be estimated using the presented noise model. Finally, experimental results are provided to support our findings.

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...

Signals and noise in measurements of low-frequency geomagnetic fields

International Nuclear Information System (INIS)

Nichols, E.A.; Morrison, H.F.; Clarke, J.

1988-01-01

The apparent magnetic noise, obtained from the coherency function for two parallel magnetic sensors, generally overstimates sensor noise because the sensors do not measure the same signal. The different signals result from the nonparallel alignment of the sensors and from the additional magnetic signal induced in each sensor by its motion in the Earth's magnetic field. A magnetometer array experiment was completed in Grass Valley, Nevada, to determine the minimum magnetic signal that could be detected in the presence of background natural field variations and motion of the sensor. Superconducting quantum interference device (SQUID) magnetometers with interval biaxial tiltmeters were used to record the magnetic fields and the motion of the sensors

Reactor noise monitoring device

International Nuclear Information System (INIS)

Yamanaka, Hiroto.

1990-01-01

The present invention concerns a reactor noise monitoring device by detecting abnormal sounds in background noises. Vibration sounds detected by accelerometers are applied to a loose parts detector. The detector generates high alarm if there are sudden impact sounds in the background noises and applies output signals to an accumulation device. If there is slight impact sounds in the vicinity of any of the accelerometers, the accumulation device accumulates the abnormal sounds assumed to be generated from an identical site while synchronizing the waveforms for all of the channels. Then, the device outputs signals in which the background noises are cancelled, as detection signals. Therefore, S/N ratio can be improved and the abnormal sounds contained in the background noises can be detected, to thereby improve the accuracy for estimating the position where the abnormal sounds are generated. (I.S.)

Significant improvement in one-dimensional cursor control using Laplacian electroencephalography over electroencephalography

Science.gov (United States)

Boudria, Yacine; Feltane, Amal; Besio, Walter

2014-06-01

Objective. Brain-computer interfaces (BCIs) based on electroencephalography (EEG) have been shown to accurately detect mental activities, but the acquisition of high levels of control require extensive user training. Furthermore, EEG has low signal-to-noise ratio and low spatial resolution. The objective of the present study was to compare the accuracy between two types of BCIs during the first recording session. EEG and tripolar concentric ring electrode (TCRE) EEG (tEEG) brain signals were recorded and used to control one-dimensional cursor movements. Approach. Eight human subjects were asked to imagine either ‘left’ or ‘right’ hand movement during one recording session to control the computer cursor using TCRE and disc electrodes. Main results. The obtained results show a significant improvement in accuracies using TCREs (44%-100%) compared to disc electrodes (30%-86%). Significance. This study developed the first tEEG-based BCI system for real-time one-dimensional cursor movements and showed high accuracies with little training.

LIMPIC: a computational method for the separation of protein MALDI-TOF-MS signals from noise

Directory of Open Access Journals (Sweden)

Di Nicola Marta

2007-03-01

Full Text Available Abstract Background Mass spectrometry protein profiling is a promising tool for biomarker discovery in clinical proteomics. However, the development of a reliable approach for the separation of protein signals from noise is required. In this paper, LIMPIC, a computational method for the detection of protein peaks from linear-mode MALDI-TOF data is proposed. LIMPIC is based on novel techniques for background noise reduction and baseline removal. Peak detection is performed considering the presence of a non-homogeneous noise level in the mass spectrum. A comparison of the peaks collected from multiple spectra is used to classify them on the basis of a detection rate parameter, and hence to separate the protein signals from other disturbances. Results LIMPIC preprocessing proves to be superior than other classical preprocessing techniques, allowing for a reliable decomposition of the background noise and the baseline drift from the MALDI-TOF mass spectra. It provides lower coefficient of variation associated with the peak intensity, improving the reliability of the information that can be extracted from single spectra. Our results show that LIMPIC peak-picking is effective even in low protein concentration regimes. The analytical comparison with commercial and freeware peak-picking algorithms demonstrates its superior performances in terms of sensitivity and specificity, both on in-vitro purified protein samples and human plasma samples. Conclusion The quantitative information on the peak intensity extracted with LIMPIC could be used for the recognition of significant protein profiles by means of advanced statistic tools: LIMPIC might be valuable in the perspective of biomarker discovery.

Signal-to-noise ratio estimation in digital computer simulation of lowpass and bandpass systems with applications to analog and digital communications, volume 3

Science.gov (United States)

Tranter, W. H.; Turner, M. D.

1977-01-01

Techniques are developed to estimate power gain, delay, signal-to-noise ratio, and mean square error in digital computer simulations of lowpass and bandpass systems. The techniques are applied to analog and digital communications. The signal-to-noise ratio estimates are shown to be maximum likelihood estimates in additive white Gaussian noise. The methods are seen to be especially useful for digital communication systems where the mapping from the signal-to-noise ratio to the error probability can be obtained. Simulation results show the techniques developed to be accurate and quite versatile in evaluating the performance of many systems through digital computer simulation.

ECG signal performance de-noising assessment based on threshold tuning of dual-tree wavelet transform.

Science.gov (United States)

El B'charri, Oussama; Latif, Rachid; Elmansouri, Khalifa; Abenaou, Abdenbi; Jenkal, Wissam

2017-02-07

Since the electrocardiogram (ECG) signal has a low frequency and a weak amplitude, it is sensitive to miscellaneous mixed noises, which may reduce the diagnostic accuracy and hinder the physician's correct decision on patients. The dual tree wavelet transform (DT-WT) is one of the most recent enhanced versions of discrete wavelet transform. However, threshold tuning on this method for noise removal from ECG signal has not been investigated yet. In this work, we shall provide a comprehensive study on the impact of the choice of threshold algorithm, threshold value, and the appropriate wavelet decomposition level to evaluate the ECG signal de-noising performance. A set of simulations is performed on both synthetic and real ECG signals to achieve the promised results. First, the synthetic ECG signal is used to observe the algorithm response. The evaluation results of synthetic ECG signal corrupted by various types of noise has showed that the modified unified threshold and wavelet hyperbolic threshold de-noising method is better in realistic and colored noises. The tuned threshold is then used on real ECG signals from the MIT-BIH database. The results has shown that the proposed method achieves higher performance than the ordinary dual tree wavelet transform into all kinds of noise removal from ECG signal. The simulation results indicate that the algorithm is robust for all kinds of noises with varying degrees of input noise, providing a high quality clean signal. Moreover, the algorithm is quite simple and can be used in real time ECG monitoring.

Particle image velocimetry correlation signal-to-noise ratio metrics and measurement uncertainty quantification

International Nuclear Information System (INIS)

Xue, Zhenyu; Charonko, John J; Vlachos, Pavlos P

2014-01-01

In particle image velocimetry (PIV) the measurement signal is contained in the recorded intensity of the particle image pattern superimposed on a variety of noise sources. The signal-to-noise-ratio (SNR) strength governs the resulting PIV cross correlation and ultimately the accuracy and uncertainty of the resulting PIV measurement. Hence we posit that correlation SNR metrics calculated from the correlation plane can be used to quantify the quality of the correlation and the resulting uncertainty of an individual measurement. In this paper we extend the original work by Charonko and Vlachos and present a framework for evaluating the correlation SNR using a set of different metrics, which in turn are used to develop models for uncertainty estimation. Several corrections have been applied in this work. The SNR metrics and corresponding models presented herein are expanded to be applicable to both standard and filtered correlations by applying a subtraction of the minimum correlation value to remove the effect of the background image noise. In addition, the notion of a ‘valid’ measurement is redefined with respect to the correlation peak width in order to be consistent with uncertainty quantification principles and distinct from an ‘outlier’ measurement. Finally the type and significance of the error distribution function is investigated. These advancements lead to more robust and reliable uncertainty estimation models compared with the original work by Charonko and Vlachos. The models are tested against both synthetic benchmark data as well as experimental measurements. In this work, U 68.5 uncertainties are estimated at the 68.5% confidence level while U 95 uncertainties are estimated at 95% confidence level. For all cases the resulting calculated coverage factors approximate the expected theoretical confidence intervals, thus demonstrating the applicability of these new models for estimation of uncertainty for individual PIV measurements. (paper)

Particle image velocimetry correlation signal-to-noise ratio metrics and measurement uncertainty quantification

Science.gov (United States)

Xue, Zhenyu; Charonko, John J.; Vlachos, Pavlos P.

2014-11-01

In particle image velocimetry (PIV) the measurement signal is contained in the recorded intensity of the particle image pattern superimposed on a variety of noise sources. The signal-to-noise-ratio (SNR) strength governs the resulting PIV cross correlation and ultimately the accuracy and uncertainty of the resulting PIV measurement. Hence we posit that correlation SNR metrics calculated from the correlation plane can be used to quantify the quality of the correlation and the resulting uncertainty of an individual measurement. In this paper we extend the original work by Charonko and Vlachos and present a framework for evaluating the correlation SNR using a set of different metrics, which in turn are used to develop models for uncertainty estimation. Several corrections have been applied in this work. The SNR metrics and corresponding models presented herein are expanded to be applicable to both standard and filtered correlations by applying a subtraction of the minimum correlation value to remove the effect of the background image noise. In addition, the notion of a ‘valid’ measurement is redefined with respect to the correlation peak width in order to be consistent with uncertainty quantification principles and distinct from an ‘outlier’ measurement. Finally the type and significance of the error distribution function is investigated. These advancements lead to more robust and reliable uncertainty estimation models compared with the original work by Charonko and Vlachos. The models are tested against both synthetic benchmark data as well as experimental measurements. In this work, {{U}68.5} uncertainties are estimated at the 68.5% confidence level while {{U}95} uncertainties are estimated at 95% confidence level. For all cases the resulting calculated coverage factors approximate the expected theoretical confidence intervals, thus demonstrating the applicability of these new models for estimation of uncertainty for individual PIV measurements.

Comparison of contrast-to-noise ratios of transmission and dark-field signal in grating-based X-ray imaging for healthy murine lung tissue

International Nuclear Information System (INIS)

Schwab, Felix; Schleede, Simone; Hahn, Dieter

2013-01-01

Purpose: An experimental comparison of the contrast-to-noise ratio (CNR) between transmission and dark-field signals in grating-based X-ray imaging for ex-vivo murine lung tissue. Materials and Methods: Lungs from three healthy mice were imaged ex vivo using a laser-driven compact synchrotron X-ray source. Background noise of transmission and dark-field signal was quantified by measuring the standard deviation in a region of interest (ROI) placed in a homogeneous area outside the specimen. Image contrast was quantified by measuring the signal range in rectangular ROIs placed in central and peripheral lung parenchyma. The relative contrast gain (RCG) of dark-field over transmission images was calculated as CNRDF / CNRT. Results: In all images, there was a trend for contrast-to-noise ratios of dark-field images (CNRDF) to be higher than for transmission images (CNRT) for all ROIs (median 61 vs. 38, p = 0.10), but the difference was statistically significant only for peripheral ROIs (61 vs. 32, p = 0.03). Median RCG was >1 for all ROIs (1.84). RCG values were significantly smaller for central ROIs than for peripheral ROIs (1.34 vs. 2.43, p = 0.03). Conclusion: The contrast-to-noise ratio of dark-field images compares more favorably to the contrast-to-noise ratio of transmission images for peripheral lung regions as compared to central regions. For any specific specimen, a calculation of the RCG allows comparing which X-ray modality (dark-field or transmission imaging) produces better contrast-to-noise characteristics in a well-defined ROI. (orig.)

Application of time-resolved glucose concentration photoacoustic signals based on an improved wavelet denoising

Science.gov (United States)

Ren, Zhong; Liu, Guodong; Huang, Zhen

2014-10-01

Real-time monitoring of blood glucose concentration (BGC) is a great important procedure in controlling diabetes mellitus and preventing the complication for diabetic patients. Noninvasive measurement of BGC has already become a research hotspot because it can overcome the physical and psychological harm. Photoacoustic spectroscopy is a well-established, hybrid and alternative technique used to determine the BGC. According to the theory of photoacoustic technique, the blood is irradiated by plused laser with nano-second repeation time and micro-joule power, the photoacoustic singals contained the information of BGC are generated due to the thermal-elastic mechanism, then the BGC level can be interpreted from photoacoustic signal via the data analysis. But in practice, the time-resolved photoacoustic signals of BGC are polluted by the varities of noises, e.g., the interference of background sounds and multi-component of blood. The quality of photoacoustic signal of BGC directly impacts the precision of BGC measurement. So, an improved wavelet denoising method was proposed to eliminate the noises contained in BGC photoacoustic signals. To overcome the shortcoming of traditional wavelet threshold denoising, an improved dual-threshold wavelet function was proposed in this paper. Simulation experimental results illustrated that the denoising result of this improved wavelet method was better than that of traditional soft and hard threshold function. To varify the feasibility of this improved function, the actual photoacoustic BGC signals were test, the test reslut demonstrated that the signal-to-noises ratio(SNR) of the improved function increases about 40-80%, and its root-mean-square error (RMSE) decreases about 38.7-52.8%.

Signal and noise analysis of a-Si:H radiation detector-amplifier system

International Nuclear Information System (INIS)

Cho, Gyuseong.

1992-03-01

Hydrogenated amorphous silicon (a-Si:H) has potential advantages in making radiation detectors for many applications because of its deposition capability on a large-area substrate and its high radiation resistance. Position-sensitive radiation detectors can be made out of a 1d strip or a 2-d pixel array of a Si:H pin diodes. In addition, signal processing electronics can be made by thin-film transistors on the same substrate. The calculated radiation signal, based on a simple charge collection model agreed well with results from various wave length light sources and 1 MeV beta particles on sample diodes. The total noise of the detection system was analyzed into (a) shot noise and (b) 1/f noise from a detector diode, and (c) thermal noise and (d) 1/f noise from the frontend TFT of a charge-sensitive preamplifier. the effective noise charge calculated by convoluting these noise power spectra with the transfer function of a CR-RC shaping amplifier showed a good agreement with the direct measurements of noise charge. The derived equations of signal and noise charge can be used to design an a-Si:H pixel detector amplifier system optimally. Signals from a pixel can be readout using switching TFTs, or diodes. Prototype tests of a double-diode readout scheme showed that the storage time and the readout time are limited by the resistances of the reverse-biased pixel diode and the forward biased switching diodes respectively. A prototype charge-sensitive amplifier was made using poly-Si TFTs to test the feasibility of making pixel-level amplifiers which would be required in small-signal detection. The measured overall gain-bandwidth product was ∼400 MHz and the noise charge ∼1000 electrons at a 1 μsec shaping time. When the amplifier is connected to a pixel detector of capacitance 0.2 pF, it would give a charge-to-voltage gain of ∼0.02 mV/electron with a pulse rise time less than 100 nsec and a dynamic range of 48 dB

Signal and noise analysis of a-Si:H radiation detector-amplifier system

Energy Technology Data Exchange (ETDEWEB)

Cho, Gyuseong [Univ. of California, Berkeley, CA (United States)

1992-03-01

Hydrogenated amorphous silicon (a-Si:H) has potential advantages in making radiation detectors for many applications because of its deposition capability on a large-area substrate and its high radiation resistance. Position-sensitive radiation detectors can be made out of a 1d strip or a 2-d pixel array of a Si:H pin diodes. In addition, signal processing electronics can be made by thin-film transistors on the same substrate. The calculated radiation signal, based on a simple charge collection model agreed well with results from various wave length light sources and 1 MeV beta particles on sample diodes. The total noise of the detection system was analyzed into (a) shot noise and (b) 1/f noise from a detector diode, and (c) thermal noise and (d) 1/f noise from the frontend TFT of a charge-sensitive preamplifier. the effective noise charge calculated by convoluting these noise power spectra with the transfer function of a CR-RC shaping amplifier showed a good agreement with the direct measurements of noise charge. The derived equations of signal and noise charge can be used to design an a-Si:H pixel detector amplifier system optimally. Signals from a pixel can be readout using switching TFTs, or diodes. Prototype tests of a double-diode readout scheme showed that the storage time and the readout time are limited by the resistances of the reverse-biased pixel diode and the forward biased switching diodes respectively. A prototype charge-sensitive amplifier was made using poly-Si TFTs to test the feasibility of making pixel-level amplifiers which would be required in small-signal detection. The measured overall gain-bandwidth product was ~400 MHz and the noise charge ~1000 electrons at a 1 μsec shaping time. When the amplifier is connected to a pixel detector of capacitance 0.2 pF, it would give a charge-to-voltage gain of ~0.02 mV/electron with a pulse rise time less than 100 nsec and a dynamic range of 48 dB.

Signal and noise analysis of a-Si:H radiation detector-amplifier system

Energy Technology Data Exchange (ETDEWEB)

Cho, Gyuseong.

1992-03-01

Hydrogenated amorphous silicon (a-Si:H) has potential advantages in making radiation detectors for many applications because of its deposition capability on a large-area substrate and its high radiation resistance. Position-sensitive radiation detectors can be made out of a 1d strip or a 2-d pixel array of a Si:H pin diodes. In addition, signal processing electronics can be made by thin-film transistors on the same substrate. The calculated radiation signal, based on a simple charge collection model agreed well with results from various wave length light sources and 1 MeV beta particles on sample diodes. The total noise of the detection system was analyzed into (a) shot noise and (b) 1/f noise from a detector diode, and (c) thermal noise and (d) 1/f noise from the frontend TFT of a charge-sensitive preamplifier. the effective noise charge calculated by convoluting these noise power spectra with the transfer function of a CR-RC shaping amplifier showed a good agreement with the direct measurements of noise charge. The derived equations of signal and noise charge can be used to design an a-Si:H pixel detector amplifier system optimally. Signals from a pixel can be readout using switching TFTs, or diodes. Prototype tests of a double-diode readout scheme showed that the storage time and the readout time are limited by the resistances of the reverse-biased pixel diode and the forward biased switching diodes respectively. A prototype charge-sensitive amplifier was made using poly-Si TFTs to test the feasibility of making pixel-level amplifiers which would be required in small-signal detection. The measured overall gain-bandwidth product was {approximately}400 MHz and the noise charge {approximately}1000 electrons at a 1 {mu}sec shaping time. When the amplifier is connected to a pixel detector of capacitance 0.2 pF, it would give a charge-to-voltage gain of {approximately}0.02 mV/electron with a pulse rise time less than 100 nsec and a dynamic range of 48 dB.

A Background Noise Reduction Technique Using Adaptive Noise Cancellation for Microphone Arrays

Science.gov (United States)

Spalt, Taylor B.; Fuller, Christopher R.; Brooks, Thomas F.; Humphreys, William M., Jr.; Brooks, Thomas F.

2011-01-01

Background noise in wind tunnel environments poses a challenge to acoustic measurements due to possible low or negative Signal to Noise Ratios (SNRs) present in the testing environment. This paper overviews the application of time domain Adaptive Noise Cancellation (ANC) to microphone array signals with an intended application of background noise reduction in wind tunnels. An experiment was conducted to simulate background noise from a wind tunnel circuit measured by an out-of-flow microphone array in the tunnel test section. A reference microphone was used to acquire a background noise signal which interfered with the desired primary noise source signal at the array. The technique s efficacy was investigated using frequency spectra from the array microphones, array beamforming of the point source region, and subsequent deconvolution using the Deconvolution Approach for the Mapping of Acoustic Sources (DAMAS) algorithm. Comparisons were made with the conventional techniques for improving SNR of spectral and Cross-Spectral Matrix subtraction. The method was seen to recover the primary signal level in SNRs as low as -29 dB and outperform the conventional methods. A second processing approach using the center array microphone as the noise reference was investigated for more general applicability of the ANC technique. It outperformed the conventional methods at the -29 dB SNR but yielded less accurate results when coherence over the array dropped. This approach could possibly improve conventional testing methodology but must be investigated further under more realistic testing conditions.

Low-Noise CMOS Circuits for On-Chip Signal Processing in Focal-Plane Arrays

Science.gov (United States)

Pain, Bedabrata

The performance of focal-plane arrays can be significantly enhanced through the use of on-chip signal processing. Novel, in-pixel, on-focal-plane, analog signal-processing circuits for high-performance imaging are presented in this thesis. The presence of a high background-radiation is a major impediment for infrared focal-plane array design. An in-pixel, background-suppression scheme, using dynamic analog current memory circuit, is described. The scheme also suppresses spatial noise that results from response non-uniformities of photo-detectors, leading to background limited infrared detector readout performance. Two new, low-power, compact, current memory circuits, optimized for operation at ultra-low current levels required in infrared-detection, are presented. The first one is a self-cascading current memory that increases the output impedance, and the second one is a novel, switch feed-through reducing current memory, implemented using error-current feedback. This circuit can operate with a residual absolute -error of less than 0.1%. The storage-time of the memory is long enough to also find applications in neural network circuits. In addition, a voltage-mode, accurate, low-offset, low-power, high-uniformity, random-access sample-and-hold cell, implemented using a CCD with feedback, is also presented for use in background-suppression and neural network applications. A new, low noise, ultra-low level signal readout technique, implemented by individually counting photo-electrons within the detection pixel, is presented. The output of each unit-cell is a digital word corresponding to the intensity of the photon flux, and the readout is noise free. This technique requires the use of unit-cell amplifiers that feature ultra-high-gain, low-power, self-biasing capability and noise in sub-electron levels. Both single-input and differential-input implementations of such amplifiers are investigated. A noise analysis technique is presented for analyzing sampled

Ultra-low noise miniaturized neural amplifier with hardware averaging.

Science.gov (United States)

Dweiri, Yazan M; Eggers, Thomas; McCallum, Grant; Durand, Dominique M

2015-08-01

Peripheral nerves carry neural signals that could be used to control hybrid bionic systems. Cuff electrodes provide a robust and stable interface but the recorded signal amplitude is small (concept of hardware averaging to nerve recordings obtained with cuff electrodes. An optimization procedure is developed to minimize noise and power simultaneously. The novel design was based on existing neural amplifiers (Intan Technologies, LLC) and is validated with signals obtained from the FINE in chronic dog experiments. We showed that hardware averaging leads to a reduction in the total recording noise by a factor of 1/√N or less depending on the source resistance. Chronic recording of physiological activity with FINE using the presented design showed significant improvement on the recorded baseline noise with at least two parallel operation transconductance amplifiers leading to a 46.1% reduction at N = 8. The functionality of these recordings was quantified by the SNR improvement and shown to be significant for N = 3 or more. The present design was shown to be capable of generating hardware averaging on noise improvement for neural recording with cuff electrodes, and can accommodate the presence of high source impedances that are associated with the miniaturized contacts and the high channel count in electrode arrays. This technique can be adopted for other applications where miniaturized and implantable multichannel acquisition systems with ultra-low noise and low power are required.

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.

Autonomous data acquisition system for Paks NPP process noise signals

International Nuclear Information System (INIS)

Lipcsei, S.; Kiss, S.; Czibok, T.; Dezso, Z.; Horvath, Cs.

2005-01-01

A prototype of a new concept noise diagnostics data acquisition system has been developed recently to renew the aged present system. This new system is capable of collecting the whole available noise signal set simultaneously. Signal plugging and data acquisition are performed by autonomous systems (installed at each reactor unit) that are controlled through the standard plant network from a central computer installed at a suitable location. Experts can use this central unit to process and archive data series downloaded from the reactor units. This central unit also provides selected noise diagnostics information for other departments. The paper describes the hardware and software architecture of the new system in detail, emphasising the potential benefits of the new approach. (author)

The Signal and Noise Analysis of Direct Conversion EHM Transceivers

Directory of Open Access Journals (Sweden)

Shayegh

2006-01-01

Full Text Available A direct conversion modulator-demodulator with even harmonic mixers with emphasis on noise analysis is presented. The circuits consist of even harmonic mixers (EHMs realized with antiparallel diode pairs (APDPs. We evaluate the different levels of I/Q imbalances and DC offsets and use signal space concepts to analyze the bit error rate (BER of the proposed transceiver using M-ary QAM schemes. Moreover, the simultaneous analysis of the signal and noise has been presented.

Random noise can help to improve synchronization of excimer laser pulses.

Science.gov (United States)

Mingesz, Róbert; Barna, Angéla; Gingl, Zoltán; Mellár, János

2016-02-01

Recently, we have reported on a compact microcontroller-based unit developed to accurately synchronize excimer laser pulses (Mingesz et al. 2012 Fluct. Noise Lett. 11, 1240007 (doi:10.1142/S021947751240007X)). We have shown that dithering based on random jitter noise plus pseudorandom numbers can be used in the digital control system to radically reduce the long-term drift of the laser pulse from the trigger and to improve the accuracy of the synchronization. In this update paper, we present our new experimental results obtained by the use of the delay-controller unit to tune the timing of a KrF excimer laser as an addition to our previous numerical simulation results. The hardware was interfaced to the laser using optical signal paths in order to reduce sensitivity to electromagnetic interference and the control algorithm tested by simulations was applied in the experiments. We have found that the system is able to reduce the delay uncertainty very close to the theoretical limit and performs well in real applications. The simple, compact and flexible system is universal enough to also be used in various multidisciplinary applications.

Complex diffusion process for noise reduction

DEFF Research Database (Denmark)

Nadernejad, Ehsan; Barari, A.

2014-01-01

equations (PDEs) in image restoration and de-noising prompted many researchers to search for an improvement in the technique. In this paper, a new method is presented for signal de-noising, based on PDEs and Schrodinger equations, named as complex diffusion process (CDP). This method assumes that variations...... for signal de-noising. To evaluate the performance of the proposed method, a number of experiments have been performed using Sinusoid, multi-component and FM signals cluttered with noise. The results indicate that the proposed method outperforms the approaches for signal de-noising known in prior art....

A comparative study of chaotic and white noise signals in digital watermarking

International Nuclear Information System (INIS)

Mooney, Aidan; Keating, John G.; Pitas, Ioannis

2008-01-01

Digital watermarking is an ever increasing and important discipline, especially in the modern electronically-driven world. Watermarking aims to embed a piece of information into digital documents which their owner can use to prove that the document is theirs, at a later stage. In this paper, performance analysis of watermarking schemes is performed on white noise sequences and chaotic sequences for the purpose of watermark generation. Pseudorandom sequences are compared with chaotic sequences generated from the chaotic skew tent map. In particular, analysis is performed on highpass signals generated from both these watermark generation schemes, along with analysis on lowpass watermarks and white noise watermarks. This analysis focuses on the watermarked images after they have been subjected to common image distortion attacks. It is shown that signals generated from highpass chaotic signals have superior performance than highpass noise signals, in the presence of such attacks. It is also shown that watermarks generated from lowpass chaotic signals have superior performance over the other signal types analysed

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

Electrocardiogram (ECG Signal Modeling and Noise Reduction Using Hopfield Neural Networks

Directory of Open Access Journals (Sweden)

F. Bagheri

2013-02-01

Full Text Available The Electrocardiogram (ECG signal is one of the diagnosing approaches to detect heart disease. In this study the Hopfield Neural Network (HNN is applied and proposed for ECG signal modeling and noise reduction. The Hopfield Neural Network (HNN is a recurrent neural network that stores the information in a dynamic stable pattern. This algorithm retrieves a pattern stored in memory in response to the presentation of an incomplete or noisy version of that pattern. Computer simulation results show that this method can successfully model the ECG signal and remove high-frequency noise.

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

Cancelation and its simulation using Matlab according to active noise control case study of automotive noise silencer

Science.gov (United States)

Alfisyahrin; Isranuri, I.

2018-02-01

Active Noise Control is a technique to overcome noisy with noise or sound countered with sound in scientific terminology i.e signal countered with signals. This technique can be used to dampen relevant noise in accordance with the wishes of the engineering task and reducing automotive muffler noise to a minimum. Objective of this study is to develop a Active Noise Control which should cancel the noise of automotive Exhaust (Silencer) through Signal Processing Simulation methods. Noise generator of Active Noise Control is to make the opponent signal amplitude and frequency of the automotive noise. The steps are: Firstly, the noise of automotive silencer was measured to characterize the automotive noise that its amplitude and frequency which intended to be expressed. The opposed sound which having similar character with the signal source should be generated by signal function. A comparison between the data which has been completed with simulation calculations Fourier transform field data is data that has been captured on the muffler (noise silencer) Toyota Kijang Capsule assembly 2009. MATLAB is used to simulate how the signal processing noise generated by exhaust (silencer) using FFT. This opponent is inverted phase signal from the signal source 180° conducted by Instruments of Signal Noise Generators. The process of noise cancelation examined through simulation using computer software simulation. The result is obtained that attenuation of sound (noise cancellation) has a difference of 33.7%. This value is obtained from the comparison of the value of the signal source and the signal value of the opponent. So it can be concluded that the noisy signal can be attenuated by 33.7%.

Noise and signal properties in PSF-based fully 3D PET image reconstruction: an experimental evaluation

International Nuclear Information System (INIS)

Tong, S; Alessio, A M; Kinahan, P E

2010-01-01

The addition of accurate system modeling in PET image reconstruction results in images with distinct noise texture and characteristics. In particular, the incorporation of point spread functions (PSF) into the system model has been shown to visually reduce image noise, but the noise properties have not been thoroughly studied. This work offers a systematic evaluation of noise and signal properties in different combinations of reconstruction methods and parameters. We evaluate two fully 3D PET reconstruction algorithms: (1) OSEM with exact scanner line of response modeled (OSEM+LOR), (2) OSEM with line of response and a measured point spread function incorporated (OSEM+LOR+PSF), in combination with the effects of four post-reconstruction filtering parameters and 1-10 iterations, representing a range of clinically acceptable settings. We used a modified NEMA image quality (IQ) phantom, which was filled with 68 Ge and consisted of six hot spheres of different sizes with a target/background ratio of 4:1. The phantom was scanned 50 times in 3D mode on a clinical system to provide independent noise realizations. Data were reconstructed with OSEM+LOR and OSEM+LOR+PSF using different reconstruction parameters, and our implementations of the algorithms match the vendor's product algorithms. With access to multiple realizations, background noise characteristics were quantified with four metrics. Image roughness and the standard deviation image measured the pixel-to-pixel variation; background variability and ensemble noise quantified the region-to-region variation. Image roughness is the image noise perceived when viewing an individual image. At matched iterations, the addition of PSF leads to images with less noise defined as image roughness (reduced by 35% for unfiltered data) and as the standard deviation image, while it has no effect on background variability or ensemble noise. In terms of signal to noise performance, PSF-based reconstruction has a 7% improvement in

Noise temperature improvement for magnetic fusion plasma millimeter wave imaging systems

Energy Technology Data Exchange (ETDEWEB)

Lai, J.; Domier, C. W.; Luhmann, N. C. [Department of Electrical and Computer Engineering, University of California at Davis, Davis, California 95616 (United States)

2014-03-15

Significant progress has been made in the imaging and visualization of magnetohydrodynamic and microturbulence phenomena in magnetic fusion plasmas [B. Tobias et al., Plasma Fusion Res. 6, 2106042 (2011)]. Of particular importance have been microwave electron cyclotron emission imaging and microwave imaging reflectometry systems for imaging T{sub e} and n{sub e} fluctuations. These instruments have employed heterodyne receiver arrays with Schottky diode mixer elements directly connected to individual antennas. Consequently, the noise temperature has been strongly determined by the conversion loss with typical noise temperatures of ∼60 000 K. However, this can be significantly improved by making use of recent advances in Monolithic Microwave Integrated Circuit chip low noise amplifiers to insert a pre-amplifier in front of the Schottky diode mixer element. In a proof-of-principle design at V-Band (50–75 GHz), significant improvement of noise temperature from the current 60 000 K to measured 4000 K has been obtained.

Noise temperature improvement for magnetic fusion plasma millimeter wave imaging systems.

Science.gov (United States)

Lai, J; Domier, C W; Luhmann, N C

2014-03-01

Significant progress has been made in the imaging and visualization of magnetohydrodynamic and microturbulence phenomena in magnetic fusion plasmas [B. Tobias et al., Plasma Fusion Res. 6, 2106042 (2011)]. Of particular importance have been microwave electron cyclotron emission imaging and microwave imaging reflectometry systems for imaging T(e) and n(e) fluctuations. These instruments have employed heterodyne receiver arrays with Schottky diode mixer elements directly connected to individual antennas. Consequently, the noise temperature has been strongly determined by the conversion loss with typical noise temperatures of ~60,000 K. However, this can be significantly improved by making use of recent advances in Monolithic Microwave Integrated Circuit chip low noise amplifiers to insert a pre-amplifier in front of the Schottky diode mixer element. In a proof-of-principle design at V-Band (50-75 GHz), significant improvement of noise temperature from the current 60,000 K to measured 4000 K has been obtained.

Noise temperature improvement for magnetic fusion plasma millimeter wave imaging systems

International Nuclear Information System (INIS)

Lai, J.; Domier, C. W.; Luhmann, N. C.

2014-01-01

Significant progress has been made in the imaging and visualization of magnetohydrodynamic and microturbulence phenomena in magnetic fusion plasmas [B. Tobias et al., Plasma Fusion Res. 6, 2106042 (2011)]. Of particular importance have been microwave electron cyclotron emission imaging and microwave imaging reflectometry systems for imaging T e and n e fluctuations. These instruments have employed heterodyne receiver arrays with Schottky diode mixer elements directly connected to individual antennas. Consequently, the noise temperature has been strongly determined by the conversion loss with typical noise temperatures of ∼60 000 K. However, this can be significantly improved by making use of recent advances in Monolithic Microwave Integrated Circuit chip low noise amplifiers to insert a pre-amplifier in front of the Schottky diode mixer element. In a proof-of-principle design at V-Band (50–75 GHz), significant improvement of noise temperature from the current 60 000 K to measured 4000 K has been obtained

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.

The Efficacy of Short-term Gated Audiovisual Speech Training for Improving Auditory Sentence Identification in Noise in Elderly Hearing Aid Users

Science.gov (United States)

Moradi, Shahram; Wahlin, Anna; Hällgren, Mathias; Rönnberg, Jerker; Lidestam, Björn

2017-01-01

This study aimed to examine the efficacy and maintenance of short-term (one-session) gated audiovisual speech training for improving auditory sentence identification in noise in experienced elderly hearing-aid users. Twenty-five hearing aid users (16 men and 9 women), with an average age of 70.8 years, were randomly divided into an experimental (audiovisual training, n = 14) and a control (auditory training, n = 11) group. Participants underwent gated speech identification tasks comprising Swedish consonants and words presented at 65 dB sound pressure level with a 0 dB signal-to-noise ratio (steady-state broadband noise), in audiovisual or auditory-only training conditions. The Hearing-in-Noise Test was employed to measure participants’ auditory sentence identification in noise before the training (pre-test), promptly after training (post-test), and 1 month after training (one-month follow-up). The results showed that audiovisual training improved auditory sentence identification in noise promptly after the training (post-test vs. pre-test scores); furthermore, this improvement was maintained 1 month after the training (one-month follow-up vs. pre-test scores). Such improvement was not observed in the control group, neither promptly after the training nor at the one-month follow-up. However, no significant between-groups difference nor an interaction between groups and session was observed. Conclusion: Audiovisual training may be considered in aural rehabilitation of hearing aid users to improve listening capabilities in noisy conditions. However, the lack of a significant between-groups effect (audiovisual vs. auditory) or an interaction between group and session calls for further research. PMID:28348542

Measuring multielectron beam imaging fidelity with a signal-to-noise ratio analysis

Science.gov (United States)

Mukhtar, Maseeh; Bunday, Benjamin D.; Quoi, Kathy; Malloy, Matt; Thiel, Brad

2016-07-01

Java Monte Carlo Simulator for Secondary Electrons (JMONSEL) simulations are used to generate expected imaging responses of chosen test cases of patterns and defects with the ability to vary parameters for beam energy, spot size, pixel size, and/or defect material and form factor. The patterns are representative of the design rules for an aggressively scaled FinFET-type design. With these simulated images and resulting shot noise, a signal-to-noise framework is developed, which relates to defect detection probabilities. Additionally, with this infrastructure, the effect of detection chain noise and frequency-dependent system response can be made, allowing for targeting of best recipe parameters for multielectron beam inspection validation experiments. Ultimately, these results should lead to insights into how such parameters will impact tool design, including necessary doses for defect detection and estimations of scanning speeds for achieving high throughput for high-volume manufacturing.

Optimization of number and signal to noise ratio radiographs for defects 3D reconstruction in industrial control

International Nuclear Information System (INIS)

Bruandet, J.-P.

2001-01-01

Among numerous techniques for non-destructive evaluation (NOE), X-rays systems are well suited to inspect inner objects. Acquiring several radiographs of inspected objects under different points of view enables to recover a three dimensional structural information. In this NOE application, a tomographic testing is considered. This work deals with two tomographic testing optimizations in order to improve the characterization of defects that may occur into metallic welds. The first one consists in the optimization of the acquisition strategy. Because tomographic testing is made on-line, the total duration for image acquisition is fixed, limiting the number of available views. Hence, for a given acquisition duration, it is possible either to acquire a very limited number of radiographs with a good signal to noise ratio in each single acquisition or a larger number of radiographs with a limited signal to noise ratio. The second one consists in optimizing the 3D reconstruction algorithms from a limited number of cone-beam projections. To manage the lack of data, we first used algebraic reconstruction algorithms such as ART or regularized ICM. In terms of acquisition strategy optimization, an increase of the number of projections was proved to be valuable. Taking into account specific prior knowledge such as support constraint or physical noise model in attenuation images also improved reconstruction quality. Then, a new regularized region based reconstruction approach was developed. Defects to reconstruct are binary (lack of material in a homogeneous object). As a consequence, they are entirely described by their shapes. Because the number of defects to recover is unknown and is totally arbitrary, a level set formulation allowing handling topological changes was used. Results obtained with a regularized level-set reconstruction algorithm are optimistic in the proposed context. (author) [fr

Stochastic resonance: noise-enhanced order

International Nuclear Information System (INIS)

Anishchenko, Vadim S; Neiman, Arkady B; Moss, F; Shimansky-Geier, L

1999-01-01

Stochastic resonance (SR) provides a glaring example of a noise-induced transition in a nonlinear system driven by an information signal and noise simultaneously. In the regime of SR some characteristics of the information signal (amplification factor, signal-to-noise ratio, the degrees of coherence and of order, etc.) at the output of the system are significantly improved at a certain optimal noise level. SR is realized only in nonlinear systems for which a noise-intensity-controlled characteristic time becomes available. In the present review the physical mechanism and methods of theoretical description of SR are briefly discussed. SR features determined by the structure of the information signal, noise statistics and properties of particular systems with SR are studied. A nontrivial phenomenon of stochastic synchronization defined as locking of the instantaneous phase and switching frequency of a bistable system by external periodic force is analyzed in detail. Stochastic synchronization is explored in single and coupled bistable oscillators, including ensembles. The effects of SR and stochastic synchronization of ensembles of stochastic resonators are studied both with and without coupling between the elements. SR is considered in dynamical and nondynamical (threshold) systems. The SR effect is analyzed from the viewpoint of information and entropy characteristics of the signal, which determine the degree of order or self-organization in the system. Applications of the SR concept to explaining the results of a series of biological experiments are discussed. (reviews of topical problems)

Stochastic resonance: noise-enhanced order

Energy Technology Data Exchange (ETDEWEB)

Anishchenko, Vadim S; Neiman, Arkady B [N.G. Chernyshevskii Saratov State University, Saratov (Russian Federation); Moss, F [Department of Physics and Astronomy, University of Missouri at St. Louis (United States); Shimansky-Geier, L [Humboldt University at Berlin (Germany)

1999-01-31

Stochastic resonance (SR) provides a glaring example of a noise-induced transition in a nonlinear system driven by an information signal and noise simultaneously. In the regime of SR some characteristics of the information signal (amplification factor, signal-to-noise ratio, the degrees of coherence and of order, etc.) at the output of the system are significantly improved at a certain optimal noise level. SR is realized only in nonlinear systems for which a noise-intensity-controlled characteristic time becomes available. In the present review the physical mechanism and methods of theoretical description of SR are briefly discussed. SR features determined by the structure of the information signal, noise statistics and properties of particular systems with SR are studied. A nontrivial phenomenon of stochastic synchronization defined as locking of the instantaneous phase and switching frequency of a bistable system by external periodic force is analyzed in detail. Stochastic synchronization is explored in single and coupled bistable oscillators, including ensembles. The effects of SR and stochastic synchronization of ensembles of stochastic resonators are studied both with and without coupling between the elements. SR is considered in dynamical and nondynamical (threshold) systems. The SR effect is analyzed from the viewpoint of information and entropy characteristics of the signal, which determine the degree of order or self-organization in the system. Applications of the SR concept to explaining the results of a series of biological experiments are discussed. (reviews of topical problems)

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

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...

Stochastic resonance and stability for a stochastic metapopulation system subjected to non-Gaussian noise and multiplicative periodic signal

International Nuclear Information System (INIS)

Kang-Kang, Wang; Xian-Bin, Liu; Yu, Zhou

2015-01-01

In this paper, the stability and stochastic resonance (SR) phenomenon induced by the multiplicative periodic signal for a metapopulation system driven by the additive Gaussian noise, multiplicative non-Gaussian noise and noise correlation time is investigated. By using the fast descent method, unified colored noise approximation and McNamara and Wiesenfeld’s SR theory, the analytical expressions of the stationary probability distribution function and signal-to-noise ratio (SNR) are derived in the adiabatic limit. Via numerical calculations, each effect of the addictive noise intensity, the multiplicative noise intensity and the correlation time upon the steady state probability distribution function and the SNR is discussed, respectively. It is shown that multiplicative, additive noises and the departure parameter from the Gaussian noise can all destroy the stability of the population system. However, the noise correlation time can consolidate the stability of the system. On the other hand, the correlation time always plays an important role in motivating the SR and enhancing the SNR. Under different parameter conditions of the system, the multiplicative, additive noises and the departure parameter can not only excite SR phenomenon, but also restrain the SR phenomenon, which demonstrates the complexity of different noises upon the nonlinear system. (paper)

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...

Signal to noise ratio enhancement for Eddy Current testing of steam generator tubes in PWR's

International Nuclear Information System (INIS)

Georgel, B.

1985-01-01

Noise reduction is a compulsory task when we try to recognize and characterize flaws. The signals we deal with come from Eddy Current testings of steam generator steel tubes. We point out the need for a spectral invariant in digital spectral analysis of 2 components signals. We make clear the pros and cons of classical passband filtering and suggest the use of a new noise cancellation method first discussed by Moriwaki and Tlusty. We generalize this tricky technique and prove it is a very special case of the well-known Wiener filter. In that sense the M-T method is shown to be optimal. 6 refs

An adaptive segment method for smoothing lidar signal based on noise estimation

Science.gov (United States)

Wang, Yuzhao; Luo, Pingping

2014-10-01

An adaptive segmentation smoothing method (ASSM) is introduced in the paper to smooth the signal and suppress the noise. In the ASSM, the noise is defined as the 3σ of the background signal. An integer number N is defined for finding the changing positions in the signal curve. If the difference of adjacent two points is greater than 3Nσ, the position is recorded as an end point of the smoothing segment. All the end points detected as above are recorded and the curves between them will be smoothed separately. In the traditional method, the end points of the smoothing windows in the signals are fixed. The ASSM creates changing end points in different signals and the smoothing windows could be set adaptively. The windows are always set as the half of the segmentations and then the average smoothing method will be applied in the segmentations. The Iterative process is required for reducing the end-point aberration effect in the average smoothing method and two or three times are enough. In ASSM, the signals are smoothed in the spacial area nor frequent area, that means the frequent disturbance will be avoided. A lidar echo was simulated in the experimental work. The echo was supposed to be created by a space-born lidar (e.g. CALIOP). And white Gaussian noise was added to the echo to act as the random noise resulted from environment and the detector. The novel method, ASSM, was applied to the noisy echo to filter the noise. In the test, N was set to 3 and the Iteration time is two. The results show that, the signal could be smoothed adaptively by the ASSM, but the N and the Iteration time might be optimized when the ASSM is applied in a different lidar.

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.

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

KAUST Repository

Laleg-Kirati, Taous-Meriem; Zhang, Jiayu; Achten, Eric; Serrai, Hacene

2016-01-01

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.

Performance Analysis of the Effect of Pulsed-Noise Interference on WLAN Signals Transmitted Over a Nakagami Fading Channel

National Research Council Canada - National Science Library

Tsoumanis, Andreas

2004-01-01

...) coding with soft decision decoding (SDD) and maximum- likelihood detection improves performance as compared to uncoded signals, In addition, the combination of maximum-likelihood detection and error connection coding renders pulsed-noise...

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.

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.

Frequency-domain method for separating signal and noise

Institute of Scientific and Technical Information of China (English)

无

2000-01-01

A new method for separation of signal and noise (SSN) is put forward. Frequency is redefined according to the features of signal and its derivative in the sampl ing time interval, thus double orthogonal basis (DOB) is constructed so that a signal can be precisely signified with a linear combination of low-frequency DOB . Under joint consideration in time domain (TD) and frequency domain (FD), a method on SSN with high accuracy is derived and a matched algorithm is designed and analyzed. This method is applicable to SSN in multiple frequency bands, and convenient in applying signal characteristics in TD and FD synthetically with highe raccuracy.

Frequency-domain method for separating signal and noise

Institute of Scientific and Technical Information of China (English)

王正明; 段晓君

2000-01-01

A new method for separation of signal and noise (SSN) is put forward. Frequency is redefined according to the features of signal and its derivative in the sampling time interval, thus double orthogonal basis (DOB) is constructed so that a signal can be precisely signified with a linear combination of low-frequency DOB. Under joint consideration in time domain (TD) and frequency domain (FD), a method on SSN with high accuracy is derived and a matched algorithm is designed and analyzed. This method is applicable to SSN in multiple frequency bands, and convenient in applying signal characteristics in TD and FD synthetically with higher accuracy.

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.

Active noise control in a duct to cancel broadband noise

Science.gov (United States)

Chen, Kuan-Chun; Chang, Cheng-Yuan; Kuo, Sen M.

2017-09-01

The paper presents cancelling duct noises by using the active noise control (ANC) techniques. We use the single channel feed forward algorithm with feedback neutralization to realize ANC. Several kinds of ducts noises including tonal noises, sweep tonal signals, and white noise had investigated. Experimental results show that the proposed ANC system can cancel these noises in a PVC duct very well. The noise reduction of white noise can be up to 20 dB.

Signal-to-noise ratio analysis and evaluation of the Hadamard imaging technique

Science.gov (United States)

Jobson, D. J.; Katzberg, S. J.; Spiers, R. B., Jr.

1977-01-01

The signal-to-noise ratio performance of the Hadamard imaging technique is analyzed and an experimental evaluation of a laboratory Hadamard imager is presented. A comparison between the performances of Hadamard and conventional imaging techniques shows that the Hadamard technique is superior only when the imaging objective lens is required to have an effective F (focus) number of about 2 or slower.

Signal-to-noise ratio measurement in parallel MRI with subtraction mapping and consecutive methods

International Nuclear Information System (INIS)

Imai, Hiroshi; Miyati, Tosiaki; Ogura, Akio; Doi, Tsukasa; Tsuchihashi, Toshio; Machida, Yoshio; Kobayashi, Masato; Shimizu, Kouzou; Kitou, Yoshihiro

2008-01-01

When measuring the signal-to-noise ratio (SNR) of an image the used parallel magnetic resonance imaging, it was confirmed that there was a problem in the application of past SNR measurement. With the method of measuring the noise from the background signal, SNR with parallel imaging was higher than that without parallel imaging. In the subtraction method (NEMA standard), which sets a wide region of interest, the white noise was not evaluated correctly although SNR was close to the theoretical value. We proposed two techniques because SNR in parallel imaging was not uniform according to inhomogeneity of the coil sensitivity distribution and geometry factor. Using the first method (subtraction mapping), two images were scanned with identical parameters. The SNR in each pixel divided the running mean (7 by 7 pixels in neighborhood) by standard deviation/√2 in the same region of interest. Using the second (consecutive) method, more than fifty consecutive scans of the uniform phantom were obtained with identical scan parameters. Then the SNR was calculated from the ratio of mean signal intensity to the standard deviation in each pixel on a series of images. Moreover, geometry factors were calculated from SNRs with and without parallel imaging. The SNR and geometry factor using parallel imaging in the subtraction mapping method agreed with those of the consecutive method. Both methods make it possible to obtain a more detailed determination of SNR in parallel imaging and to calculate the geometry factor. (author)

When noise is beneficial for sensory encoding: Noise adaptation can improve face processing.

Science.gov (United States)

Menzel, Claudia; Hayn-Leichsenring, Gregor U; Redies, Christoph; Németh, Kornél; Kovács, Gyula

2017-10-01

The presence of noise usually impairs the processing of a stimulus. Here, we studied the effects of noise on face processing and show, for the first time, that adaptation to noise patterns has beneficial effects on face perception. We used noiseless faces that were either surrounded by random noise or presented on a uniform background as stimuli. In addition, the faces were either preceded by noise adaptors or not. Moreover, we varied the statistics of the noise so that its spectral slope either matched that of the faces or it was steeper or shallower. Results of parallel ERP recordings showed that the background noise reduces the amplitude of the face-evoked N170, indicating less intensive face processing. Adaptation to a noise pattern, however, led to reduced P1 and enhanced N170 amplitudes as well as to a better behavioral performance in two of the three noise conditions. This effect was also augmented by the presence of background noise around the target stimuli. Additionally, the spectral slope of the noise pattern affected the size of the P1, N170 and P2 amplitudes. We reason that the observed effects are due to the selective adaptation of noise-sensitive neurons present in the face-processing cortical areas, which may enhance the signal-to-noise-ratio. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Effects of signal salience and noise on performance and stress in an abbreviated vigil

Science.gov (United States)

Helton, William Stokely

Vigilance or sustained attention tasks traditionally require observers to detect predetermined signals that occur unpredictably over periods of 30 min to several hours (Warm, 1984). These tasks are taxing and have been useful in revealing the effects of stress agents, such as infectious disease and drugs, on human performance (Alluisi, 1969; Damos & Parker, 1994; Warm, 1993). However, their long duration has been an inconvenience. Recently, Temple and his associates (Temple et al., 2000) developed an abbreviated 12-min vigilance task that duplicates many of the findings with longer duration vigils. The present study was designed to explore further the similarity of the abbreviated task to long-duration vigils by investigating the effects of signal salience and jet-aircraft engine noise on performance, operator stress, and coping strategies. Forty-eight observers (24 males and 24 females) were assigned at random to each of four conditions resulting from the factorial combination of signal salience (high and low contrast signals) and background noise (quiet and jet-aircraft noise). As is the case with long-duration vigils (Warm, 1993), signal detection in the abbreviated task was poorer for low salience than for high salience signals. In addition, stress scores, as indexed by the Dundee Stress State Questionnaire (Matthews, Joiner, Gilliland, Campbell, & Falconer, 1999), were elevated in the low as compared to the high salience condition. Unlike longer vigils, however, (Becker, Warm, Dember, & Hancock, 1996), signal detection in the abbreviated task was superior in the presence of aircraft noise than in quiet. Noise also attenuated the stress of the vigil, a result that is counter to previous findings regarding the effects of noise in a variety of other scenarios (Clark, 1984). Examination of observers' coping responses, as assessed by the Coping Inventory for Task Situations (Matthews & Campbell, 1998), indicated that problem-focused coping was the overwhelming

High signal-to-noise ratio sensing with Shack–Hartmann wavefront sensor based on auto gain control of electron multiplying CCD

International Nuclear Information System (INIS)

Zhu Zhao-Yi; Li Da-Yu; Hu Li-Fa; Mu Quan-Quan; Yang Cheng-Liang; Cao Zhao-Liang; Xuan Li

2016-01-01

High signal-to-noise ratio can be achieved with the electron multiplying charge-coupled-device (EMCCD) applied in the Shack–Hartmann wavefront sensor (S–H WFS) in adaptive optics (AO). However, when the brightness of the target changes in a large scale, the fixed electron multiplying (EM) gain will not be suited to the sensing limitation. Therefore an auto-gain-control method based on the brightness of light-spots array in S–H WFS is proposed in this paper. The control value is the average of the maximum signals of every light spot in an array, which has been demonstrated to be kept stable even under the influence of some noise and turbulence, and sensitive enough to the change of target brightness. A goal value is needed in the control process and it is predetermined based on the characters of EMCCD. Simulations and experiments have demonstrated that this auto-gain-control method is valid and robust, the sensing SNR reaches the maximum for the corresponding signal level, and especially is greatly improved for those dim targets from 6 to 4 magnitude in the visual band. (special topic)

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.

Preliminary study of acoustic emission (ae) noise signal identification for crude oil storage tank

International Nuclear Information System (INIS)

Nurul Ain Ahmad Latif; Shukri Mohd

2008-08-01

This preliminary work was carried out to simulate the Acoustic Emission (AE) signal contributed by pitting corrosion, and noise signal from environment during crude oil storage tanks monitoring. The purpose of this study is to prove that acoustic emission (AE) could be used to detect the formation of pitting corrosion in the crude oil storage tank and differentiated it from other sources of noise signal. In this study, the pitting corrosion was simulated by inducing low voltage and low amperage current onto the crude oil storage tank material (ASTM 516 G 70). Water drop, air blow and surface rubbing were applied onto the specimen surface. To simulate the noise signal produce by rain fall, wind blow and other sources of noise during AE crude oil storage tanks monitoring. AE sensor was attached onto the other surface of specimen to acquire all of these AE signals which then has send to AE DiSP 24 data acquisition system for signal conditioning. AE win software has been used to analyse this entire signal. It is found that, simulated pitting corrosion could be detected by AE system and differentiated from other sources of noise by using amplitude analysis. From the amplitude analysis is shown that 20-30 dB is the range amplitude for the blow test, 50-60 dB for surface rubbing test and over than 60 dB for water drop test. (Author)

Relationship of signal-to-noise ratio with acquisition parameters in MRI for a given contrast

International Nuclear Information System (INIS)

Bittoun, J.; Leroy-Willig, A.; Idy, I.; Halimi, P.; Syrota, A.; Desgrez, A.; Saint-Jalmes, H.

1987-01-01

The signal-to-noise ratio (SNR) is certainly the most important characteristic of medical images, since the spatial resolution and the visualization of contrast are dependent on its value. On the other hand, modifying an acquisition variable in magnetic resonance imaging, in order to improve spatial resolution for example, may induce a SNR loss and finally alter the image quality. We have studied a theoretical relation between SNR and 2DFT method acquisition variables with the exception of parameters such as TR, TE and TI; these parameters are determined by the desired contrast in order to confirm a diagnosis. According to this relation SNR is proportional to each dimension of the slice, and to the square root of the number of averaged signals; it is inversely proportional to the number of frequency points and to the square root of the number of phase points. This relation was experimentally verified with phantoms and on an MR system at 1.5 T. It was then plotted as a multiple-entry graph on which operators at the console can read the number of averaged signals necessary to compensate SNR loss induced by a modification of other parameters [fr

Correlated cone noise decreases rod signal contributions to the post-receptoral pathways.

Science.gov (United States)

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

2018-04-01

This study investigated how invisible extrinsic temporal white noise that correlates with the activity of one of the three [magnocellular (MC), parvocellular (PC), or koniocellular (KC)] post-receptoral pathways alters mesopic rod signaling. A four-primary photostimulator provided independent control of the rod and three cone photoreceptor excitations. The rod contributions to the three post-receptoral pathways were estimated by perceptually matching a 20% contrast rod pulse by independently varying the LMS (MC pathway), +L-M (PC pathway), and S-cone (KC pathway) excitations. We show that extrinsic cone noise caused a predominant decrease in the overall magnitude and ratio of the rod contributions to each pathway. Thus, the relative cone activity in the post-receptoral pathways determines the relative mesopic rod inputs to each pathway.

Improving the accuracy of smart devices to measure noise exposure.

Science.gov (United States)

Roberts, Benjamin; Kardous, Chucri; Neitzel, Richard

2016-11-01

Occupational noise exposure is one of the most frequent hazards present in the workplace; up to 22 million workers have potentially hazardous noise exposures in the U.S. As a result, noise-induced hearing loss is one of the most common occupational injuries in the U.S. Workers in manufacturing, construction, and the military are at the highest risk for hearing loss. Despite the large number of people exposed to high levels of noise at work, many occupations have not been adequately evaluated for noise exposure. The objective of this experiment was to investigate whether or not iOS smartphones and other smart devices (Apple iPhones and iPods) could be used as reliable instruments to measure noise exposures. For this experiment three different types of microphones were tested with a single model of iPod and three generations of iPhones: the internal microphones on the device, a low-end lapel microphone, and a high-end lapel microphone marketed as being compliant with the International Electrotechnical Commission's (IEC) standard for a Class 2-microphone. All possible combinations of microphones and noise measurement applications were tested in a controlled environment using several different levels of pink noise ranging from 60-100 dBA. Results were compared to simultaneous measurements made using a Type 1 sound level measurement system. Analysis of variance and Tukey's honest significant difference (HSD) test were used to determine if the results differed by microphone or noise measurement application. Levels measured with external microphones combined with certain noise measurement applications did not differ significantly from levels measured with the Type 1 sound measurement system. Results showed that it may be possible to use iOS smartphones and smart devices, with specific combinations of measurement applications and calibrated external microphones, to collect reliable, occupational noise exposure data under certain conditions and within the limitations of the

Practical Ranges of Loudness Levels of Various Types of Environmental Noise, Including Traffic Noise, Aircraft Noise, and Industrial Noise

Directory of Open Access Journals (Sweden)

Sabine A. Janssen

2011-05-01

Full Text Available In environmental noise control one commonly employs the A-weighted sound level as an approximate measure of the effect of noise on people. A measure that is more closely related to direct human perception of noise is the loudness level. At constant A-weighted sound level, the loudness level of a noise signal varies considerably with the shape of the frequency spectrum of the noise signal. In particular the bandwidth of the spectrum has a large effect on the loudness level, due to the effect of critical bands in the human hearing system. The low-frequency content of the spectrum also has an effect on the loudness level. In this note the relation between loudness level and A-weighted sound level is analyzed for various environmental noise spectra, including spectra of traffic noise, aircraft noise, and industrial noise. From loudness levels calculated for these environmental noise spectra, diagrams are constructed that show the relation between loudness level, A‑weighted sound level, and shape of the spectrum. The diagrams show that the upper limits of the loudness level for broadband environmental noise spectra are about 20 to 40 phon higher than the lower limits for narrowband spectra, which correspond to the loudness levels of pure tones. The diagrams are useful for assessing limitations and potential improvements of environmental noise control methods and policy based on A-weighted sound levels.

Stochastic model for detection of signals in noise

OpenAIRE

Klein, Stanley A.; Levi, Dennis M.

2009-01-01

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 o...

Signal-to-noise ratio, contrast-to-noise ratio and their trade-offs with resolution in axial-shear strain elastography

International Nuclear Information System (INIS)

Thitaikumar, Arun; Krouskop, Thomas A; Ophir, Jonathan

2007-01-01

In axial-shear strain elastography, the local axial-shear strain resulting from the application of quasi-static axial compression to an inhomogeneous material is imaged. In this paper, we investigated the image quality of the axial-shear strain estimates in terms of the signal-to-noise ratio (SNR asse ) and contrast-to-noise ratio (CNR asse ) using simulations and experiments. Specifically, we investigated the influence of the system parameters (beamwidth, transducer element pitch and bandwidth), signal processing parameters (correlation window length and axial window shift) and mechanical parameters (Young's modulus contrast, applied axial strain) on the SNR asse and CNR asse . The results of the study show that the CNR asse (SNR asse ) is maximum for axial-shear strain values in the range of 0.005-0.03. For the inclusion/background modulus contrast range considered in this study ( asse (SNR asse ) is maximum for applied axial compressive strain values in the range of 0.005%-0.03%. This suggests that the RF data acquired during axial elastography can be used to obtain axial-shear strain elastograms, since this range is typically used in axial elastography as well. The CNR asse (SNR asse ) remains almost constant with an increase in the beamwidth while it increases as the pitch increases. As expected, the axial shift had only a weak influence on the CNR asse (SNR asse ) of the axial-shear strain estimates. We observed that the differential estimates of the axial-shear strain involve a trade-off between the CNR asse (SNR asse ) and the spatial resolution only with respect to pitch and not with respect to signal processing parameters. Simulation studies were performed to confirm such an observation. The results demonstrate a trade-off between CNR asse and the resolution with respect to pitch

Simulation for noise cancellation using LMS adaptive filter

Science.gov (United States)

Lee, Jia-Haw; Ooi, Lu-Ean; Ko, Ying-Hao; Teoh, Choe-Yung

2017-06-01

In this paper, the fundamental algorithm of noise cancellation, Least Mean Square (LMS) algorithm is studied and enhanced with adaptive filter. The simulation of the noise cancellation using LMS adaptive filter algorithm is developed. The noise corrupted speech signal and the engine noise signal are used as inputs for LMS adaptive filter algorithm. The filtered signal is compared to the original noise-free speech signal in order to highlight the level of attenuation of the noise signal. The result shows that the noise signal is successfully canceled by the developed adaptive filter. The difference of the noise-free speech signal and filtered signal are calculated and the outcome implies that the filtered signal is approaching the noise-free speech signal upon the adaptive filtering. The frequency range of the successfully canceled noise by the LMS adaptive filter algorithm is determined by performing Fast Fourier Transform (FFT) on the signals. The LMS adaptive filter algorithm shows significant noise cancellation at lower frequency range.

Improved Noise Minimum Statistics Estimation Algorithm for Using in a Speech-Passing Noise-Rejecting Headset

Directory of Open Access Journals (Sweden)

Seyedtabaee Saeed

2010-01-01

Full Text Available This paper deals with configuration of an algorithm to be used in a speech-passing angle grinder noise-canceling headset. Angle grinder noise is annoying and interrupts ordinary oral communication. Meaning that, low SNR noisy condition is ahead. Since variation in angle grinder working condition changes noise statistics, the noise will be nonstationary with possible jumps in its power. Studies are conducted for picking an appropriate algorithm. A modified version of the well-known spectral subtraction shows superior performance against alternate methods. Noise estimation is calculated through a multi-band fast adapting scheme. The algorithm is adapted very quickly to the non-stationary noise environment while inflecting minimum musical noise and speech distortion on the processed signal. Objective and subjective measures illustrating the performance of the proposed method are introduced.

Monte Carlo analysis of megavoltage x-ray interaction-induced signal and noise in detectors for container inspection

Energy Technology Data Exchange (ETDEWEB)

Kim, Jinwoo; Park, Jiwoong; Kim, Junwoo; Kim, Dong Woon; Kim, Ho Kyung [Pusan National University, Busan (Korea, Republic of); Lim, Chang Hwy [Korea Research Institute of Ships and Ocean Engineering, Daejeon (Korea, Republic of)

2016-10-15

In a scanner system, a scintillation crystal is the first stage in the cascaded imaging chain transferring x-ray interaction information in cargo to be investigated to the final user who investigates x-ray images. On the other hand, the signal and noise is irreversibly transferred through the cascaded imaging chain. Therefore, the imaging performance of the first stage scintillator mainly governs the ultimate imaging performance of the system. In MV imaging, it is generally accepted that high-density scintillators, because of their sufficient optical yield, and low optical self-absorption and scattering coefficients. We chose the CdWO{sub 4} as the scintillation material. CdWO{sub 4} has a high density (7.9 g/cm{sup 3}), high atomic number (64), resistance to radiation, high optical yield, and low optical self-absorption. For the given MV spectrum, the improvement of QE from a detector with a thickness of 10 mm to 30 mm is 27% whereas the improvement from 30 mm to 50 mm is only 7%. On the other hand, the Swank noise is almost independent of the detector thickness. Consequently, the improvement of DQE from a detector with a thickness of 10 mm to 30 mm is 46% whereas the improvement from 30 mm to 50 mm is only 11%. In conclusion, the detector thickness of 30 mm would be the best for x-ray interaction-induced signal and noise performance as well as cost.

Development and significance of a fetal electrocardiogram recorded by signal-averaged high-amplification electrocardiography.

Science.gov (United States)

Hayashi, Risa; Nakai, Kenji; Fukushima, Akimune; Itoh, Manabu; Sugiyama, Toru

2009-03-01

Although ultrasonic diagnostic imaging and fetal heart monitors have undergone great technological improvements, the development and use of fetal electrocardiograms to evaluate fetal arrhythmias and autonomic nervous activity have not been fully established. We verified the clinical significance of the novel signal-averaged vector-projected high amplification ECG (SAVP-ECG) method in fetuses from 48 gravidas at 32-41 weeks of gestation and in 34 neonates. SAVP-ECGs from fetuses and newborns were recorded using a modified XYZ-leads system. Once noise and maternal QRS waves were removed, the P, QRS, and T wave intervals were measured from the signal-averaged fetal ECGs. We also compared fetal and neonatal heart rates (HRs), coefficients of variation of heart rate variability (CV) as a parasympathetic nervous activity, and the ratio of low to high frequency (LF/HF ratio) as a sympathetic nervous activity. The rate of detection of a fetal ECG by SAVP-ECG was 72.9%, and the fetal and neonatal QRS and QTc intervals were not significantly different. The neonatal CVs and LF/HF ratios were significantly increased compared with those in the fetus. In conclusion, we have developed a fetal ECG recording method using the SAVP-ECG system, which we used to evaluate autonomic nervous system development.

Improvement of the characterization of ultrasonic data by means of digital signal processing

International Nuclear Information System (INIS)

Bieth, M.; Romy, D.; Weigel, D.

1985-01-01

The digital signal processing method for averaging using minima developed by Framatome allows to improve signal-to-noise ratio up to 7 dB during ultrasonic testing of cast stainless steel structures (primary pipes of PWR power plants). Application of digital signal processing to industrial testing conditions requires the availability of a fast analog-digital converter capable of real time processings which has been developed by CGR [fr

Comparison of different cardiac MRI sequences at 1.5T/3.0T with respect to signal-to-noise and contrast-to-noise ratios - initial experience

International Nuclear Information System (INIS)

Gutberlet, M.; Spors, B.; Grothoff, M.; Freyhardt, P.; Schwinge, K.; Plotkin, M.; Amthauer, H.; Felix, R.

2004-01-01

Purpose: To compare image quality, signal-to-noise (SNR) and contrast-to-noise ratios (CNR) of different MRI sequences for cardiac imaging at 1.5 T and 3.0 T in volunteers. Material and Methods: 10 volunteers (5 male, 5 female) with a mean age of 33 years (±8) without any history of cardiac diseases were examined on a GE Signa 3.0 T and a GE Signa 1.5 T TwinSpeed Excite (GE Medical Systems, Milwaukee, WI, USA) scanner using a 4-element phased array surface coil (same design) on the same day. For tissue characterization ECG gated Fast Spinecho (FSE) T 1 - (Double IR), T 1 -STIR (Triple IR) and T 2 -weighted sequences in transverse orientation were used. For functional analysis a steady state free precession (SSFP-FIESTA) sequence was performed in the 4-chamber, 2-chamber long axis and short axis view. The flip angle used for the SSFP sequence at 3.0 T was reduced from 45 to 30 to keep short TR times while staying within the pre-defined SAR limitations. All other sequence parameters were kept constant. Results: All acquisitions could successfully be completed for the 10 volunteers. The mean SNR 3.0 T compared to 1.5 T was remarkably increased (p 2 - (160% SNR increase), the STIR-T 1 - (123%) and the T 1 - (91%) weighted FSE. Similar results were found comparing CNR at 3.0 T and 1.5 T. The mean SNR achieved using the SSFP sequences was more than doubled by 3.0 T (150%), but did not have any significant effect on the CNR. The image quality at 3.0 T did not appear to be improved, and was considered to be significantly worse when using SSFP sequences. Artefacts like shading in the area of the right ventricle (RV) were found to be more present at 3.0 T using FSE sequences. After a localized shim had been performed in 5/10 volunteers at the infero-lateral wall of the left ventricle (LV) with the SSFP sequences at 3.0 T no significant increase in artefacts could be detected. (orig.) [de

Methods to characterize non-Gaussian noise in TAMA

International Nuclear Information System (INIS)

Ando, Masaki; Arai, K; Takahashi, R; Tatsumi, D; Beyersdorf, P; Kawamura, S; Miyoki, S; Mio, N; Moriwaki, S; Numata, K; Kanda, N; Aso, Y; Fujimoto, M-K; Tsubono, K; Kuroda, K

2003-01-01

We present a data characterization method for the main output signal of the interferometric gravitational-wave detector, in particular targeting at effective detection of burst gravitational waves from stellar core collapse. The time scale of non-Gaussian events is evaluated in this method, and events with longer time scale than real signals are rejected as non-Gaussian noises. As a result of data analysis using 1000 h of real data with the interferometric gravitational-wave detector TAMA300, the false-alarm rate was improved 10 3 times with this non-Gaussian noise evaluation and rejection method

A study of filtering problems of background noise in nuclear spectrometry, improvement of signal-to-noise ratio, and of pulse characteristics produced by the optimum predictor device; Etude de problemes de filtrage de bruit de fond en spectrometrie nucleaire, amelioration du rapport signal sur bruit et des caracteristiques de l'impulsion mise en forme par le dispositif du predicteur optimum

Energy Technology Data Exchange (ETDEWEB)

Benda, J [Commissariat a l' Energie Atomique, 91 - Saclay (France). Centre d' Etudes Nucleaires

1967-05-01

The purpose of nuclear spectrometry is the precise measurement of particles energy. The resolving power of a spectrometer design is an important factor. Two main phenomena are involved in the limitation of this resolving power: The statistical fluctuations of the detector itself, and the background noise. For a given noise, the theory of filters enables the calculation of networks specially designed for the improvement of signal to noise ratio. The proposed system should lead to an improvement of 10.5 per cent of this ratio. Experiments have confirmed this theoretical estimation. The predictor device also makes possible the obtaining of shortened pulses. (author) [French] Les mesures en spectrometrie nucleaire ont pour but la determination precise de l'energie des particules. Le pouvoir de resolution d'une chaine de spectrometrie est une caracteristique importante. Deux phenomenes principaux concourent a limiter ce pouvoir de resolution: les fluctuations statistiques du detecteur et le bruit de fond. Pour un bruit de fond donne, la theorie des filtres permet de calculer des reseaux susceptibles de modifier le rapport signal sur bruit. Le systeme propose permet d'ameliorer de 10.5 pour cent ce rapport lorsqu'on se place dans les conditions optimales. Les resultats experimentaux confirment les previsions. Le dispositif predicteur permet aussi un raccourcissement de l'impulsion dans le temps. (auteur)

A Novel Partial Discharge Ultra-High Frequency Signal De-Noising Method Based on a Single-Channel Blind Source Separation Algorithm

Directory of Open Access Journals (Sweden)

Liangliang Wei

2018-02-01

Full Text Available To effectively de-noise the Gaussian white noise and periodic narrow-band interference in the background noise of partial discharge ultra-high frequency (PD UHF signals in field tests, a novel de-noising method, based on a single-channel blind source separation algorithm, is proposed. Compared with traditional methods, the proposed method can effectively de-noise the noise interference, and the distortion of the de-noising PD signal is smaller. Firstly, the PD UHF signal is time-frequency analyzed by S-transform to obtain the number of source signals. Then, the single-channel detected PD signal is converted into multi-channel signals by singular value decomposition (SVD, and background noise is separated from multi-channel PD UHF signals by the joint approximate diagonalization of eigen-matrix method. At last, the source PD signal is estimated and recovered by the l1-norm minimization method. The proposed de-noising method was applied on the simulation test and field test detected signals, and the de-noising performance of the different methods was compared. The simulation and field test results demonstrate the effectiveness and correctness of the proposed method.

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

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.

Core Noise Diagnostics of Turbofan Engine Noise Using Correlation and Coherence Functions

Science.gov (United States)

Miles, Jeffrey H.

2009-01-01

Cross-correlation and coherence functions are used to look for periodic acoustic components in turbofan engine combustor time histories, to investigate direct and indirect combustion noise source separation based on signal propagation time delays, and to provide information on combustor acoustics. Using the cross-correlation function, time delays were identified in all cases, clearly indicating the combustor is the source of the noise. In addition, unfiltered and low-pass filtered at 400 Hz signals had a cross-correlation time delay near 90 ms, while the low-pass filtered at less than 400 Hz signals had a cross-correlation time delay longer than 90 ms. Low-pass filtering at frequencies less than 400 Hz partially removes the direct combustion noise signals. The remainder includes the indirect combustion noise signal, which travels more slowly because of the dependence on the entropy convection velocity in the combustor. Source separation of direct and indirect combustion noise is demonstrated by proper use of low-pass filters with the cross-correlation function for a range of operating conditions. The results may lead to a better idea about the acoustics in the combustor and may help develop and validate improved reduced-order physics-based methods for predicting direct and indirect combustion noise.

Removing the Influence of Shimmer in the Calculation of Harmonics-To-Noise Ratios Using Ensemble-Averages in Voice Signals

OpenAIRE

Carlos Ferrer; Eduardo González; María E. Hernández-Díaz; Diana Torres; Anesto del Toro

2009-01-01

Harmonics-to-noise ratios (HNRs) are affected by general aperiodicity in voiced speech signals. To specifically reflect a signal-to-additive-noise ratio, the measurement should be insensitive to other periodicity perturbations, like jitter, shimmer, and waveform variability. The ensemble averaging technique is a time-domain method which has been gradually refined in terms of its sensitivity to jitter and waveform variability and required number of pulses. In this paper, shimmer is introduced ...

Speed of response, pile-up and signal to noise ratio in liquid ionization calorimeters

International Nuclear Information System (INIS)

Colas, J.

1989-11-01

Although liquid ionization calorimeters have been mostly used up to now with slow readout, their signals have a fast rise time. However, it is not easy to get this fast component of the pulse out of the calorimeter. For this purpose a new connection scheme of the electrodes, the electrostatic transformer, is presented and discussed. This technique reduces the detector capacitance while keeping the number of channels at an acceptable level. Also it allows the use of transmission lines to bring signals from the electrodes to the preamplifiers which could be located in an accessible area. With room temperature liquids the length of these cables can be short, keeping the added noise at a reasonable level. Contributions to the error on the energy measurement from pile up and electronics noise are studied in detail. Even on this issue, room temperature liquids (TMP/TMS) are found to be competitive with cold liquid argon at the expense of a moderately higher gap voltage

Speed of response, pile-up, and signal to noise ratio in liquid ionization calorimeters

International Nuclear Information System (INIS)

Colas, J.

1989-06-01

Although liquid ionization calorimeters have been mostly used up to now with slow readout, their signals have a fast rise time. However, it is not easy to get this fast component of the pulse out of the calorimeter. For this purpose a new connection scheme of the electrodes, the ''electrostatic transformer,'' is presented. This technique reduces the detector capacitance while keeping the number of channels at an acceptable level. Also it allows the use of transmission lines to bring signals from the electrodes to the preamplifiers which could be located in an accessible area. With room temperature liquids the length of these cables can be short, keeping the added noise at a reasonable level. Contributions to the error on the energy measurement from pile up and electronics noise are studied in detail. Even on this issue, room temperature liquids (TMP/TMS) are found to be competitive with cold liquid argon at the expense of a moderately higher gap voltage. 5 refs., 9 figs., 2 tabs

Non-Pilot-Aided Sequential Monte Carlo Method to Joint Signal, Phase Noise, and Frequency Offset Estimation in Multicarrier Systems

Directory of Open Access Journals (Sweden)

Christelle Garnier

2008-05-01

Full Text Available We address the problem of phase noise (PHN and carrier frequency offset (CFO mitigation in multicarrier receivers. In multicarrier systems, phase distortions cause two effects: the common phase error (CPE and the intercarrier interference (ICI which severely degrade the accuracy of the symbol detection stage. Here, we propose a non-pilot-aided scheme to jointly estimate PHN, CFO, and multicarrier signal in time domain. Unlike existing methods, non-pilot-based estimation is performed without any decision-directed scheme. Our approach to the problem is based on Bayesian estimation using sequential Monte Carlo filtering commonly referred to as particle filtering. The particle filter is efficiently implemented by combining the principles of the Rao-Blackwellization technique and an approximate optimal importance function for phase distortion sampling. Moreover, in order to fully benefit from time-domain processing, we propose a multicarrier signal model which includes the redundancy information induced by the cyclic prefix, thus leading to a significant performance improvement. Simulation results are provided in terms of bit error rate (BER and mean square error (MSE to illustrate the efficiency and the robustness of the proposed algorithm.

Novel noise reduction filter for improving visibility of early computed tomography signs of hyperacute stroke. Evaluation of the filter's performance. Preliminary clinical experience

International Nuclear Information System (INIS)

Takahashi, Noriyuki; Ishii, Kiyoshi; Lee, Y.; Tsai, D.Y.

2007-01-01

The aim of this study was to evaluate the performance of a novel noise reduction filter for improving the visibility of early computed tomography (CT) signs of hyperacute stroke on nonenhanced CT images. Fourteen patients with a middle cerebral artery occlusion within 4.5 h after onset were evaluated. The signal-to-noise ratio (SNR) of the processed images with the noise reduction filter and that of original images were measured. Two neuroradiologists visually rated all the processed and original images on the visibility of normal and abnormal gray-white matter interfaces. The SNR value of the processed images was approximately eight times as high as that of the original images, and a 87% reduction of noise was achieved using this technique. For the visual assessment, the results showed that the visibility of normal gray-white matter interface and that of the loss of the gray-white matter interface were significantly improved using the proposed method (P<0.05). The noise reduction filter proposed in the present study has the potential to improve the visibility of early CT signs of hyperacute stroke on nonenhanced CT images. (author)

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.

Nonlinear Bayesian Estimation of BOLD Signal under Non-Gaussian Noise

Directory of Open Access Journals (Sweden)

Ali Fahim Khan

2015-01-01

Full Text Available 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.

Novel Acoustic Feedback Cancellation Approaches In Hearing Aid Applications Using Probe Noise and Probe Noise Enhancement

DEFF Research Database (Denmark)

Guo, Meng; Jensen, Søren Holdt; Jensen, Jesper

2012-01-01

. In many cases, this bias problem causes the cancellation system to fail. The traditional probe noise approach, where a noise signal is added to the loudspeaker signal can, in theory, prevent the bias. However, in practice, the probe noise level must often be so high that the noise is clearly audible...... and annoying; this makes the traditional probe noise approach less useful in practical applications. In this work, we explain theoretically the decreased convergence rate when using low-level probe noise in the traditional approach, before we propose and study analytically two new probe noise approaches...... the proposed approaches much more attractive in practical applications. We demonstrate this through a simulation experiment with audio signals in a hearing aid acoustic feedback cancellation system, where the convergence rate is improved by as much as a factor of 10....

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.

Parallel feedback active noise control of MRI acoustic noise with signal decomposition using hybrid RLS-NLMS adaptive algorithms.

Science.gov (United States)

Ganguly, Anshuman; Krishna Vemuri, Sri Hari; Panahi, Issa

2014-01-01

This paper presents a cost-effective adaptive feedback Active Noise Control (FANC) method for controlling functional Magnetic Resonance Imaging (fMRI) acoustic noise by decomposing it into dominant periodic components and residual random components. Periodicity of fMRI acoustic noise is exploited by using linear prediction (LP) filtering to achieve signal decomposition. A hybrid combination of adaptive filters-Recursive Least Squares (RLS) and Normalized Least Mean Squares (NLMS) are then used to effectively control each component separately. Performance of the proposed FANC system is analyzed and Noise attenuation levels (NAL) up to 32.27 dB obtained by simulation are presented which confirm the effectiveness of the proposed FANC method.

Comprehensive quantification of signal-to-noise ratio and g-factor for image-based and k-space-based parallel imaging reconstructions.

Science.gov (United States)

Robson, Philip M; Grant, Aaron K; Madhuranthakam, Ananth J; Lattanzi, Riccardo; Sodickson, Daniel K; McKenzie, Charles A

2008-10-01

Parallel imaging reconstructions result in spatially varying noise amplification characterized by the g-factor, precluding conventional measurements of noise from the final image. A simple Monte Carlo based method is proposed for all linear image reconstruction algorithms, which allows measurement of signal-to-noise ratio and g-factor and is demonstrated for SENSE and GRAPPA reconstructions for accelerated acquisitions that have not previously been amenable to such assessment. Only a simple "prescan" measurement of noise amplitude and correlation in the phased-array receiver, and a single accelerated image acquisition are required, allowing robust assessment of signal-to-noise ratio and g-factor. The "pseudo multiple replica" method has been rigorously validated in phantoms and in vivo, showing excellent agreement with true multiple replica and analytical methods. This method is universally applicable to the parallel imaging reconstruction techniques used in clinical applications and will allow pixel-by-pixel image noise measurements for all parallel imaging strategies, allowing quantitative comparison between arbitrary k-space trajectories, image reconstruction, or noise conditioning techniques. (c) 2008 Wiley-Liss, Inc.

Improving ambient noise cross-correlations in the noisy ocean bottom environment of the Juan de Fuca plate

Science.gov (United States)

Tian, Ye; Ritzwoller, Michael H.

2017-09-01

Ambient noise tomography exploits seismic ground motions that propagate coherently over long interstation distances. Such ground motions provide information about the medium of propagation that is recoverable from interstation cross-correlations. Local noise sources, which are particularly strong in ocean bottom environments, corrupt ambient noise cross-correlations and compromise the effectiveness of ambient noise tomography. Based on 62 ocean bottom seismometers (OBSs) located on Juan de Fuca (JdF) plate from the Cascadia Initiative experiment and 40 continental stations near the coast of the western United States obtained in 2011 and 2012, we attempt to reduce the effects of local noise on vertical component seismic records across the plate and onto US continent. The goal is to provide better interstation cross-correlations for use in ambient noise tomography and the study of ambient noise directionality. As shown in previous studies, tilt and compliance noise are major sources of noise that contaminate the vertical channels of the OBSs and such noise can be greatly reduced by exploiting information on the horizontal components and the differential pressure gauge records, respectively. We find that ambient noise cross-correlations involving OBSs are of significantly higher signal-to-noise ratio at periods greater than 10 s after reducing these types of noise, particularly in shallow water environments where tilt and compliance noise are especially strong. The reduction of tilt and compliance noise promises to improve the accuracy and spatial extent of ambient noise tomography, allowing measurements based on coherently propagating ambient noise to be made at stations in the shallower parts of the JdF plate and at longer periods than in previous studies. In addition such local noise reduction produces better estimates of the azimuthal content of ambient noise.

Blind signal processing algorithms under DC biased Gaussian noise

Science.gov (United States)

Kim, Namyong; Byun, Hyung-Gi; Lim, Jeong-Ok

2013-05-01

Distortions caused by the DC-biased laser input can be modeled as DC biased Gaussian noise and removing DC bias is important in the demodulation process of the electrical signal in most optical communications. In this paper, a new performance criterion and a related algorithm for unsupervised equalization are proposed for communication systems in the environment of channel distortions and DC biased Gaussian noise. The proposed criterion utilizes the Euclidean distance between the Dirac-delta function located at zero on the error axis and a probability density function of biased constant modulus errors, where constant modulus error is defined by the difference between the system out and a constant modulus calculated from the transmitted symbol points. From the results obtained from the simulation under channel models with fading and DC bias noise abruptly added to background Gaussian noise, the proposed algorithm converges rapidly even after the interruption of DC bias proving that the proposed criterion can be effectively applied to optical communication systems corrupted by channel distortions and DC bias noise.

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.

Time Delay Mechanical-noise Cancellation (TDMC) to Provide Order of Magnitude Improvements in Radio Science Observations

Science.gov (United States)

Atkinson, D. H.; Babuscia, A.; Lazio, J.; Asmar, S.

2017-12-01

Many Radio Science investigations, including the determinations of planetary masses, measurements of planetary atmospheres, studies of the solar wind, and solar system tests of relativistic gravity, rely heavily on precision Doppler tracking. Recent and currently proposed missions such as VERITAS, Bepi Colombo, Juno have shown that the largest error source in the precision Doppler tracking data is noise in the Doppler system. This noise is attributed to un-modeled motions of the ground antenna's phase center and is commonly referred to as "antenna mechanical noise." Attempting to reduce this mechanical noise has proven difficult since the deep space communications antennas utilize large steel structures that are already optimized for mechanical stability. Armstrong et al. (2008) have demonstrated the Time Delay Mechanical-noise Cancellation (TDMC) concept using Goldstone DSN antennas (70 m & 34 m) and the Cassinispacecraft to show that the mechanical noise of the 70 m antenna could be suppressed when two-way Doppler tracking from the 70 m antenna and the receive-only Doppler data from the smaller, stiffer 34 m antenna were combined with suitable delays. The proof-of-concept confirmed that the mechanical noise in the final Doppler observable was reduced to that of the stiffer, more stable antenna. Caltech's Owens Valley Radio Observatory (OVRO) near Bishop, CA now has six 10.4 m diameter antennas, a consequence of the closure of Combined Array for Research in Millimeter Astronomy (CARMA). In principle, a 10 m antenna can lead to an order-of-magnitude improvement for the mechanical noise correction, as the smaller dish offers better mechanical stability compared to a DSN 34-m antenna. These antennas also have existing Ka-band receiving systems, and preliminary discussions with the OVRO staff suggest that much of the existing signal path could be used for Radio Science observations.

Speech perception for adult cochlear implant recipients in a realistic background noise: effectiveness of preprocessing strategies and external options for improving speech recognition in noise.

Science.gov (United States)

Gifford, René H; Revit, Lawrence J

2010-01-01

, a standard t-test was run to evaluate effectiveness across manufacturer for improving the SRT in noise. In Experiment 2, 16 of the 20 Cochlear Corporation subjects were reassessed obtaining an SRT in noise using the manufacturer-suggested "Everyday," "Noise," and "Focus" preprocessing strategies. A repeated-measures ANOVA was employed to assess the effects of preprocessing. The primary findings were (i) both Noise and Focus preprocessing strategies (Cochlear Corporation) significantly improved the SRT in noise as compared to Everyday preprocessing, (ii) the T-Mic accessory option (Advanced Bionics) significantly improved the SRT as compared to the BTE mic, and (iii) Focus preprocessing and the T-Mic resulted in similar degrees of improvement that were not found to be significantly different from one another. Options available in current cochlear implant sound processors are able to significantly improve speech understanding in a realistic, semidiffuse noise with both Cochlear Corporation and Advanced Bionics systems. For Cochlear Corporation recipients, Focus preprocessing yields the best speech-recognition performance in a complex listening environment; however, it is recommended that Noise preprocessing be used as the new default for everyday listening environments to avoid the need for switching programs throughout the day. For Advanced Bionics recipients, the T-Mic offers significantly improved performance in noise and is recommended for everyday use in all listening environments. American Academy of Audiology.

Signal and noise modeling in confocal laser scanning fluorescence microscopy.

Science.gov (United States)

Herberich, Gerlind; Windoffer, Reinhard; Leube, Rudolf E; Aach, Til

2012-01-01

Fluorescence confocal laser scanning microscopy (CLSM) has revolutionized imaging of subcellular structures in biomedical research by enabling the acquisition of 3D time-series of fluorescently-tagged proteins in living cells, hence forming the basis for an automated quantification of their morphological and dynamic characteristics. Due to the inherently weak fluorescence, CLSM images exhibit a low SNR. We present a novel model for the transfer of signal and noise in CLSM that is both theoretically sound as well as corroborated by a rigorous analysis of the pixel intensity statistics via measurement of the 3D noise power spectra, signal-dependence and distribution. Our model provides a better fit to the data than previously proposed models. Further, it forms the basis for (i) the simulation of the CLSM imaging process indispensable for the quantitative evaluation of CLSM image analysis algorithms, (ii) the application of Poisson denoising algorithms and (iii) the reconstruction of the fluorescence signal.

Application of adaptive digital signal processing to speech enhancement for the hearing impaired.

Science.gov (United States)

Chabries, D M; Christiansen, R W; Brey, R H; Robinette, M S; Harris, R W

1987-01-01

A major complaint of individuals with normal hearing and hearing impairments is a reduced ability to understand speech in a noisy environment. This paper describes the concept of adaptive noise cancelling for removing noise from corrupted speech signals. Application of adaptive digital signal processing has long been known and is described from a historical as well as technical perspective. The Widrow-Hoff LMS (least mean square) algorithm developed in 1959 forms the introduction to modern adaptive signal processing. This method uses a "primary" input which consists of the desired speech signal corrupted with noise and a second "reference" signal which is used to estimate the primary noise signal. By subtracting the adaptively filtered estimate of the noise, the desired speech signal is obtained. Recent developments in the field as they relate to noise cancellation are described. These developments include more computationally efficient algorithms as well as algorithms that exhibit improved learning performance. A second method for removing noise from speech, for use when no independent reference for the noise exists, is referred to as single channel noise suppression. Both adaptive and spectral subtraction techniques have been applied to this problem--often with the result of decreased speech intelligibility. Current techniques applied to this problem are described, including signal processing techniques that offer promise in the noise suppression application.

Non-linear signal response functions and their effects on the statistical and noise cancellation properties of isotope ratio measurements by multi-collector plasma mass spectrometry

International Nuclear Information System (INIS)

Doherty, W.

2013-01-01

noise limited isotope ion signals always produced negative skew histograms. ► The corresponding isotope ratio histograms were symmetric, negative or positive skew. ► Skew direction is predictable from relations among the response function coefficients. ► Non-linear signal division improved noise cancellation, typically by 3 × to 10 ×

Broadband squeezing of quantum noise in a Michelson interferometer with Twin-Signal-Recycling.

Science.gov (United States)

Thüring, André; Gräf, Christian; Vahlbruch, Henning; Mehmet, Moritz; Danzmann, Karsten; Schnabel, Roman

2009-03-15

Twin-Signal-Recycling (TSR) builds on the resonance doublet of two optically coupled cavities and efficiently enhances the sensitivity of an interferometer at a dedicated signal frequency. We report on what we believe to be the first experimental realization of a TSR Michelson interferometer and also its broadband enhancement by squeezed light injection. The complete setup was stably locked, and a broadband quantum noise reduction of the interferometers shot noise by a factor of up to 4 dB was demonstrated. The system was characterized by measuring its quantum noise spectra for several tunings of the TSR cavities. We found good agreement between the experimental results and numerical simulations.

Low-Arousal Speech Noise Improves Performance in N-Back Task: An ERP Study

Science.gov (United States)

Zhang, Dandan; Jin, Yi; Luo, Yuejia

2013-01-01

The relationship between noise and human performance is a crucial topic in ergonomic research. However, the brain dynamics of the emotional arousal effects of background noises are still unclear. The current study employed meaningless speech noises in the n-back working memory task to explore the changes of event-related potentials (ERPs) elicited by the noises with low arousal level vs. high arousal level. We found that the memory performance in low arousal condition were improved compared with the silent and the high arousal conditions; participants responded more quickly and had larger P2 and P3 amplitudes in low arousal condition while the performance and ERP components showed no significant difference between high arousal and silent conditions. These findings suggested that the emotional arousal dimension of background noises had a significant influence on human working memory performance, and that this effect was independent of the acoustic characteristics of noises (e.g., intensity) and the meaning of speech materials. The current findings improve our understanding of background noise effects on human performance and lay the ground for the investigation of patients with attention deficits. PMID:24204607

Low-arousal speech noise improves performance in N-back task: an ERP study.

Science.gov (United States)

Han, Longzhu; Liu, Yunzhe; Zhang, Dandan; Jin, Yi; Luo, Yuejia

2013-01-01

The relationship between noise and human performance is a crucial topic in ergonomic research. However, the brain dynamics of the emotional arousal effects of background noises are still unclear. The current study employed meaningless speech noises in the n-back working memory task to explore the changes of event-related potentials (ERPs) elicited by the noises with low arousal level vs. high arousal level. We found that the memory performance in low arousal condition were improved compared with the silent and the high arousal conditions; participants responded more quickly and had larger P2 and P3 amplitudes in low arousal condition while the performance and ERP components showed no significant difference between high arousal and silent conditions. These findings suggested that the emotional arousal dimension of background noises had a significant influence on human working memory performance, and that this effect was independent of the acoustic characteristics of noises (e.g., intensity) and the meaning of speech materials. The current findings improve our understanding of background noise effects on human performance and lay the ground for the investigation of patients with attention deficits.

Low-arousal speech noise improves performance in N-back task: an ERP study.

Directory of Open Access Journals (Sweden)

Longzhu Han

Full Text Available The relationship between noise and human performance is a crucial topic in ergonomic research. However, the brain dynamics of the emotional arousal effects of background noises are still unclear. The current study employed meaningless speech noises in the n-back working memory task to explore the changes of event-related potentials (ERPs elicited by the noises with low arousal level vs. high arousal level. We found that the memory performance in low arousal condition were improved compared with the silent and the high arousal conditions; participants responded more quickly and had larger P2 and P3 amplitudes in low arousal condition while the performance and ERP components showed no significant difference between high arousal and silent conditions. These findings suggested that the emotional arousal dimension of background noises had a significant influence on human working memory performance, and that this effect was independent of the acoustic characteristics of noises (e.g., intensity and the meaning of speech materials. The current findings improve our understanding of background noise effects on human performance and lay the ground for the investigation of patients with attention deficits.

Sensor-based vibration signal feature extraction using an improved composite dictionary matching pursuit algorithm.

Science.gov (United States)

Cui, Lingli; Wu, Na; Wang, Wenjing; Kang, Chenhui

2014-09-09

This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP) algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP) is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and reconstruction algorithm

Sensor-Based Vibration Signal Feature Extraction Using an Improved Composite Dictionary Matching Pursuit Algorithm

Directory of Open Access Journals (Sweden)

Lingli Cui

2014-09-01

Full Text Available This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and

A simulation study of harmonics regeneration in noise reduction for electric and acoustic stimulation.

Science.gov (United States)

Hu, Yi

2010-05-01

Recent research results show that combined electric and acoustic stimulation (EAS) significantly improves speech recognition in noise, and it is generally established that access to the improved F0 representation of target speech, along with the glimpse cues, provide the EAS benefits. Under noisy listening conditions, noise signals degrade these important cues by introducing undesired temporal-frequency components and corrupting harmonics structure. In this study, the potential of combining noise reduction and harmonics regeneration techniques was investigated to further improve speech intelligibility in noise by providing improved beneficial cues for EAS. Three hypotheses were tested: (1) noise reduction methods can improve speech intelligibility in noise for EAS; (2) harmonics regeneration after noise reduction can further improve speech intelligibility in noise for EAS; and (3) harmonics sideband constraints in frequency domain (or equivalently, amplitude modulation in temporal domain), even deterministic ones, can provide additional benefits. Test results demonstrate that combining noise reduction and harmonics regeneration can significantly improve speech recognition in noise for EAS, and it is also beneficial to preserve the harmonics sidebands under adverse listening conditions. This finding warrants further work into the development of algorithms that regenerate harmonics and the related sidebands for EAS processing under noisy conditions.

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.

Improved Kalman Filter Method for Measurement Noise Reduction in Multi Sensor RFID Systems

Directory of Open Access Journals (Sweden)

Min Chul Kim

2011-10-01

Full Text Available Recently, the range of available Radio Frequency Identification (RFID tags has been widened to include smart RFID tags which can monitor their varying surroundings. One of the most important factors for better performance of smart RFID system is accurate measurement from various sensors. In the multi-sensing environment, some noisy signals are obtained because of the changing surroundings. We propose in this paper an improved Kalman filter method to reduce noise and obtain correct data. Performance of Kalman filter is determined by a measurement and system noise covariance which are usually called the R and Q variables in the Kalman filter algorithm. Choosing a correct R and Q variable is one of the most important design factors for better performance of the Kalman filter. For this reason, we proposed an improved Kalman filter to advance an ability of noise reduction of the Kalman filter. The measurement noise covariance was only considered because the system architecture is simple and can be adjusted by the neural network. With this method, more accurate data can be obtained with smart RFID tags. In a simulation the proposed improved Kalman filter has 40.1%, 60.4% and 87.5% less Mean Squared Error (MSE than the conventional Kalman filter method for a temperature sensor, humidity sensor and oxygen sensor, respectively. The performance of the proposed method was also verified with some experiments.

Improved Kalman filter method for measurement noise reduction in multi sensor RFID systems.

Science.gov (United States)

Eom, Ki Hwan; Lee, Seung Joon; Kyung, Yeo Sun; Lee, Chang Won; Kim, Min Chul; Jung, Kyung Kwon

2011-01-01

Recently, the range of available radio frequency identification (RFID) tags has been widened to include smart RFID tags which can monitor their varying surroundings. One of the most important factors for better performance of smart RFID system is accurate measurement from various sensors. In the multi-sensing environment, some noisy signals are obtained because of the changing surroundings. We propose in this paper an improved Kalman filter method to reduce noise and obtain correct data. Performance of Kalman filter is determined by a measurement and system noise covariance which are usually called the R and Q variables in the Kalman filter algorithm. Choosing a correct R and Q variable is one of the most important design factors for better performance of the Kalman filter. For this reason, we proposed an improved Kalman filter to advance an ability of noise reduction of the Kalman filter. The measurement noise covariance was only considered because the system architecture is simple and can be adjusted by the neural network. With this method, more accurate data can be obtained with smart RFID tags. In a simulation the proposed improved Kalman filter has 40.1%, 60.4% and 87.5% less mean squared error (MSE) than the conventional Kalman filter method for a temperature sensor, humidity sensor and oxygen sensor, respectively. The performance of the proposed method was also verified with some experiments.

Restoring the encoding properties of a stochastic neuron model by an exogenous noise

Science.gov (United States)

Paffi, Alessandra; Camera, Francesca; Apollonio, Francesca; d'Inzeo, Guglielmo; Liberti, Micaela

2015-01-01

Here we evaluate the possibility of improving the encoding properties of an impaired neuronal system by superimposing an exogenous noise to an external electric stimulation signal. The approach is based on the use of mathematical neuron models consisting of stochastic HH-like circuit, where the impairment of the endogenous presynaptic inputs is described as a subthreshold injected current and the exogenous stimulation signal is a sinusoidal voltage perturbation across the membrane. Our results indicate that a correlated Gaussian noise, added to the sinusoidal signal can significantly increase the encoding properties of the impaired system, through the Stochastic Resonance (SR) phenomenon. These results suggest that an exogenous noise, suitably tailored, could improve the efficacy of those stimulation techniques used in neuronal systems, where the presynaptic sensory neurons are impaired and have to be artificially bypassed. PMID:25999845

Restoring the encoding properties of a stochastic neuron model by an exogenous noise

Directory of Open Access Journals (Sweden)

Alessandra ePaffi

2015-05-01

Full Text Available Here we evaluate the possibility of improving the encoding properties of an impaired neuronal system by superimposing an exogenous noise to an external electric stimulation signal. The approach is based on the use of mathematical neuron models consisting of stochastic HH-like circuit, where the impairment of the endogenous presynaptic inputs is described as a subthreshold injected current and the exogenous stimulation signal is a sinusoidal voltage perturbation across the membrane. Our results indicate that a correlated Gaussian noise, added to the sinusoidal signal can significantly increase the encoding properties of the impaired system, through the Stochastic Resonance (SR phenomenon. These results suggest that an exogenous noise, suitably tailored, could improve the efficacy of those stimulation techniques used in neuronal systems, where the presynaptic sensory neurons are impaired and have to be artificially bypassed.

Stochastic resonance in a gain-noise model of a single-mode laser driven by pump noise and quantum noise with cross-correlation between real and imaginary parts under direct signal modulation

Institute of Scientific and Technical Information of China (English)

Chen Li-Mei; Cao Li; Wu Da-Jin

2007-01-01

Stochastic resonance (SR) is studied in a gain-noise model of a single-mode laser driven by a coloured pump noise and a quantum noise with cross-correlation between real and imaginary parts under a direct signal modulation. By using a linear approximation method, we find that the SR appears during the variation of signal-to-noise ratio (SNR)separately with the pump noise self-correlation time τ, the noise correlation coefficient between the real part and the imaginary part of the quantum noise λq, the attenuation coefficient γ and the deterministic steady-state intensity I0.In addition, it is found that the SR can be characterized not only by the dependence of SNR on the noise variables of τand λq, but also by the dependence of SNR on the laser system variables of γ and I0. Thus our investigation extends the characteristic quantity of SR proposed before.

Spectrogram Image Analysis of Error Signals for Minimizing Impulse Noise

Directory of Open Access Journals (Sweden)

Jeakwan Kim

2016-01-01

Full Text Available This paper presents the theoretical and experimental study on the spectrogram image analysis of error signals for minimizing the impulse input noises in the active suppression of noise. Impulse inputs of some specific wave patterns as primary noises to a one-dimensional duct with the length of 1800 mm are shown. The convergence speed of the adaptive feedforward algorithm based on the least mean square approach was controlled by a normalized step size which was incorporated into the algorithm. The variations of the step size govern the stability as well as the convergence speed. Because of this reason, a normalized step size is introduced as a new method for the control of impulse noise. The spectrogram images which indicate the degree of the attenuation of the impulse input noises are considered to represent the attenuation with the new method. The algorithm is extensively investigated in both simulation and real-time control experiment. It is demonstrated that the suggested algorithm worked with a nice stability and performance against impulse noises. The results in this study can be used for practical active noise control systems.

High-frequency signal and noise estimates of CSR GRACE RL04

Science.gov (United States)

Bonin, Jennifer A.; Bettadpur, Srinivas; Tapley, Byron D.

2012-12-01

A sliding window technique is used to create daily-sampled Gravity Recovery and Climate Experiment (GRACE) solutions with the same background processing as the official CSR RL04 monthly series. By estimating over shorter time spans, more frequent solutions are made using uncorrelated data, allowing for higher frequency resolution in addition to daily sampling. Using these data sets, high-frequency GRACE errors are computed using two different techniques: assuming the GRACE high-frequency signal in a quiet area of the ocean is the true error, and computing the variance of differences between multiple high-frequency GRACE series from different centers. While the signal-to-noise ratios prove to be sufficiently high for confidence at annual and lower frequencies, at frequencies above 3 cycles/year the signal-to-noise ratios in the large hydrological basins looked at here are near 1.0. Comparisons with the GLDAS hydrological model and high frequency GRACE series developed at other centers confirm CSR GRACE RL04's poor ability to accurately and reliably measure hydrological signal above 3-9 cycles/year, due to the low power of the large-scale hydrological signal typical at those frequencies compared to the GRACE errors.

Signal-to-noise optimization and evaluation of a home-made visible diode-array spectrophotometer

Science.gov (United States)

Raimundo, Jr., Ivo M.; Pasquini, Celio

1993-01-01

This paper describes a simple low-cost multichannel visible spectrophotometer built with an RL512G EGG-Reticon photodiode array. A symmetric Czerny-Turner optical design was employed; instrument control was via a single-board microcomputer based on the 8085 Intel microprocessor. Spectral intensity data are stored in the single-board's RAM and then transferred to an IBM-AT 3865X compatible microcomputer through a RS-232C interface. This external microcomputer processes the data to recover transmittance, absorbance or relative intensity of the spectra. The signal-to-noise ratio and dynamic range were improved by using variable integration times, which increase during the same scan; and by the use of either weighted or unweighted sliding average of consecutive diodes. The instrument is suitable for automatic methods requiring quasi-simultaneous multiwavelength detections, such as multivariative calibration and flow-injection gradient scan techniques. PMID:18924979

Photoacoustic signal and noise analysis for Si thin plate: signal correction in frequency domain.

Science.gov (United States)

Markushev, D D; Rabasović, M D; Todorović, D M; Galović, S; Bialkowski, S E

2015-03-01

Methods for photoacoustic signal measurement, rectification, and analysis for 85 μm thin Si samples in the 20-20 000 Hz modulation frequency range are presented. Methods for frequency-dependent amplitude and phase signal rectification in the presence of coherent and incoherent noise as well as distortion due to microphone characteristics are presented. Signal correction is accomplished using inverse system response functions deduced by comparing real to ideal signals for a sample with well-known bulk parameters and dimensions. The system response is a piece-wise construction, each component being due to a particular effect of the measurement system. Heat transfer and elastic effects are modeled using standard Rosencweig-Gersho and elastic-bending theories. Thermal diffusion, thermoelastic, and plasmaelastic signal components are calculated and compared to measurements. The differences between theory and experiment are used to detect and correct signal distortion and to determine detector and sound-card characteristics. Corrected signal analysis is found to faithfully reflect known sample parameters.

Signal and noise analysis in TRION-Time-Resolved Integrative Optical Fast Neutron detector

International Nuclear Information System (INIS)

Vartsky, D; Feldman, G; Mor, I; Goldberg, M B; Bar, D; Dangendorf, V

2009-01-01

TRION is a sub-mm spatial resolution fast neutron imaging detector, which employs an integrative optical time-of-flight technique. The detector was developed for fast neutron resonance radiography, a method capable of detecting a broad range of conventional and improvised explosives. In this study we have analyzed in detail, using Monte-Carlo calculations and experimentally determined parameters, all the processes that influence the signal and noise in the TRION detector. In contrast to event-counting detectors where the signal-to-noise ratio is dependent only on the number of detected events (quantum noise), in an energy-integrating detector additional factors, such as the fluctuations in imparted energy, number of photoelectrons, system gain and other factors will contribute to the noise. The excess noise factor (over the quantum noise) due to these processes was 4.3, 2.7, 2.1, 1.9 and 1.9 for incident neutron energies of 2, 4, 7.5, 10 and 14 MeV, respectively. It is shown that, even under ideal light collection conditions, a fast neutron detection system operating in an integrative mode cannot be quantum-noise-limited due to the relatively large variance in the imparted proton energy and the resulting scintillation light distributions.

Effect of Simultaneous Bilingualism on Speech Intelligibility across Different Masker Types, Modalities, and Signal-to-Noise Ratios in School-Age Children.

Science.gov (United States)

Reetzke, Rachel; Lam, Boji Pak-Wing; Xie, Zilong; Sheng, Li; Chandrasekaran, Bharath

2016-01-01

Recognizing speech in adverse listening conditions is a significant cognitive, perceptual, and linguistic challenge, especially for children. Prior studies have yielded mixed results on the impact of bilingualism on speech perception in noise. Methodological variations across studies make it difficult to converge on a conclusion regarding the effect of bilingualism on speech-in-noise performance. Moreover, there is a dearth of speech-in-noise evidence for bilingual children who learn two languages simultaneously. The aim of the present study was to examine the extent to which various adverse listening conditions modulate differences in speech-in-noise performance between monolingual and simultaneous bilingual children. To that end, sentence recognition was assessed in twenty-four school-aged children (12 monolinguals; 12 simultaneous bilinguals, age of English acquisition ≤ 3 yrs.). We implemented a comprehensive speech-in-noise battery to examine recognition of English sentences across different modalities (audio-only, audiovisual), masker types (steady-state pink noise, two-talker babble), and a range of signal-to-noise ratios (SNRs; 0 to -16 dB). Results revealed no difference in performance between monolingual and simultaneous bilingual children across each combination of modality, masker, and SNR. Our findings suggest that when English age of acquisition and socioeconomic status is similar between groups, monolingual and bilingual children exhibit comparable speech-in-noise performance across a range of conditions analogous to everyday listening environments.

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

International Nuclear Information System (INIS)

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

2009-01-01

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.

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.

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.

Influence of Signal-to-Noise Ratio and Point Spread Function on Limits of Super-Resolution

NARCIS (Netherlands)

Pham, T.Q.; Vliet, L.J. van; Schutte, K.

2005-01-01

This paper presents a method to predict the limit of possible resolution enhancement given a sequence of low resolution images. Three important parameters influence the outcome of this limit: the total Point Spread Function (PSF), the Signal-to-Noise Ratio (SNR) and the number of input images.

Influence of signal-to-noise ratio and point spread function on limits of super-resolution

NARCIS (Netherlands)

Pham, T.Q.; Van Vliet, L.; Schutte, K.

2005-01-01

This paper presents a method to predict the limit of possible resolution enhancement given a sequence of lowresolution images. Three important parameters influence the outcome of this limit: the total Point Spread Function (PSF), the Signal-to-Noise Ratio (SNR) and the number of input images.

Noise reduction with complex bilateral filter.

Science.gov (United States)

Matsumoto, Mitsuharu

2017-12-01

This study introduces a noise reduction technique that uses a complex bilateral filter. A bilateral filter is a nonlinear filter originally developed for images that can reduce noise while preserving edge information. It is an attractive filter and has been used in many applications in image processing. When it is applied to an acoustical signal, small-amplitude noise is reduced while the speech signal is preserved. However, a bilateral filter cannot handle noise with relatively large amplitudes owing to its innate characteristics. In this study, the noisy signal is transformed into the time-frequency domain and the filter is improved to handle complex spectra. The high-amplitude noise is reduced in the time-frequency domain via the proposed filter. The features and the potential of the proposed filter are also confirmed through experiments.

A novel crystal-analyzer phase retrieval algorithm and its noise property.

Science.gov (United States)

Bao, Yuan; Wang, Yan; Li, Panyun; Wu, Zhao; Shao, Qigang; Gao, Kun; Wang, Zhili; Ju, Zaiqiang; Zhang, Kai; Yuan, Qingxi; Huang, Wanxia; Zhu, Peiping; Wu, Ziyu

2015-05-01

A description of the rocking curve in diffraction enhanced imaging (DEI) is presented in terms of the angular signal response function and a simple multi-information retrieval algorithm based on the cosine function fitting. A comprehensive analysis of noise properties of DEI is also given considering the noise transfer characteristic of the X-ray source. The validation has been performed with synchrotron radiation experimental data and Monte Carlo simulations based on the Geant4 toolkit combined with the refractive process of X-rays, which show good agreement with each other. Moreover, results indicate that the signal-to-noise ratios of the refraction and scattering images are about one order of magnitude better than that of the absorption image at the edges of low-Z samples. The noise penalty is drastically reduced with the increasing photon flux and visibility. Finally, this work demonstrates that the analytical method can build an interesting connection between DEI and GDPCI (grating-based differential phase contrast imaging) and is widely suitable for a variety of measurement noise in the angular signal response imaging prototype. The analysis significantly contributes to the understanding of noise characteristics of DEI images and may allow improvements to the signal-to-noise ratio in biomedical and material science imaging.

A Dynamically Focusing Cochlear Implant Strategy Can Improve Vowel Identification in Noise.

Science.gov (United States)

Arenberg, Julie G; Parkinson, Wendy S; Litvak, Leonid; Chen, Chen; Kreft, Heather A; Oxenham, Andrew J

2018-03-09

The standard, monopolar (MP) electrode configuration used in commercially available cochlear implants (CI) creates a broad electrical field, which can lead to unwanted channel interactions. Use of more focused configurations, such as tripolar and phased array, has led to mixed results for improving speech understanding. The purpose of the present study was to assess the efficacy of a physiologically inspired configuration called dynamic focusing, using focused tripolar stimulation at low levels and less focused stimulation at high levels. Dynamic focusing may better mimic cochlear excitation patterns in normal acoustic hearing, while reducing the current levels necessary to achieve sufficient loudness at high levels. Twenty postlingually deafened adult CI users participated in the study. Speech perception was assessed in quiet and in a four-talker babble background noise. Speech stimuli were closed-set spondees in noise, and medial vowels at 50 and 60 dB SPL in quiet and in noise. The signal to noise ratio was adjusted individually such that performance was between 40 and 60% correct with the MP strategy. Subjects were fitted with three experimental strategies matched for pulse duration, pulse rate, filter settings, and loudness on a channel-by-channel basis. The strategies included 14 channels programmed in MP, fixed partial tripolar (σ = 0.8), and dynamic partial tripolar (σ at 0.8 at threshold and 0.5 at the most comfortable level). Fifteen minutes of listening experience was provided with each strategy before testing. Sound quality ratings were also obtained. Speech perception performance for vowel identification in quiet at 50 and 60 dB SPL and for spondees in noise was similar for the three tested strategies. However, performance on vowel identification in noise was significantly better for listeners using the dynamic focusing strategy. Sound quality ratings were similar for the three strategies. Some subjects obtained more benefit than others, with some

An adaptive grid to improve the efficiency and accuracy of modelling underwater noise from shipping

Science.gov (United States)

Trigg, Leah; Chen, Feng; Shapiro, Georgy; Ingram, Simon; Embling, Clare

2017-04-01

Underwater noise from shipping is becoming a significant concern and has been listed as a pollutant under Descriptor 11 of the Marine Strategy Framework Directive. Underwater noise models are an essential tool to assess and predict noise levels for regulatory procedures such as environmental impact assessments and ship noise monitoring. There are generally two approaches to noise modelling. The first is based on simplified energy flux models, assuming either spherical or cylindrical propagation of sound energy. These models are very quick but they ignore important water column and seabed properties, and produce significant errors in the areas subject to temperature stratification (Shapiro et al., 2014). The second type of model (e.g. ray-tracing and parabolic equation) is based on an advanced physical representation of sound propagation. However, these acoustic propagation models are computationally expensive to execute. Shipping noise modelling requires spatial discretization in order to group noise sources together using a grid. A uniform grid size is often selected to achieve either the greatest efficiency (i.e. speed of computations) or the greatest accuracy. In contrast, this work aims to produce efficient and accurate noise level predictions by presenting an adaptive grid where cell size varies with distance from the receiver. The spatial range over which a certain cell size is suitable was determined by calculating the distance from the receiver at which propagation loss becomes uniform across a grid cell. The computational efficiency and accuracy of the resulting adaptive grid was tested by comparing it to uniform 1 km and 5 km grids. These represent an accurate and computationally efficient grid respectively. For a case study of the Celtic Sea, an application of the adaptive grid over an area of 160×160 km reduced the number of model executions required from 25600 for a 1 km grid to 5356 in December and to between 5056 and 13132 in August, which

Electrocardiogram signal denoising based on empirical mode decomposition technique: an overview

International Nuclear Information System (INIS)

Han, G.; Lin, B.; Xu, Z.

2017-01-01

Electrocardiogram (ECG) signal is nonlinear and non-stationary weak signal which reflects whether the heart is functioning normally or abnormally. ECG signal is susceptible to various kinds of noises such as high/low frequency noises, powerline interference and baseline wander. Hence, the removal of noises from ECG signal becomes a vital link in the ECG signal processing and plays a significant role in the detection and diagnosis of heart diseases. The review will describe the recent developments of ECG signal denoising based on Empirical Mode Decomposition (EMD) technique including high frequency noise removal, powerline interference separation, baseline wander correction, the combining of EMD and Other Methods, EEMD technique. EMD technique is a quite potential and prospective but not perfect method in the application of processing nonlinear and non-stationary signal like ECG signal. The EMD combined with other algorithms is a good solution to improve the performance of noise cancellation. The pros and cons of EMD technique in ECG signal denoising are discussed in detail. Finally, the future work and challenges in ECG signal denoising based on EMD technique are clarified.