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.
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.
Time-frequency peak filtering for random noise attenuation of magnetic resonance sounding signal
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.
International Nuclear Information System (INIS)
Zhang Yu; Wang Guangyi; Lu Xinmiao; Hu Yongcai; Xu Jiangtao
2016-01-01
The random telegraph signal noise in the pixel source follower MOSFET is the principle component of the noise in the CMOS image sensor under low light. In this paper, the physical and statistical model of the random telegraph signal noise in the pixel source follower based on the binomial distribution is set up. The number of electrons captured or released by the oxide traps in the unit time is described as the random variables which obey the binomial distribution. As a result, the output states and the corresponding probabilities of the first and the second samples of the correlated double sampling circuit are acquired. The standard deviation of the output states after the correlated double sampling circuit can be obtained accordingly. In the simulation section, one hundred thousand samples of the source follower MOSFET have been simulated, and the simulation results show that the proposed model has the similar statistical characteristics with the existing models under the effect of the channel length and the density of the oxide trap. Moreover, the noise histogram of the proposed model has been evaluated at different environmental temperatures. (paper)
M. O. Partala; S. Ya. Zhuk
2007-01-01
On the base of mixed Markoff process in discrete time optimal and quasioptimal algorithms is designed for adaptive filtration of speech signals in the presence of correlated noise with random variation of probabilistic characteristics.
Kolhatkar, J.S.; Vandamme, L.K.J.; Salm, Cora; Wallinga, Hans
2004-01-01
The low-frequency noise power spectrum of small dimension MOSFETs is dominated by Lorentzians arising from random telegraph signals (RTS). The low-frequency noise is observed to decrease when the devices are periodically switched 'off'. The technique of determining the statistical lifetimes and
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
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.)
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
The Signal Importance of Noise
Macy, Michael; Tsvetkova, Milena
2015-01-01
Noise is widely regarded as a residual category--the unexplained variance in a linear model or the random disturbance of a predictable pattern. Accordingly, formal models often impose the simplifying assumption that the world is noise-free and social dynamics are deterministic. Where noise is assigned causal importance, it is often assumed to be a…
Kastelein, Ronald A; Wensveen, Paul J; Hoek, Lean; Au, Whitlow W L; Terhune, John M; de Jong, Christ A F
2009-09-01
A psychoacoustic behavioral technique was used to determine the critical ratios (CRs) of two harbor porpoises for tonal signals with frequencies between 0.315 and 150 kHz, in random Gaussian white noise. The masked 50% detection hearing thresholds were measured using a "go/no-go" response paradigm and an up-down staircase psychometric method. CRs were determined at one masking noise level for each test frequency and were similar in both animals. For signals between 0.315 and 4 kHz, the CRs were relatively constant at around 18 dB. Between 4 and 150 kHz the CR increased gradually from 18 to 39 dB ( approximately 3.3 dB/octave). Generally harbor porpoises can detect tonal signals in Gaussian white noise slightly better than most odontocetes tested so far. By combining the mean CRs found in the present study with the spectrum level of the background noise levels at sea, the basic audiogram, and the directivity index, the detection threshold levels of harbor porpoises for tonal signals in various sea states can be calculated.
Audibility of modulation noise in stationary signals
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
Pseudo random signal processing theory and application
Zepernick, Hans-Jurgen
2013-01-01
In recent years, pseudo random signal processing has proven to be a critical enabler of modern communication, information, security and measurement systems. The signal's pseudo random, noise-like properties make it vitally important as a tool for protecting against interference, alleviating multipath propagation and allowing the potential of sharing bandwidth with other users. Taking a practical approach to the topic, this text provides a comprehensive and systematic guide to understanding and using pseudo random signals. Covering theoretical principles, design methodologies and applications
Quantum-noise randomized ciphers
International Nuclear Information System (INIS)
Nair, Ranjith; Yuen, Horace P.; Kumar, Prem; Corndorf, Eric; Eguchi, Takami
2006-01-01
We review the notion of a classical random cipher and its advantages. We sharpen the usual description of random ciphers to a particular mathematical characterization suggested by the salient feature responsible for their increased security. We describe a concrete system known as αη and show that it is equivalent to a random cipher in which the required randomization is affected by coherent-state quantum noise. We describe the currently known security features of αη and similar systems, including lower bounds on the unicity distances against ciphertext-only and known-plaintext attacks. We show how αη used in conjunction with any standard stream cipher such as the Advanced Encryption Standard provides an additional, qualitatively different layer of security from physical encryption against known-plaintext attacks on the key. We refute some claims in the literature that αη is equivalent to a nonrandom stream cipher
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
Modeling Random Telegraph Noise Under Switched Bias Conditions Using Cyclostationary RTS Noise
van der Wel, A.P.; Klumperink, Eric A.M.; Vandamme, L.K.J.; Nauta, Bram
In this paper, we present measurements and simulation of random telegraph signal (RTS) noise in n-channel MOSFETs under periodic large signal gate-source excitation (switched bias conditions). This is particularly relevant to analog CMOS circuit design where large signal swings occur and where LF
Naseri, H; Homaeinezhad, M R; Pourkhajeh, H
2013-09-01
The major aim of this study is to describe a unified procedure for detecting noisy segments and spikes in transduced signals with a cyclic but non-stationary periodic nature. According to this procedure, the cycles of the signal (onset and offset locations) are detected. Then, the cycles are clustered into a finite number of groups based on appropriate geometrical- and frequency-based time series. Next, the median template of each time series of each cluster is calculated. Afterwards, a correlation-based technique is devised for making a comparison between a test cycle feature and the associated time series of each cluster. Finally, by applying a suitably chosen threshold for the calculated correlation values, a segment is prescribed to be either clean or noisy. As a key merit of this research, the procedure can introduce a decision support for choosing accurately orthogonal-expansion-based filtering or to remove noisy segments. In this paper, the application procedure of the proposed method is comprehensively described by applying it to phonocardiogram (PCG) signals for finding noisy cycles. The database consists of 126 records from several patients of a domestic research station acquired by a 3M Littmann(®) 3200, 4KHz sampling frequency electronic stethoscope. By implementing the noisy segments detection algorithm with this database, a sensitivity of Se=91.41% and a positive predictive value, PPV=92.86% were obtained based on physicians assessments. Copyright © 2013 Elsevier Ltd. All rights reserved.
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
Signal processing in noise waveform radar
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
Advanced digital signal processing and noise reduction
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
Orbiter CCTV video signal noise analysis
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.
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...
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
DEFF Research Database (Denmark)
Bjørnsten, Thomas
2012-01-01
The article discusses the intricate relationship between sound and signification through notions of noise. The emergence of new fields of sonic artistic practices has generated several questions of how to approach sound as aesthetic form and material. During the past decade an increased attention...... has been paid to, for instance, a category such as ‘sound art’ together with an equally strengthened interest in phenomena and concepts that fall outside the accepted aesthetic procedures and constructions of what we traditionally would term as musical sound – a recurring example being ‘noise’....
McDonough, Robert N
1995-01-01
The Second Edition is an updated revision to the authors highly successful and widely used introduction to the principles and application of the statistical theory of signal detection. This book emphasizes those theories that have been found to be particularly useful in practice including principles applied to detection problems encountered in digital communications, radar, and sonar.Detection processing based upon the fast Fourier transform
Random Correlation Matrix and De-Noising
Ken-ichi Mitsui; Yoshio Tabata
2006-01-01
In Finance, the modeling of a correlation matrix is one of the important problems. In particular, the correlation matrix obtained from market data has the noise. Here we apply the de-noising processing based on the wavelet analysis to the noisy correlation matrix, which is generated by a parametric function with random parameters. First of all, we show that two properties, i.e. symmetry and ones of all diagonal elements, of the correlation matrix preserve via the de-noising processing and the...
Seismic signal and noise on Europa
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.
GPR random noise reduction using BPD and EMD
Ostoori, Roya; Goudarzi, Alireza; Oskooi, Behrooz
2018-04-01
Ground-penetrating radar (GPR) exploration is a new high-frequency technology that explores near-surface objects and structures accurately. The high-frequency antenna of the GPR system makes it a high-resolution method compared to other geophysical methods. The frequency range of recorded GPR is so wide that random noise recording is inevitable due to acquisition. This kind of noise comes from unknown sources and its correlation to the adjacent traces is nearly zero. This characteristic of random noise along with the higher accuracy of GPR system makes denoising very important for interpretable results. The main objective of this paper is to reduce GPR random noise based on pursuing denoising using empirical mode decomposition. Our results showed that empirical mode decomposition in combination with basis pursuit denoising (BPD) provides satisfactory outputs due to the sifting process compared to the time-domain implementation of the BPD method on both synthetic and real examples. Our results demonstrate that because of the high computational costs, the BPD-empirical mode decomposition technique should only be used for heavily noisy signals.
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
Adaptive EMG noise reduction in ECG signals using noise level approximation
Marouf, Mohamed; Saranovac, Lazar
2017-12-01
In this paper the usage of noise level approximation for adaptive Electromyogram (EMG) noise reduction in the Electrocardiogram (ECG) signals is introduced. To achieve the adequate adaptiveness, a translation-invariant noise level approximation is employed. The approximation is done in the form of a guiding signal extracted as an estimation of the signal quality vs. EMG noise. The noise reduction framework is based on a bank of low pass filters. So, the adaptive noise reduction is achieved by selecting the appropriate filter with respect to the guiding signal aiming to obtain the best trade-off between the signal distortion caused by filtering and the signal readability. For the evaluation purposes; both real EMG and artificial noises are used. The tested ECG signals are from the MIT-BIH Arrhythmia Database Directory, while both real and artificial records of EMG noise are added and used in the evaluation process. Firstly, comparison with state of the art methods is conducted to verify the performance of the proposed approach in terms of noise cancellation while preserving the QRS complex waves. Additionally, the signal to noise ratio improvement after the adaptive noise reduction is computed and presented for the proposed method. Finally, the impact of adaptive noise reduction method on QRS complexes detection was studied. The tested signals are delineated using a state of the art method, and the QRS detection improvement for different SNR is presented.
Theory and Measurement of Signal-to-Noise Ratio in Continuous-Wave Noise Radar.
Stec, Bronisław; Susek, Waldemar
2018-05-06
Determination of the signal power-to-noise power ratio on the input and output of reception systems is essential to the estimation of their quality and signal reception capability. This issue is especially important in the case when both signal and noise have the same characteristic as Gaussian white noise. This article considers the problem of how a signal-to-noise ratio is changed as a result of signal processing in the correlation receiver of a noise radar in order to determine the ability to detect weak features in the presence of strong clutter-type interference. These studies concern both theoretical analysis and practical measurements of a noise radar with a digital correlation receiver for 9.2 GHz bandwidth. Firstly, signals participating individually in the correlation process are defined and the terms signal and interference are ascribed to them. Further studies show that it is possible to distinguish a signal and a noise on the input and output of a correlation receiver, respectively, when all the considered noises are in the form of white noise. Considering the above, a measurement system is designed in which it is possible to represent the actual conditions of noise radar operation and power measurement of a useful noise signal and interference noise signals—in particular the power of an internal leakage signal between a transmitter and a receiver of the noise radar. The proposed measurement stands and the obtained results show that it is possible to optimize with the use of the equipment and not with the complex processing of a noise signal. The radar parameters depend on its prospective application, such as short- and medium-range radar, ground-penetrating radar, and through-the-wall detection radar.
Computational study of noise in a large signal transduction network
Directory of Open Access Journals (Sweden)
Ruohonen Keijo
2011-06-01
Full Text Available Abstract Background Biochemical systems are inherently noisy due to the discrete reaction events that occur in a random manner. Although noise is often perceived as a disturbing factor, the system might actually benefit from it. In order to understand the role of noise better, its quality must be studied in a quantitative manner. Computational analysis and modeling play an essential role in this demanding endeavor. Results We implemented a large nonlinear signal transduction network combining protein kinase C, mitogen-activated protein kinase, phospholipase A2, and β isoform of phospholipase C networks. We simulated the network in 300 different cellular volumes using the exact Gillespie stochastic simulation algorithm and analyzed the results in both the time and frequency domain. In order to perform simulations in a reasonable time, we used modern parallel computing techniques. The analysis revealed that time and frequency domain characteristics depend on the system volume. The simulation results also indicated that there are several kinds of noise processes in the network, all of them representing different kinds of low-frequency fluctuations. In the simulations, the power of noise decreased on all frequencies when the system volume was increased. Conclusions We concluded that basic frequency domain techniques can be applied to the analysis of simulation results produced by the Gillespie stochastic simulation algorithm. This approach is suited not only to the study of fluctuations but also to the study of pure noise processes. Noise seems to have an important role in biochemical systems and its properties can be numerically studied by simulating the reacting system in different cellular volumes. Parallel computing techniques make it possible to run massive simulations in hundreds of volumes and, as a result, accurate statistics can be obtained from computational studies.
Seismic random noise attenuation using shearlet and total generalized variation
International Nuclear Information System (INIS)
Kong, Dehui; Peng, Zhenming
2015-01-01
Seismic denoising from a corrupted observation is an important part of seismic data processing which improves the signal-to-noise ratio (SNR) and resolution. In this paper, we present an effective denoising method to attenuate seismic random noise. The method takes advantage of shearlet and total generalized variation (TGV) regularization. Different regularity levels of TGV improve the quality of the final result by suppressing Gibbs artifacts caused by the shearlet. The problem is formulated as mixed constraints in a convex optimization. A Bregman algorithm is proposed to solve the proposed model. Extensive experiments based on one synthetic datum and two post-stack field data are done to compare performance. The results demonstrate that the proposed method provides superior effectiveness and preserve the structure better. (paper)
Seismic random noise attenuation using shearlet and total generalized variation
Kong, Dehui; Peng, Zhenming
2015-12-01
Seismic denoising from a corrupted observation is an important part of seismic data processing which improves the signal-to-noise ratio (SNR) and resolution. In this paper, we present an effective denoising method to attenuate seismic random noise. The method takes advantage of shearlet and total generalized variation (TGV) regularization. Different regularity levels of TGV improve the quality of the final result by suppressing Gibbs artifacts caused by the shearlet. The problem is formulated as mixed constraints in a convex optimization. A Bregman algorithm is proposed to solve the proposed model. Extensive experiments based on one synthetic datum and two post-stack field data are done to compare performance. The results demonstrate that the proposed method provides superior effectiveness and preserve the structure better.
The importance for speech intelligibility of random fluctuations in "steady" background noise.
Stone, Michael A; Füllgrabe, Christian; Mackinnon, Robert C; Moore, Brian C J
2011-11-01
Spectrally shaped steady noise is commonly used as a masker of speech. The effects of inherent random fluctuations in amplitude of such a noise are typically ignored. Here, the importance of these random fluctuations was assessed by comparing two cases. For one, speech was mixed with steady speech-shaped noise and N-channel tone vocoded, a process referred to as signal-domain mixing (SDM); this preserved the random fluctuations of the noise. For the second, the envelope of speech alone was extracted for each vocoder channel and a constant was added corresponding to the root-mean-square value of the noise envelope for that channel. This is referred to as envelope-domain mixing (EDM); it removed the random fluctuations of the noise. Sinusoidally modulated noise and a single talker were also used as backgrounds, with both SDM and EDM. Speech intelligibility was measured for N = 12, 19, and 30, with the target-to-background ratio fixed at -7 dB. For SDM, performance was best for the speech background and worst for the steady noise. For EDM, this pattern was reversed. Intelligibility with steady noise was consistently very poor for SDM, but near-ceiling for EDM, demonstrating that the random fluctuations in steady noise have a large effect.
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.
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...
Super fast physical-random number generation using laser diode frequency noises
Ushiki, Tetsuro; Doi, Kohei; Maehara, Shinya; Sato, Takashi; Ohkawa, Masashi; Ohdaira, Yasuo
2011-02-01
Random numbers can be classified as either pseudo- or physical-random in character. Pseudo-random numbers' periodicity renders them inappropriate for use in cryptographic applications, but naturally-generated physical-random numbers have no calculable periodicity, thereby making them ideally-suited to the task. The laser diode naturally produces a wideband "noise" signal that is believed to have tremendous capacity and great promise, for the rapid generation of physical-random numbers for use in cryptographic applications. We measured a laser diode's output, at a fast photo detector and generated physical-random numbers from frequency noises. We then identified and evaluated the binary-number-line's statistical properties. The result shows that physical-random number generation, at speeds as high as 40Gbps, is obtainable, using the laser diode's frequency noise characteristic.
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.
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
A signal theoretic introduction to random processes
Howard, Roy M
2015-01-01
A fresh introduction to random processes utilizing signal theory By incorporating a signal theory basis, A Signal Theoretic Introduction to Random Processes presents a unique introduction to random processes with an emphasis on the important random phenomena encountered in the electronic and communications engineering field. The strong mathematical and signal theory basis provides clarity and precision in the statement of results. The book also features: A coherent account of the mathematical fundamentals and signal theory that underpin the presented material Unique, in-depth coverage of
Signal noise/interferer combiner unit programmable (SINCUP)
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.
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)
On signal design by the R/0/ criterion for non-white Gaussian noise channels
Bordelon, D. L.
1977-01-01
The use of the cut-off rate criterion for modulation system design is investigated for channels with non-white Gaussian noise. A signal space representation of the waveform channel is developed, and the cut-off rate for vector channels with additive non-white Gaussian noise and unquantized demodulation is derived. When the signal input to the channel is a continuous random vector, maximization of the cut-off rate with constrained average signal energy leads to a water-filling interpretation of optimal energy distribution in signal space. The necessary condition for a finite signal set to maximize the cut-off rate with constrained energy and an equally likely probability assignment of signal vectors is presented, and an algorithm is outlined for numerically computing the optimum signal set. As an example, the rectangular signal set which has the water-filling average energy distribution and the optimum rectangular set are compared.
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)
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.
Ultrasonic correlator versus signal averager as a signal to noise enhancement instrument
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.
Measurement of MOSFET LF Noise Under Large Signal RF Excitation
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
Removing Background Noise with Phased Array Signal Processing
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.
Coherence method of identifying signal noise model
International Nuclear Information System (INIS)
Vavrin, J.
1981-01-01
The noise analysis method is discussed in identifying perturbance models and their parameters by a stochastic analysis of the noise model of variables measured on a reactor. The analysis of correlations is made in the frequency region using coherence analysis methods. In identifying an actual specific perturbance, its model should be determined and recognized in a compound model of the perturbance system using the results of observation. The determination of the optimum estimate of the perturbance system model is based on estimates of related spectral densities which are determined from the spectral density matrix of the measured variables. Partial and multiple coherence, partial transfers, the power spectral densities of the input and output variables of the noise model are determined from the related spectral densities. The possibilities of applying the coherence identification methods were tested on a simple case of a simulated stochastic system. Good agreement was found of the initial analytic frequency filters and the transfers identified. (B.S.)
Signal processing for boiling noise detection
International Nuclear Information System (INIS)
Ledwidge, T.J.; Black, J.L.
1989-01-01
The present paper deals with investigations of acoustic signals from a boiling experiment performed on the KNS I loop at KfK Karlsruhe. Signals have been analysed in frequency as well as in time domain. Signal characteristics successfully used to detect the boiling process have been found in time domain. (author). 6 refs, figs
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.
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....
Empirical mode decomposition of the ECG signal for noise removal
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.
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.
Light field reconstruction robust to signal dependent noise
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.
Realistic noise-tolerant randomness amplification using finite number of devices
Brandão, Fernando G. S. L.; Ramanathan, Ravishankar; Grudka, Andrzej; Horodecki, Karol; Horodecki, Michał; Horodecki, Paweł; Szarek, Tomasz; Wojewódka, Hanna
2016-04-01
Randomness is a fundamental concept, with implications from security of modern data systems, to fundamental laws of nature and even the philosophy of science. Randomness is called certified if it describes events that cannot be pre-determined by an external adversary. It is known that weak certified randomness can be amplified to nearly ideal randomness using quantum-mechanical systems. However, so far, it was unclear whether randomness amplification is a realistic task, as the existing proposals either do not tolerate noise or require an unbounded number of different devices. Here we provide an error-tolerant protocol using a finite number of devices for amplifying arbitrary weak randomness into nearly perfect random bits, which are secure against a no-signalling adversary. The correctness of the protocol is assessed by violating a Bell inequality, with the degree of violation determining the noise tolerance threshold. An experimental realization of the protocol is within reach of current technology.
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...
The clustering of local maxima in random noise
International Nuclear Information System (INIS)
Coles, P.
1989-01-01
A mixture of analytic and numerical techniques is used to study the clustering properties of local maxima of random noise. Technical complexities restrict us to the case of 1D noise, but the results obtained should give a reasonably accurate picture of the behaviour of cosmological density peaks in noise defined on a 3D domain. We give estimates of the two-point correlation function of local maxima, for both Gaussian and non-Gaussian noise and show that previous approximations are not accurate. (author)
Random Valued Impulse Noise Removal Using Region Based Detection Approach
Directory of Open Access Journals (Sweden)
S. Banerjee
2017-12-01
Full Text Available Removal of random valued noisy pixel is extremely challenging when the noise density is above 50%. The existing filters are generally not capable of eliminating such noise when density is above 70%. In this paper a region wise density based detection algorithm for random valued impulse noise has been proposed. On the basis of the intensity values, the pixels of a particular window are sorted and then stored into four regions. The higher density based region is considered for stepwise detection of noisy pixels. As a result of this detection scheme a maximum of 75% of noisy pixels can be detected. For this purpose this paper proposes a unique noise removal algorithm. It was experimentally proved that the proposed algorithm not only performs exceptionally when it comes to visual qualitative judgment of standard images but also this filter combination outsmarts the existing algorithm in terms of MSE, PSNR and SSIM comparison even up to 70% noise density level.
Reducing Noise by Repetition: Introduction to Signal Averaging
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…
Signal Detection with Criterion Noise: Applications to Recognition Memory
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…
Muon Signals at a Low Signal-to-Noise Ratio Environment
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).
Comparison of methods for removing electromagnetic noise from electromyographic signals.
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)
Effects of random noise in a dynamical model of love
Energy Technology Data Exchange (ETDEWEB)
Xu Yong, E-mail: hsux3@nwpu.edu.cn [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China); Gu Rencai; Zhang Huiqing [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China)
2011-07-15
Highlights: > We model the complexity and unpredictability of psychology as Gaussian white noise. > The stochastic system of love is considered including bifurcation and chaos. > We show that noise can both suppress and induce chaos in dynamical models of love. - Abstract: This paper aims to investigate the stochastic model of love and the effects of random noise. We first revisit the deterministic model of love and some basic properties are presented such as: symmetry, dissipation, fixed points (equilibrium), chaotic behaviors and chaotic attractors. Then we construct a stochastic love-triangle model with parametric random excitation due to the complexity and unpredictability of the psychological system, where the randomness is modeled as the standard Gaussian noise. Stochastic dynamics under different three cases of 'Romeo's romantic style', are examined and two kinds of bifurcations versus the noise intensity parameter are observed by the criteria of changes of top Lyapunov exponent and shape of stationary probability density function (PDF) respectively. The phase portraits and time history are carried out to verify the proposed results, and the good agreement can be found. And also the dual roles of the random noise, namely suppressing and inducing chaos are revealed.
Effects of random noise in a dynamical model of love
International Nuclear Information System (INIS)
Xu Yong; Gu Rencai; Zhang Huiqing
2011-01-01
Highlights: → We model the complexity and unpredictability of psychology as Gaussian white noise. → The stochastic system of love is considered including bifurcation and chaos. → We show that noise can both suppress and induce chaos in dynamical models of love. - Abstract: This paper aims to investigate the stochastic model of love and the effects of random noise. We first revisit the deterministic model of love and some basic properties are presented such as: symmetry, dissipation, fixed points (equilibrium), chaotic behaviors and chaotic attractors. Then we construct a stochastic love-triangle model with parametric random excitation due to the complexity and unpredictability of the psychological system, where the randomness is modeled as the standard Gaussian noise. Stochastic dynamics under different three cases of 'Romeo's romantic style', are examined and two kinds of bifurcations versus the noise intensity parameter are observed by the criteria of changes of top Lyapunov exponent and shape of stationary probability density function (PDF) respectively. The phase portraits and time history are carried out to verify the proposed results, and the good agreement can be found. And also the dual roles of the random noise, namely suppressing and inducing chaos are revealed.
Signal and noise in financial correlation matrices
Burda, Zdzisław; Jurkiewicz, Jerzy
2004-12-01
Using Random Matrix Theory one can derive exact relations between the eigenvalue spectrum of the covariance matrix and the eigenvalue spectrum of its estimator (experimentally measured correlation matrix). These relations will be used to analyze a particular case of the correlations in financial series and to show that contrary to earlier claims, correlations can be measured also in the “random” part of the spectrum. Implications for the portfolio optimization are briefly discussed.
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.
Innovative signal processing for Johnson Noise thermometry
Energy Technology Data Exchange (ETDEWEB)
Ezell, N. Dianne Bull [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Britton, Jr, Charles L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Roberts, Michael [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
2016-07-01
This report summarizes the newly developed algorithm that subtracted the Electromagnetic Interference (EMI). The EMI performance is very important to this measurement because any interference in the form on pickup from external signal sources from such as fluorescent lighting ballasts, motors, etc. can skew the measurement. Two methods of removing EMI were developed and tested at various locations. This report also summarizes the testing performed at different facilities outside Oak Ridge National Laboratory using both EMI removal techniques. The first EMI removal technique reviewed in previous milestone reports and therefore this report will detail the second method.
Subspace Signal Processing in Structured Noise
1990-12-01
1.7 Motivation for the Model ....... ........................... 8 1.8 E x am p les...S). We do not require that H be orthogonal to S. * 1.7 Motivation for the Model The linear model is quite versatile in terms of the types of signals...cross terms zero, we choose . = (SHs)- mS~u’ (3.69) This implies that = Ps4 , (3.70) and S t s (3.71) : = Ps . RPs -. The last step is to maximize
Noise in Neural Networks: Thresholds, Hysteresis, and Neuromodulation of Signal-To-Noise
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.
The deterministic chaos and random noise in turbulent jet
International Nuclear Information System (INIS)
Yao, Tian-Liang; Liu, Hai-Feng; Xu, Jian-Liang; Li, Wei-Feng
2014-01-01
A turbulent flow is usually treated as a superposition of coherent structure and incoherent turbulence. In this paper, the largest Lyapunov exponent and the random noise in the near field of round jet and plane jet are estimated with our previously proposed method of chaotic time series analysis [T. L. Yao, et al., Chaos 22, 033102 (2012)]. The results show that the largest Lyapunov exponents of the round jet and plane jet are in direct proportion to the reciprocal of the integral time scale of turbulence, which is in accordance with the results of the dimensional analysis, and the proportionality coefficients are equal. In addition, the random noise of the round jet and plane jet has the same linear relation with the Kolmogorov velocity scale of turbulence. As a result, the random noise may well be from the incoherent disturbance in turbulence, and the coherent structure in turbulence may well follow the rule of chaotic motion
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.
Stochastic model for detection of signals in noise
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...
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.
Directory of Open Access Journals (Sweden)
R. Caballero-Águila
2014-01-01
Full Text Available The optimal least-squares linear estimation problem is addressed for a class of discrete-time multisensor linear stochastic systems subject to randomly delayed measurements with different delay rates. For each sensor, a different binary sequence is used to model the delay process. The measured outputs are perturbed by both random parameter matrices and one-step autocorrelated and cross correlated noises. Using an innovation approach, computationally simple recursive algorithms are obtained for the prediction, filtering, and smoothing problems, without requiring full knowledge of the state-space model generating the signal process, but only the information provided by the delay probabilities and the mean and covariance functions of the processes (signal, random parameter matrices, and noises involved in the observation model. The accuracy of the estimators is measured by their error covariance matrices, which allow us to analyze the estimator performance in a numerical simulation example that illustrates the feasibility of the proposed algorithms.
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)
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.
Increasing the Signal to Noise Ratio in a Chemistry Laboratory ...
African Journals Online (AJOL)
Increasing the Signal to Noise Ratio in a Chemistry Laboratory - Improving a Practical for Academic Development Students. ... Analysis of data collected in 2001 shows that the changes made a significant impact on the effectiveness of the laboratory session. South African Journal of Chemistry Vol.56 2003: 47-53 ...
Investigations of SPND noise signals in VVER-440 reactors
International Nuclear Information System (INIS)
Kiss, S.; Lipcsei, S.; Hazi, G.
2001-01-01
This paper describes and characterises SPND noise measurements of an operating VVER-440 nuclear reactor. Characteristics of the signal can be radically influenced by the geometrical properties of the detector and the cable and by the measuring arrangement. Structure of phase spectra showing propagating perturbations measured on uncompensated SPN detectors is studied through models.(author)
An effective approach to attenuate random noise based on compressive sensing and curvelet transform
International Nuclear Information System (INIS)
Liu, Wei; Cao, Siyuan; Zu, Shaohuan; Chen, Yangkang
2016-01-01
Random noise attenuation is an important step in seismic data processing. In this paper, we propose a novel denoising approach based on compressive sensing and the curvelet transform. We formulate the random noise attenuation problem as an L _1 norm regularized optimization problem. We propose to use the curvelet transform as the sparse transform in the optimization problem to regularize the sparse coefficients in order to separate signal and noise and to use the gradient projection for sparse reconstruction (GPSR) algorithm to solve the formulated optimization problem with an easy implementation and a fast convergence. We tested the performance of our proposed approach on both synthetic and field seismic data. Numerical results show that the proposed approach can effectively suppress the distortion near the edge of seismic events during the noise attenuation process and has high computational efficiency compared with the traditional curvelet thresholding and iterative soft thresholding based denoising methods. Besides, compared with f-x deconvolution, the proposed denoising method is capable of eliminating the random noise more effectively while preserving more useful signals. (paper)
Signal and noise modeling in confocal laser scanning fluorescence microscopy.
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.
Random noise characterization on the carrying capacities of a ...
African Journals Online (AJOL)
The process of the survival of species dependent on a limited resource in a polluted environment which isnot a new idea can be described by the technique of a mathematical modelling. We have utilised the technique of a numerical simulation to study the impact of environmental random noise on the carrying capacities of ...
Debuncher Momentum Cooling Systems Signal to Noise Measurements
Energy Technology Data Exchange (ETDEWEB)
Pasquinelli, Ralph J.; /Fermilab
2001-12-18
The Debuncher Momentum cooling systems were carefully measured for signal to noise. It was observed that cooling performance was not optimum. Closer inspection shows that the installed front-end bandpass filters are wider than the pickup response. (The original filters were specified to be wider so that none of the available bandwidth would be clipped.) The end result is excess noise is amplified and passed onto the kickers unimpeded, hence, reducing the achievable system gain. From this data, new filters should be designed to improve performance. New system bandwidths are specified on the data figures. Also included are the transfer function measurements that clearly show adjacent band response. In band 4 upper, the adjacent lobes are strong and out of phase. This is also degrading the system performance. The correlation between spectrum analyzer signal to noise and network analyzer system transfer functions is very strong. The table below has a calculation of expected improvement of front noise reduction by means of building new front-end bandpass filters. The calculation is based on a flat input noise spectrum and is a linear estimation of improvement. The listed 3dB bandwidths of the original filters are from measured data. The expected bandwidth is taken from the linear spectrum analyzer plots and is closer to a 10 dB bandwidth making the percentage improvement conservative. The signal to noise measurements are taken with circulating pbars in the Debuncher. One cooling system was measured at a time with all others off. Beam currents are below ten microamperes.
Debuncher Momentum Cooling Systems Signal to Noise Measurements
International Nuclear Information System (INIS)
Pasquinelli, Ralph J.
2001-01-01
The Debuncher Momentum cooling systems were carefully measured for signal to noise. It was observed that cooling performance was not optimum. Closer inspection shows that the installed front-end bandpass filters are wider than the pickup response. (The original filters were specified to be wider so that none of the available bandwidth would be clipped.) The end result is excess noise is amplified and passed onto the kickers unimpeded, hence, reducing the achievable system gain. From this data, new filters should be designed to improve performance. New system bandwidths are specified on the data figures. Also included are the transfer function measurements that clearly show adjacent band response. In band 4 upper, the adjacent lobes are strong and out of phase. This is also degrading the system performance. The correlation between spectrum analyzer signal to noise and network analyzer system transfer functions is very strong. The table below has a calculation of expected improvement of front noise reduction by means of building new front-end bandpass filters. The calculation is based on a flat input noise spectrum and is a linear estimation of improvement. The listed 3dB bandwidths of the original filters are from measured data. The expected bandwidth is taken from the linear spectrum analyzer plots and is closer to a 10 dB bandwidth making the percentage improvement conservative. The signal to noise measurements are taken with circulating pbars in the Debuncher. One cooling system was measured at a time with all others off. Beam currents are below ten microamperes.
Photonic microwave signals with zeptosecond-level absolute timing noise
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.
On signal design by the R sub 0 criterion for non-white Gaussian noise channels
Bordelon, D. L.
1976-01-01
The use of the R sub 0 criterion for modulation system design is investigated for channels with non-white Gaussian noise. A signal space representation of the waveform channel is developed, and the cut-off rate R sub 0 for vector channels with additive nonwhite Gaussian noise and unquantized demodulation is derived. When the signal unput to the channel is a continuous random vector, maximization of R sub 0 with constrained average signal energy leads to a water-filling interpretation of optimal energy distribution in signal space. The necessary condition for a finite signal set to maximize R sub 0 with constrained energy and an equally likely probability assignment of signal vectors is presented, and an algorithm is outlined for numerically computing the optimum signal set. A necessary condition on a constrained energy, finite signal set is found which maximizes a Taylor series approximation of R sub 0. This signal set is compared with the finite signal set which has the water-filling average energy distribution.
Effects of signal salience and noise on performance and stress in an abbreviated vigil
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
An adaptive segment method for smoothing lidar signal based on noise estimation
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.
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
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.
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).
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
Blind signal processing algorithms under DC biased Gaussian noise
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.
Random walk in dynamically disordered chains: Poisson white noise disorder
International Nuclear Information System (INIS)
Hernandez-Garcia, E.; Pesquera, L.; Rodriguez, M.A.; San Miguel, M.
1989-01-01
Exact solutions are given for a variety of models of random walks in a chain with time-dependent disorder. Dynamic disorder is modeled by white Poisson noise. Models with site-independent (global) and site-dependent (local) disorder are considered. Results are described in terms of an affective random walk in a nondisordered medium. In the cases of global disorder the effective random walk contains multistep transitions, so that the continuous limit is not a diffusion process. In the cases of local disorder the effective process is equivalent to usual random walk in the absence of disorder but with slower diffusion. Difficulties associated with the continuous-limit representation of random walk in a disordered chain are discussed. In particular, the authors consider explicit cases in which taking the continuous limit and averaging over disorder sources do not commute
Signal-to-noise limitations in white light holography.
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.
Directory of Open Access Journals (Sweden)
Edward Nuhfer
2016-01-01
Full Text Available Self-assessment measures of competency are blends of an authentic self-assessment signal that researchers seek to measure and random disorder or "noise" that accompanies that signal. In this study, we use random number simulations to explore how random noise affects critical aspects of self-assessment investigations: reliability, correlation, critical sample size, and the graphical representations of self-assessment data. We show that graphical conventions common in the self-assessment literature introduce artifacts that invite misinterpretation. Troublesome conventions include: (y minus x vs. (x scatterplots; (y minus x vs. (x column graphs aggregated as quantiles; line charts that display data aggregated as quantiles; and some histograms. Graphical conventions that generate minimal artifacts include scatterplots with a best-fit line that depict (y vs. (x measures (self-assessed competence vs. measured competence plotted by individual participant scores, and (y vs. (x scatterplots of collective average measures of all participants plotted item-by-item. This last graphic convention attenuates noise and improves the definition of the signal. To provide relevant comparisons across varied graphical conventions, we use a single dataset derived from paired measures of 1154 participants' self-assessed competence and demonstrated competence in science literacy. Our results show that different numerical approaches employed in investigating and describing self-assessment accuracy are not equally valid. By modeling this dataset with random numbers, we show how recognizing the varied expressions of randomness in self-assessment data can improve the validity of numeracy-based descriptions of self-assessment.
Linear signal noise summer accurately determines and controls S/N ratio
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.
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...
Quantum-noise randomized data encryption for wavelength-division-multiplexed fiber-optic networks
International Nuclear Information System (INIS)
Corndorf, Eric; Liang Chuang; Kanter, Gregory S.; Kumar, Prem; Yuen, Horace P.
2005-01-01
We demonstrate high-rate randomized data-encryption through optical fibers using the inherent quantum-measurement noise of coherent states of light. Specifically, we demonstrate 650 Mbit/s data encryption through a 10 Gbit/s data-bearing, in-line amplified 200-km-long line. In our protocol, legitimate users (who share a short secret key) communicate using an M-ry signal set while an attacker (who does not share the secret key) is forced to contend with the fundamental and irreducible quantum-measurement noise of coherent states. Implementations of our protocol using both polarization-encoded signal sets as well as polarization-insensitive phase-keyed signal sets are experimentally and theoretically evaluated. Different from the performance criteria for the cryptographic objective of key generation (quantum key-generation), one possible set of performance criteria for the cryptographic objective of data encryption is established and carefully considered
Image restoration by Wiener filtering in the presence of signal-dependent noise.
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.
Listening to the Noise: Random Fluctuations Reveal Gene Network Parameters
Munsky, Brian; Trinh, Brooke; Khammash, Mustafa
2010-03-01
The cellular environment is abuzz with noise originating from the inherent random motion of reacting molecules in the living cell. In this noisy environment, clonal cell populations exhibit cell-to-cell variability that can manifest significant prototypical differences. Noise induced stochastic fluctuations in cellular constituents can be measured and their statistics quantified using flow cytometry, single molecule fluorescence in situ hybridization, time lapse fluorescence microscopy and other single cell and single molecule measurement techniques. We show that these random fluctuations carry within them valuable information about the underlying genetic network. Far from being a nuisance, the ever-present cellular noise acts as a rich source of excitation that, when processed through a gene network, carries its distinctive fingerprint that encodes a wealth of information about that network. We demonstrate that in some cases the analysis of these random fluctuations enables the full identification of network parameters, including those that may otherwise be difficult to measure. We use theoretical investigations to establish experimental guidelines for the identification of gene regulatory networks, and we apply these guideline to experimentally identify predictive models for different regulatory mechanisms in bacteria and yeast.
Liberti, M; Paffi, A; Maggio, F; De Angelis, A; Apollonio, F; d'Inzeo, G
2009-01-01
A number of experimental investigations have evidenced the extraordinary sensitivity of neuronal cells to weak input stimulations, including electromagnetic (EM) fields. Moreover, it has been shown that biological noise, due to random channels gating, acts as a tuning factor in neuronal processing, according to the stochastic resonant (SR) paradigm. In this work the attention is focused on noise arising from the stochastic gating of ionic channels in a model of Ranvier node of acoustic fibers. The small number of channels gives rise to a high noise level, which is able to cause a spike train generation even in the absence of stimulations. A SR behavior has been observed in the model for the detection of sinusoidal signals at frequencies typical of the speech.
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
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.
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
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.
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.
Study of improving signal-noise ratio for fluorescence channel
Wang, Guoqing; Li, Xin; Lou, Yue; Chen, Dong; Zhao, Xin; Wang, Ran; Yan, Debao; Zhao, Qi
2017-10-01
Laser-induced fluorescence(LIFS), which is one of most effective discrimination methods to identify the material at the molecular level by inducing fluorescence spectrum, has been popularized for its fast and accurate probe's results. According to the research, violet laser or ultraviolet laser is always used as excitation light source. While, There is no atmospheric window for violet laser and ultraviolet laser, causing laser attenuation along its propagation path. What's worse, as the laser reaching sample, part of the light is reflected. That is, excitation laser really react on sample to produce fluorescence is very poor, leading to weak fluorescence mingled with the background light collected by LIFS' processing unit, when it used outdoor. In order to spread LIFS to remote probing under the complex background, study of improving signal-noise ratio for fluorescence channel is a meaningful work. Enhancing the fluorescence intensity and inhibiting background light both can improve fluorescence' signal-noise ratio. In this article, three different approaches of inhibiting background light are discussed to improve the signal-noise ratio of LIFS. The first method is increasing fluorescence excitation area in the proportion of LIFS' collecting field by expanding laser beam, if the collecting filed is fixed. The second one is changing field angle base to accommodate laser divergence angle. The third one is setting a very narrow gating circuit to control acquisition circuit, which is shortly open only when fluorescence arriving. At some level, these methods all can reduce the background light. But after discussion, the third one is best with adding gating acquisition circuit to acquisition circuit instead of changing light path, which is effective and economic.
Lidar signal-to-noise ratio improvements: Considerations and techniques
Hassebo, Yasser Y.
The primary objective of this study is to improve lidar signal-to-noise ratio (SNR) and hence extend attainable lidar ranges through reduction of the sky background noise (BGP), which dominates other sources of noise in daytime operations. This is particularly important for Raman lidar techniques where the Raman backscattered signal of interest is relatively weak compared with the elastic backscatter lidars. Two approaches for reduction of sky background noise are considered: (1) Improvements in lidar SNR by optimization of the design of the lidar receiver were examined by a series of simulations. This part of the research concentrated on biaxial lidar systems, where overlap between laser beam and receiver field of view (FOV) is an important aspect of noise considerations. The first optimized design evolved is a wedge shaped aperture. While this design has the virtue of greatly reducing background light, it is difficult to implement practically, requiring both changes in area and position with lidar range. A second more practical approach, which preserves some of the advantages of the wedge design, was also evolved. This uses a smaller area circular aperture optimally located in the image plane for desired ranges. Simulated numerical results for a biaxial lidar have shown that the best receiver parameters selection is one using a small circular aperture (field stop) with a small telescope focal length f, to ensure the minimum FOV that accepts all return signals over the entire lidar range while at the same time minimizing detected BGP and hence maximizing lidar SNR and attainable lidar ranges. The improvement in lidar SNR was up to 18%. (2) A polarization selection technique was implemented to reduce sky background signal for linearly polarized monostatic elastic backscatter lidar measurements. The technique takes advantage of naturally occurring polarization properties in scattered sky light, and then ensures that both the lidar transmitter and receiver track and
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)
Low-Noise CMOS Circuits for On-Chip Signal Processing in Focal-Plane Arrays
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
Signal-to-noise ratios of multiplexing spectrometers in high backgrounds
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.
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.
Indirect estimation of signal-dependent noise with nonadaptive heterogeneous samples.
Azzari, Lucio; Foi, Alessandro
2014-08-01
We consider the estimation of signal-dependent noise from a single image. Unlike conventional algorithms that build a scatterplot of local mean-variance pairs from either small or adaptively selected homogeneous data samples, our proposed approach relies on arbitrarily large patches of heterogeneous data extracted at random from the image. We demonstrate the feasibility of our approach through an extensive theoretical analysis based on mixture of Gaussian distributions. A prototype algorithm is also developed in order to validate the approach on simulated data as well as on real camera raw images.
Investigation on phase noise of the signal from a singly resonant optical parametric oscillator
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 and signal interference in optical fiber transmission systems an optimum design approach
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
A method of signal transmission path analysis for multivariate random processes
International Nuclear Information System (INIS)
Oguma, Ritsuo
1984-04-01
A method for noise analysis called ''STP (signal transmission path) analysis'' is presentd as a tool to identify noise sources and their propagation paths in multivariate random proceses. Basic idea of the analysis is to identify, via time series analysis, effective network for the signal power transmission among variables in the system and to make use of its information to the noise analysis. In the present paper, we accomplish this through two steps of signal processings; first, we estimate, using noise power contribution analysis, variables which have large contribution to the power spectrum of interest, and then evaluate the STPs for each pair of variables to identify STPs which play significant role for the generated noise to transmit to the variable under evaluation. The latter part of the analysis is executed through comparison of partial coherence function and newly introduced partial noise power contribution function. This paper presents the procedure of the STP analysis and demonstrates, using simulation data as well as Borssele PWR noise data, its effectiveness for investigation of noise generation and propagation mechanisms. (author)
An X-ray CCD signal generator with true random arrival time
International Nuclear Information System (INIS)
Huo Jia; Xu Yuming; Chen Yong; Cui Weiwei; Li Wei; Zhang Ziliang; Han Dawei; Wang Yusan; Wang Juan
2011-01-01
An FPGA-based true random signal generator with adjustable amplitude and exponential distribution of time interval is presented. Since traditional true random number generators (TRNG) are resource costly and difficult to transplant, we employed a method of random number generation based on jitter and phase noise in ring oscillators formed by gates in an FPGA. In order to improve the random characteristics, a combination of two different pseudo-random processing circuits is used for post processing. The effects of the design parameters, such as sample frequency are discussed. Statistical tests indicate that the generator can well simulate the timing behavior of random signals with Poisson distribution. The X-ray CCD signal generator will be used in debugging the CCD readout system of the Low Energy X-ray Instrument onboard the Hard X-ray Modulation Telescope (HXMT). (authors)
Quasi-Coherent Noise Jamming to LFM Radar Based on Pseudo-random Sequence Phase-modulation
Directory of Open Access Journals (Sweden)
N. Tai
2015-12-01
Full Text Available A novel quasi-coherent noise jamming method is proposed against linear frequency modulation (LFM signal and pulse compression radar. Based on the structure of digital radio frequency memory (DRFM, the jamming signal is acquired by the pseudo-random sequence phase-modulation of sampled radar signal. The characteristic of jamming signal in time domain and frequency domain is analyzed in detail. Results of ambiguity function indicate that the blanket jamming effect along the range direction will be formed when jamming signal passes through the matched filter. By flexible controlling the parameters of interrupted-sampling pulse and pseudo-random sequence, different covering distances and jamming effects will be achieved. When the jamming power is equivalent, this jamming obtains higher process gain compared with non-coherent jamming. The jamming signal enhances the detection threshold and the real target avoids being detected. Simulation results and circuit engineering implementation validate that the jamming signal covers real target effectively.
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.
Novel Signal Noise Reduction Method through Cluster Analysis, Applied to Photoplethysmography.
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.
A Dynamical System Exhibits High Signal-to-noise Ratio Gain by Stochastic Resonance
Makra, Peter; Gingl, Zoltan
2003-05-01
On the basis of mixed-signal simulations, we demonstrate that signal-to-noise ratio (SNR) gains much greater than unity can be obtained in the double-well potential through stochastic resonance (SR) with a symmetric periodic pulse train as deterministic and Gaussian white noise as random excitation. We also show that significant SNR improvement is possible in this system even for a sub-threshold sinusoid input if, instead of the commonly used narrow-band SNR, we apply an equally simple but much more realistic wide-band SNR definition. Using the latter result as an argument, we draw attention to the fact that the choice of the measure to reflect signal quality is critical with regard to the extent of signal improvement observed, and urge reconsideration of the practice prevalent in SR studies that most often the narrow-band SNR is used to characterise SR. Finally, we pose some questions concerning the possibilities of applying SNR improvement in practical set-ups.
New high resolution Random Telegraph Noise (RTN) characterization method for resistive RAM
Maestro, M.; Diaz, J.; Crespo-Yepes, A.; Gonzalez, M. B.; Martin-Martinez, J.; Rodriguez, R.; Nafria, M.; Campabadal, F.; Aymerich, X.
2016-01-01
Random Telegraph Noise (RTN) is one of the main reliability problems of resistive switching-based memories. To understand the physics behind RTN, a complete and accurate RTN characterization is required. The standard equipment used to analyse RTN has a typical time resolution of ∼2 ms which prevents evaluating fast phenomena. In this work, a new RTN measurement procedure, which increases the measurement time resolution to 2 μs, is proposed. The experimental set-up, together with the recently proposed Weighted Time Lag (W-LT) method for the analysis of RTN signals, allows obtaining a more detailed and precise information about the RTN phenomenon.
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.
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.
MOSFET LF noise under Large Signal Excitation: Measurement, Modelling and Application
van der Wel, A.P.
2005-01-01
Regarding LF noise in MOSFETs, it is noted that the MOSFET is a surface channel device. Both n and p-channel devices exhibit similar low frequency (LF) noise behaviour that can be explained by a carrier number fluctuation model (section 3.5). LF noise in MOSFETs is predominantly caused by Random
Photoacoustic signal and noise analysis for Si thin plate: signal correction in frequency domain.
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.
A Bayesian test for periodic signals in red noise
Vaughan, S.
2010-02-01
Many astrophysical sources, especially compact accreting sources, show strong, random brightness fluctuations with broad power spectra in addition to periodic or quasi-periodic oscillations (QPOs) that have narrower spectra. The random nature of the dominant source of variance greatly complicates the process of searching for possible weak periodic signals. We have addressed this problem using the tools of Bayesian statistics; in particular, using Markov Chain Monte Carlo techniques to approximate the posterior distribution of model parameters, and posterior predictive model checking to assess model fits and search for periodogram outliers that may represent periodic signals. The methods developed are applied to two example data sets, both long XMM-Newton observations of highly variable Seyfert 1 galaxies: RE J1034 + 396 and Mrk 766. In both cases, a bend (or break) in the power spectrum is evident. In the case of RE J1034 + 396, the previously reported QPO is found but with somewhat weaker statistical significance than reported in previous analyses. The difference is due partly to the improved continuum modelling, better treatment of nuisance parameters and partly to different data selection methods.
Balanced detection for self-mixing interferometry to improve signal-to-noise ratio
Zhao, Changming; Norgia, Michele; Li, Kun
2018-01-01
We apply balanced detection to self-mixing interferometry for displacement and vibration measurement, using two photodiodes for implementing a differential acquisition. The method is based on the phase opposition of the self-mixing signal measured between the two laser diode facet outputs. The balanced signal obtained by enlarging the self-mixing signal, also by canceling of the common-due noises mainly due to disturbances on laser supply and transimpedance amplifier. Experimental results demonstrate the signal-to-noise ratio significantly improves, with almost twice signals enhancement and more than half noise decreasing. This method allows for more robust, longer-distance measurement systems, especially using fringe-counting.
Detecting impact signal in mechanical fault diagnosis under chaotic and Gaussian background noise
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.
Downhole microseismic signal-to-noise ratio enhancement via strip matching shearlet transform
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.
CORTICAL ENCODING OF SIGNALS IN NOISE: EFFECTS OF STIMULUS TYPE AND RECORDING PARADIGM
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
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)
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.
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
Study of signal-to-noise ratio in digital mammography
Kato, Yuri; Fujita, Naotoshi; Kodera, Yoshie
2009-02-01
Mammography techniques have recently advanced from those using analog systems (the screen-film system) to those using digital systems; for example, computed radiography (CR) and flat-panel detectors (FPDs) are nowadays used in mammography. Further, phase contrast mammography (PCM)-a digital technique by which images with a magnification of 1.75× can be obtained-is now available in the market. We studied the effect of the air gap in PCM and evaluated the effectiveness of an antiscatter x-ray grid in conventional mammography (CM) by measuring the scatter fraction ratio (SFR) and relative signal-to-noise ratio (rSNR) and comparing them between PCM and the digital CM. The results indicated that the SFRs for the CM images obtained with a grid were the lowest and that these ratios were almost the same as those for the PCM images. In contrast, the rSNRs for the PCM images were the highest, which means that the scattering of x-rays was sufficiently reduced by the air gap without the loss of primary x-rays.
Interferometric Imaging of Geostationary Satellites: Signal-to-Noise Considerations
Jorgensen, A.; Schmitt, H.; Mozurkewich, D.; Armstrong, J.; Restaino, S.; Hindsley, R.
2011-09-01
Geostationary satellites are generally too small to image at high resolution with conventional single-dish telescopes. Obtaining many resolution elements across a typical geostationary satellite body requires a single-dish telescope with a diameter of 10’s of m or more, with a good adaptive optics system. An alternative is to use an optical/infrared interferometer consisting of multiple smaller telescopes in an array configuration. In this paper and companion papers1, 2 we discuss the performance of a common-mount 30-element interferometer. The instrument design is presented by Mozurkewich et al.,1 and imaging performance is presented by Schmitt et al.2 In this paper we discuss signal-to-noise ratio for both fringe-tracking and imaging. We conclude that the common-mount interferometer is sufficiently sensitive to track fringes on the majority of geostationary satellites. We also find that high-fidelity images can be obtained after a short integration time of a few minutes to a few tens of minutes.
Eckstein, M. P.; Ahumada, A. J. Jr; Watson, A. B.
1997-01-01
Studies of visual detection of a signal superimposed on one of two identical backgrounds show performance degradation when the background has high contrast and is similar in spatial frequency and/or orientation to the signal. To account for this finding, models include a contrast gain control mechanism that pools activity across spatial frequency, orientation and space to inhibit (divisively) the response of the receptor sensitive to the signal. In tasks in which the observer has to detect a known signal added to one of M different backgrounds grounds due to added visual noise, the main sources of degradation are the stochastic noise in the image and the suboptimal visual processing. We investigate how these two sources of degradation (contrast gain control and variations in the background) interact in a task in which the signal is embedded in one of M locations in a complex spatially varying background (structured background). We use backgrounds extracted from patient digital medical images. To isolate effects of the fixed deterministic background (the contrast gain control) from the effects of the background variations, we conduct detection experiments with three different background conditions: (1) uniform background, (2) a repeated sample of structured background, and (3) different samples of structured background. Results show that human visual detection degrades from the uniform background condition to the repeated background condition and degrades even further in the different backgrounds condition. These results suggest that both the contrast gain control mechanism and the background random variations degrade human performance in detection of a signal in a complex, spatially varying background. A filter model and added white noise are used to generate estimates of sampling efficiencies, an equivalent internal noise, an equivalent contrast-gain-control-induced noise, and an equivalent noise due to the variations in the structured background.
Ichino, Shinya; Mawaki, Takezo; Teramoto, Akinobu; Kuroda, Rihito; Park, Hyeonwoo; Wakashima, Shunichi; Goto, Tetsuya; Suwa, Tomoyuki; Sugawa, Shigetoshi
2018-04-01
Random telegraph noise (RTN), which occurs in in-pixel source follower (SF) transistors, has become one of the most critical problems in high-sensitivity CMOS image sensors (CIS) because it is a limiting factor of dark random noise. In this paper, the behaviors of RTN toward changes in SF drain current conditions were analyzed using a low-noise array test circuit measurement system with a floor noise of 35 µV rms. In addition to statistical analysis by measuring a large number of transistors (18048 transistors), we also analyzed the behaviors of RTN parameters such as amplitude and time constants in the individual transistors. It is demonstrated that the appearance probability of RTN becomes small under a small drain current condition, although large-amplitude RTN tends to appear in a very small number of cells.
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
Block matching 3D random noise filtering for absorption optical projection tomography
International Nuclear Information System (INIS)
Fumene Feruglio, P; Vinegoni, C; Weissleder, R; Gros, J; Sbarbati, A
2010-01-01
Absorption and emission optical projection tomography (OPT), alternatively referred to as optical computed tomography (optical-CT) and optical-emission computed tomography (optical-ECT), are recently developed three-dimensional imaging techniques with value for developmental biology and ex vivo gene expression studies. The techniques' principles are similar to the ones used for x-ray computed tomography and are based on the approximation of negligible light scattering in optically cleared samples. The optical clearing is achieved by a chemical procedure which aims at substituting the cellular fluids within the sample with a cell membranes' index matching solution. Once cleared the sample presents very low scattering and is then illuminated with a light collimated beam whose intensity is captured in transillumination mode by a CCD camera. Different projection images of the sample are subsequently obtained over a 360 0 full rotation, and a standard backprojection algorithm can be used in a similar fashion as for x-ray tomography in order to obtain absorption maps. Because not all biological samples present significant absorption contrast, it is not always possible to obtain projections with a good signal-to-noise ratio, a condition necessary to achieve high-quality tomographic reconstructions. Such is the case for example, for early stage's embryos. In this work we demonstrate how, through the use of a random noise removal algorithm, the image quality of the reconstructions can be considerably improved even when the noise is strongly present in the acquired projections. Specifically, we implemented a block matching 3D (BM3D) filter applying it separately on each acquired transillumination projection before performing a complete three-dimensional tomographical reconstruction. To test the efficiency of the adopted filtering scheme, a phantom and a real biological sample were processed. In both cases, the BM3D filter led to a signal-to-noise ratio increment of over 30 d
Acceptance noise level: effects of the speech signal, babble, and listener language.
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.
Savaux, Vincent
2014-01-01
This book presents an algorithm for the detection of an orthogonal frequency division multiplexing (OFDM) signal in a cognitive radio context by means of a joint and iterative channel and noise estimation technique. Based on the minimum mean square criterion, it performs an accurate detection of a user in a frequency band, by achieving a quasi-optimal channel and noise variance estimation if the signal is present, and by estimating the noise level in the band if the signal is absent. Organized into three chapters, the first chapter provides the background against which the system model is pr
Agatha: Disentangling period signals from correlated noise in a periodogram framework
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/.
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
a Universal De-Noising Algorithm for Ground-Based LIDAR Signal
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.
IIR digital filter design for powerline noise cancellation of ECG signal using arduino platform
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.
Correlated and uncorrelated invisible temporal white noise alters mesopic rod signaling.
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.
Probabilistic Signal Recovery and Random Matrices
2016-12-08
that classical methods for linear regression (such as Lasso) are applicable for non- linear data. This surprising finding has already found several...we studied the complexity of convex sets. In numerical linear algebra , we analyzed the fastest known randomized approximation algorithm for...and perfect matchings In numerical linear algebra , we studied the fastest known randomized approximation algorithm for computing the permanents of
Power Spectrum Estimation of Randomly Sampled Signals
DEFF Research Database (Denmark)
Velte, Clara M.; Buchhave, Preben; K. George, William
2014-01-01
proportional to velocity magnitude that consist of well-defined frequency content, which makes bias easy to spot. The idea is that if the algorithms are not able to produce correct statistics from this simple signal, then they will certainly not be able to function well for a more complex measured LDA signal...
Detecting modulated signals in modulated noise: (II) neural thresholds in the songbird forebrain.
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.
International Nuclear Information System (INIS)
Hayashi, Koji; Shimazaki, Junya; Nabeshima, Kunihiko; Ochiai, Masaaki; Shinohara, Yoshikuni; Inoue, Kimihiko.
1995-01-01
In order to investigate dynamics of the reactor plant of the nuclear ship Mutsu, the second reactor noise experiment using pseudo random binary sequences (PRBS) was performed on August 30, 1991 in the third experimental navigation. The experiments using both reactivity and load disturbances were performed at 50% of reactor power and under a quiet sea condition. Each PRBS was applied by manual operation of the control rod or the main steam valve. Various signals of the plant responses and of the acceleration of ship motion were measured. Furthermore, natural reactor noise signals were measured after each PRBS experiment in order to evaluate the effects of the PRBS disturbances. This paper summarizes the planning of the experiment, the instruction for the experiment and logs, the data recording conditions, recorded signal wave forms and the results of power spectral analysis. (author)
International Nuclear Information System (INIS)
Hayashi, Koji; Shimazaki, Junya; Nabeshima, Kunihiko; Ochiai, Masaaki; Shinohara, Yoshikuni; Inoue, Kimihiko.
1995-03-01
In order to investigate dynamics of the reactor plant of the nuclear ship Mutsu, the third reactor noise experiment using pseudo random binary sequences (PRBS) was performed on September 16, 1991 in the third experimental navigation. The experiments using both reactivity and load disturbances were performed at 70% of reactor power and under a normal sea condition. Each PRBS was applied by manual operation of the control rod or the main steam valve. Various signals of the plant responses and of the acceleration of ship motion were measured. Furthermore, natural reactor noise signals were measured after each PRBS experiment in order to evaluate the effects of the PRBS disturbances. This paper summarizes the planning of the experiment, the instruction for the experiment and logs, the data recording conditions, recorded signal wave forms and the results of power spectral analysis. (author)
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)
Measurement of the Low Frequency Noise of MOSFETs under Large Signal RF Excitation
van der Wel, A.P.; Klumperink, Eric A.M.; Nauta, Bram
2002-01-01
A measurement technique [1] is presented that allows measurement of MOSFET low frequency (LF) noise under large signal RF (Radio Frequency) excitation. Measurements indicate that MOSFETS exhibit a reduction in LF noise when they are cycled from inversion to accummulation and that this reduction does
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.
Random-Resistor-Random-Temperature Kirchhoff-Law-Johnson-Noise (RRRT-KLJN Key Exchange
Directory of Open Access Journals (Sweden)
Kish Laszlo B.
2016-03-01
Full Text Available We introduce two new Kirchhoff-law-Johnson-noise (KLJN secure key distribution schemes which are generalizations of the original KLJN scheme. The first of these, the Random-Resistor (RR- KLJN scheme, uses random resistors with values chosen from a quasi-continuum set. It is well-known since the creation of the KLJN concept that such a system could work in cryptography, because Alice and Bob can calculate the unknown resistance value from measurements, but the RR-KLJN system has not been addressed in prior publications since it was considered impractical. The reason for discussing it now is the second scheme, the Random Resistor Random Temperature (RRRT- KLJN key exchange, inspired by a recent paper of Vadai, Mingesz and Gingl, wherein security was shown to be maintained at non-zero power flow. In the RRRT-KLJN secure key exchange scheme, both the resistances and their temperatures are continuum random variables. We prove that the security of the RRRT-KLJN scheme can prevail at a non-zero power flow, and thus the physical law guaranteeing security is not the Second Law of Thermodynamics but the Fluctuation-Dissipation Theorem. Alice and Bob know their own resistances and temperatures and can calculate the resistance and temperature values at the other end of the communication channel from measured voltage, current and power-flow data in the wire. However, Eve cannot determine these values because, for her, there are four unknown quantities while she can set up only three equations. The RRRT-KLJN scheme has several advantages and makes all former attacks on the KLJN scheme invalid or incomplete.
Directory of Open Access Journals (Sweden)
I. I. Zabenkov
2012-01-01
Full Text Available Continuous measurement function of relative noise and interference level in the information transmission channel is considered as an important one for controlling parameters of high-frequency signal. The present paper simulates an algorithm for measuring signal-noise ratio in the transmission channel of high-voltage lines which is used in the digital equipment for transmission of relay protection and emergency automation commands of "Strela" complex.
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.
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
The dependence of signal-to-noise ratio on number of scans in covariance spectroscopy.
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.
Discrete random signal processing and filtering primer with Matlab
Poularikas, Alexander D
2013-01-01
Engineers in all fields will appreciate a practical guide that combines several new effective MATLAB® problem-solving approaches and the very latest in discrete random signal processing and filtering.Numerous Useful Examples, Problems, and Solutions - An Extensive and Powerful ReviewWritten for practicing engineers seeking to strengthen their practical grasp of random signal processing, Discrete Random Signal Processing and Filtering Primer with MATLAB provides the opportunity to doubly enhance their skills. The author, a leading expert in the field of electrical and computer engineering, offe
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
Kleist, Nathan J; Guralnick, Robert P; Cruz, Alexander; Lowry, Christopher A; Francis, Clinton D
2018-01-23
Anthropogenic noise is a pervasive pollutant that decreases environmental quality by disrupting a suite of behaviors vital to perception and communication. However, even within populations of noise-sensitive species, individuals still select breeding sites located within areas exposed to high noise levels, with largely unknown physiological and fitness consequences. We use a study system in the natural gas fields of northern New Mexico to test the prediction that exposure to noise causes glucocorticoid-signaling dysfunction and decreases fitness in a community of secondary cavity-nesting birds. In accordance with these predictions, and across all species, we find strong support for noise exposure decreasing baseline corticosterone in adults and nestlings and, conversely, increasing acute stressor-induced corticosterone in nestlings. We also document fitness consequences with increased noise in the form of reduced hatching success in the western bluebird ( Sialia mexicana ), the species most likely to nest in noisiest environments. Nestlings of all three species exhibited accelerated growth of both feathers and body size at intermediate noise amplitudes compared with lower or higher amplitudes. Our results are consistent with recent experimental laboratory studies and show that noise functions as a chronic, inescapable stressor. Anthropogenic noise likely impairs environmental risk perception by species relying on acoustic cues and ultimately leads to impacts on fitness. Our work, when taken together with recent efforts to document noise across the landscape, implies potential widespread, noise-induced chronic stress coupled with reduced fitness for many species reliant on acoustic cues.
Electromagnetic Signals and Earthquakes 2.0: Increasing Signals and Reducing Noise
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.
Characterization of Transient Noise in Advanced LIGO Relevant to Gravitational Wave Signal GW150914
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.
Broadband squeezing of quantum noise in a Michelson interferometer with Twin-Signal-Recycling.
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.
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
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.
Analogies between colored Lévy noise and random channel approach to disordered kinetics
Vlad, Marcel O.; Velarde, Manuel G.; Ross, John
2004-02-01
We point out some interesting analogies between colored Lévy noise and the random channel approach to disordered kinetics. These analogies are due to the fact that the probability density of the Lévy noise source plays a similar role as the probability density of rate coefficients in disordered kinetics. Although the equations for the two approaches are not identical, the analogies can be used for deriving new, useful results for both problems. The random channel approach makes it possible to generalize the fractional Uhlenbeck-Ornstein processes (FUO) for space- and time-dependent colored noise. We describe the properties of colored noise in terms of characteristic functionals, which are evaluated by using a generalization of Huber's approach to complex relaxation [Phys. Rev. B 31, 6070 (1985)]. We start out by investigating the properties of symmetrical white noise and then define the Lévy colored noise in terms of a Langevin equation with a Lévy white noise source. We derive exact analytical expressions for the various characteristic functionals, which characterize the noise, and a functional fractional Fokker-Planck equation for the probability density functional of the noise at a given moment in time. Second, by making an analogy between the theory of colored noise and the random channel approach to disordered kinetics, we derive fractional equations for the evolution of the probability densities of the random rate coefficients in disordered kinetics. These equations serve as a basis for developing methods for the evaluation of the statistical properties of the random rate coefficients from experimental data. Special attention is paid to the analysis of systems for which the observed kinetic curves can be described by linear or nonlinear stretched exponential kinetics.
Acoustics of fish shelters: background noise and signal-to-noise ratio.
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.
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)
Affectively salient meaning in random noise: a task sensitive to psychosis liability.
Galdos, Mariana; Simons, Claudia; Fernandez-Rivas, Aranzazu; Wichers, Marieke; Peralta, Concepción; Lataster, Tineke; Amer, Guillermo; Myin-Germeys, Inez; Allardyce, Judith; Gonzalez-Torres, Miguel Angel; van Os, Jim
2011-11-01
Stable differences in the tendency to attribute meaning and emotional value to experience may represent an indicator of liability to psychosis. A brief task was developed assessing variation in detecting affectively meaningful speech (speech illusion) in neutral random signals (white noise) and the degree to which this was associated with psychometric and familial vulnerability for psychosis. Thirty patients, 28 of their siblings, and 307 controls participated. The rate of speech illusion was compared between cases and controls. In controls, the association between speech illusion and interview-based positive schizotypy was assessed. The hypothesis of a dose-response increase in rate of speech illusion across increasing levels of familial vulnerability for psychosis (controls, siblings of patients, and patients) was examined. Patients were more likely to display speech illusions than controls (odds ratio [OR] = 4.0, 95% confidence interval [CI] = 1.4-11.7), also after controlling for neurocognitive variables (OR = 3.8, 95% CI = 1.04-14.1). The case-control difference was more accentuated for speech illusion perceived as affectively salient (positively or negatively appraised) than for neutrally appraised speech illusions. Speech illusion in the controls was strongly associated with positive schizotypy but not with negative schizotypy. In addition, the rate of speech illusion increased with increasing level of familial risk for psychotic disorder. The data suggest that the white noise task may be sensitive to psychometric and familial vulnerability for psychosis associated with alterations in top-down processing and/or salience attribution.
Random noise can help to improve synchronization of excimer laser pulses.
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.
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.
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.
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.
Power Spectrum Estimation of Randomly Sampled Signals
DEFF Research Database (Denmark)
Velte, C. M.; Buchhave, P.; K. George, W.
algorithms; sample and-hold and the direct spectral estimator without residence time weighting. The computer generated signal is a Poisson process with a sample rate proportional to velocity magnitude that consist of well-defined frequency content, which makes bias easy to spot. The idea...
Detection and Localization of Random Signals
DEFF Research Database (Denmark)
Sporring, Jon; Olsen, Niels Holm; Nielsen, Mads
2003-01-01
filtering techniques. It is therefore interesting to extend the application to objects with many but small degrees of freedom in their geometry. These geometric variations deteriorate the linear correlation signal, both regarding its strength and localization with multiple peaks from a single object...
Facial soft tissue thicknesses: Noise, signal, and P.
Stephan, Carl N; Munn, Lachlan; Caple, Jodi
2015-12-01
Facial soft tissue thicknesses (FSTTs) hold an important role in craniofacial identification, forming the underlying quantitative basis of craniofacial superimposition and facial approximation methods. It is, therefore, important that patterns in FSTTs be correctly described and interpreted. In prior FSTT literature, small statistically significant differences have almost universally been overemphasized and misinterpreted to reflect sex and ancestry effects when they instead largely encode nuisance statistical noise. Here we examine FSTT data and give an overview of why P-values do not mean everything. Scientific inference, not mechanical evaluation of P, should be awarded higher priority and should form the basis of FSTT analysis. This hinges upon tempered consideration of many factors in addition to P, e.g., study design, sampling, measurement errors, repeatability, reproducibility, and effect size. While there are multiple lessons to be had, the underlying message is foundational: know enough statistics to avoid misinterpreting background noise for real biological effects. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Probability, random variables, and random processes theory and signal processing applications
Shynk, John J
2012-01-01
Probability, Random Variables, and Random Processes is a comprehensive textbook on probability theory for engineers that provides a more rigorous mathematical framework than is usually encountered in undergraduate courses. It is intended for first-year graduate students who have some familiarity with probability and random variables, though not necessarily of random processes and systems that operate on random signals. It is also appropriate for advanced undergraduate students who have a strong mathematical background. The book has the following features: Several app
Nonlinear Estimation of Discrete-Time Signals Under Random Observation Delay
International Nuclear Information System (INIS)
Caballero-Aguila, R.; Jimenez-Lopez, J. D.; Hermoso-Carazo, A.; Linares-Perez, J.; Nakamori, S.
2008-01-01
This paper presents an approximation to the nonlinear least-squares estimation problem of discrete-time stochastic signals using nonlinear observations with additive white noise which can be randomly delayed by one sampling time. The observation delay is modelled by a sequence of independent Bernoulli random variables whose values, zero or one, indicate that the real observation arrives on time or it is delayed and, hence, the available measurement to estimate the signal is not up-to-date. Assuming that the state-space model generating the signal is unknown and only the covariance functions of the processes involved in the observation equation are ready for use, a filtering algorithm based on linear approximations of the real observations is proposed.
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.
Subspace-Based Noise Reduction for Speech Signals via Diagonal and Triangular Matrix Decompositions
DEFF Research Database (Denmark)
Hansen, Per Christian; Jensen, Søren Holdt
2007-01-01
We survey the definitions and use of rank-revealing matrix decompositions in single-channel noise reduction algorithms for speech signals. Our algorithms are based on the rank-reduction paradigm and, in particular, signal subspace techniques. The focus is on practical working algorithms, using both...... with working Matlab code and applications in speech processing....
BER analysis for MPAM signal constellations in the presence of fading and ADC quantization noise
Rizvi, U.H.; Janssen, G.J.M.; Weber, J.H.
2009-01-01
In this letter, closed-form expressions for the bit error rate of M-ary pulse amplitude modulated signal constellations as a function of the analog-to-digital converter word length, the signal-to-noise ratio and the fading distribution, are derived. These results allow for a rapid and accurate
Noise and signal processing in a microstrip detector with a time variant readout system
International Nuclear Information System (INIS)
Cattaneo, P.W.
1995-01-01
This paper treats the noise and signal processing by a time variant filter in a microstrip detector. In particular, the noise sources in the detector-electronics chain and the signal losses that cause a substantial decrease of the original signal are thoroughly analyzed. This work has been motivated by the analysis of the data of the microstrip detectors designed for the ALEPH minivertex detector. Hence, even if the discussion will be kept as general as possible, concrete examples will be presented referring to the specific ALEPH design. (orig.)
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.
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.
International Nuclear Information System (INIS)
Xie Shaofei; Xiang Bingren; Deng Haishan; Xiang Suyun; Lu Jun
2007-01-01
Based on the theory of stochastic resonance, an improved stochastic resonance algorithm with a new criterion for optimizing system parameters to enhance signal-to-noise ratio (SNR) of HPLC/UV chromatographic signal for trace analysis was presented in this study. Compared with the conventional criterion in stochastic resonance, the proposed one can ensure satisfactory SNR as well as good peak shape of chromatographic peak in output signal. Application of the criterion to experimental weak signals of HPLC/UV was investigated and the results showed an excellent quantitative relationship between different concentrations and responses
International Nuclear Information System (INIS)
Ledwidge, T.J.; Black, J.L.
1989-01-01
The present paper deals with investigations of acoustic signals from a boiling experiment performed on the BOR 60 reactor in the USSR. Signals have been analysed in frequency as well as in time domain. Signal characteristics successfully used to detect the boiling process have been found in time domain. A proposal for in-service boiling monitoring by acoustic means is described. (author). 3 refs, 16 figs
Full-Scale Turbofan Engine Noise-Source Separation Using a Four-Signal Method
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.
Random Deep Belief Networks for Recognizing Emotions from Speech Signals.
Wen, Guihua; Li, Huihui; Huang, Jubing; Li, Danyang; Xun, Eryang
2017-01-01
Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN) can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN) method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition.
International Nuclear Information System (INIS)
Doherty, W.
2013-01-01
A nebulizer-centric response function model of the analytical inductively coupled argon plasma ion source was used to investigate the statistical frequency distributions and noise reduction factors of simultaneously measured flicker noise limited isotope ion signals and their ratios. The response function model was extended by assuming i) a single gaussian distributed random noise source (nebulizer gas pressure fluctuations) and ii) the isotope ion signal response is a parabolic function of the nebulizer gas pressure. Model calculations of ion signal and signal ratio histograms were obtained by applying the statistical method of translation to the non-linear response function model of the plasma. Histograms of Ni, Cu, Pr, Tl and Pb isotope ion signals measured using a multi-collector plasma mass spectrometer were, without exception, negative skew. Histograms of the corresponding isotope ratios of Ni, Cu, Tl and Pb were either positive or negative skew. There was a complete agreement between the measured and model calculated histogram skew properties. The nebulizer-centric response function model was also used to investigate the effect of non-linear response functions on the effectiveness of noise cancellation by signal division. An alternative noise correction procedure suitable for parabolic signal response functions was derived and applied to measurements of isotope ratios of Cu, Ni, Pb and Tl. The largest noise reduction factors were always obtained when the non-linearity of the response functions was taken into account by the isotope ratio calculation. Possible applications of the nebulizer-centric response function model to other types of analytical instrumentation, large amplitude signal noise sources (e.g., lasers, pumped nebulizers) and analytical error in isotope ratio measurements by multi-collector plasma mass spectrometry are discussed. - Highlights: ► Isotope ion signal noise is modelled as a parabolic transform of a gaussian variable. ► Flicker
Effects of traffic noise on tree frog stress levels, immunity, and color signaling.
Troïanowski, Mathieu; Mondy, Nathalie; Dumet, Adeline; Arcanjo, Caroline; Lengagne, Thierry
2017-10-01
During the last decade, many studies have focused on the detrimental effects of noise pollution on acoustic communication. Surprisingly, although it is known that noise exposure strongly influences health in humans, studies on wildlife remain scarce. In order to gain insight into the consequences of traffic noise exposure, we experimentally manipulated traffic noise exposure as well as the endocrine status of animals to investigate physiological and phenotypic consequences of noise pollution in an anuran species. We showed that noise exposure increased stress hormone level and induced an immunosuppressive effect. In addition, both traffic noise exposure and stress hormone application negatively impacted H. arborea vocal sac coloration. Moreover, our results suggest profound changes in sexual selection processes because the best quality males with initial attractive vocal sac coloration were the most impacted by noise. Hence, our study suggests that the recent increases in anthropogenic noise worldwide might affect a broader range of animal species than previously thought, because of alteration of visual signals and immunity. Generalizing these results to other taxa is crucial for the conservation of biodiversity in an increasingly noisy world. © 2017 Society for Conservation Biology.
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.
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
International Nuclear Information System (INIS)
Cummins, J.D.
1964-02-01
The sources of error in the measurement of system impulse response using test signals of a discrete interval binary nature are considered. Methods of correcting for the errors due to theoretical imperfections are given and the variance of the estimate of the system impulse response due to random noise is determined. Several topics related to the main topic are considered e.g. determination of a theoretical model from experimental results. General conclusions about the magnitude of the errors due to the theoretical imperfections are made. (author)
Energy Technology Data Exchange (ETDEWEB)
Cummins, J D [Dynamics Group, Control and Instrumentation Division, Atomic Energy Establishment, Winfrith, Dorchester, Dorset (United Kingdom)
1964-02-15
The sources of error in the measurement of system impulse response using test signals of a discrete interval binary nature are considered. Methods of correcting for the errors due to theoretical imperfections are given and the variance of the estimate of the system impulse response due to random noise is determined. Several topics related to the main topic are considered e.g. determination of a theoretical model from experimental results. General conclusions about the magnitude of the errors due to the theoretical imperfections are made. (author)
Application of empirical mode decomposition method for characterization of random vibration signals
Directory of Open Access Journals (Sweden)
Setyamartana Parman
2016-07-01
Full Text Available Characterization of finite measured signals is a great of importance in dynamical modeling and system identification. This paper addresses an approach for characterization of measured random vibration signals where the approach rests on a method called empirical mode decomposition (EMD. The applicability of proposed approach is tested in one numerical and experimental data from a structural system, namely spar platform. The results are three main signal components, comprising: noise embedded in the measured signal as the first component, first intrinsic mode function (IMF called as the wave frequency response (WFR as the second component and second IMF called as the low frequency response (LFR as the third component while the residue is the trend. Band-pass filter (BPF method is taken as benchmark for the results obtained from EMD method.
Fast random-number generation using a diode laser's frequency noise characteristic
Takamori, Hiroki; Doi, Kohei; Maehara, Shinya; Kawakami, Kohei; Sato, Takashi; Ohkawa, Masashi; Ohdaira, Yasuo
2012-02-01
Random numbers can be classified as either pseudo- or physical-random, in character. Pseudo-random numbers are generated by definite periodicity, so, their usefulness in cryptographic applications is somewhat limited. On the other hand, naturally-generated physical-random numbers have no calculable periodicity, thereby making them ideal for the task. Diode lasers' considerable wideband noise gives them tremendous capacity for generating physical-random numbers, at a high rate of speed. We measured a diode laser's output with a fast photo detector, and evaluated the binary-numbers from the diode laser's frequency noise characteristics. We then identified and evaluated the binary-number-line's statistical properties. We also investigate the possibility that much faster physical-random number parallel-generation is possible, using separate outputs of different optical-path length and character, which we refer to as "coherence collapse".
Experimental Comparison of Signal Subspace Based Noise Reduction Methods
DEFF Research Database (Denmark)
Hansen, Peter Søren Kirk; Hansen, Per Christian; Hansen, Steffen Duus
1999-01-01
The signal subspace approach for non-parametric speech enhancement is considered. Several algorithms have been proposed in the literature but only partly analyzed. Here, the different algorithms are compared, and the emphasis is put onto the limiting factors and practical behavior of the estimators...
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.)
Experience with a PC-based system for noise and DC signal analysis in PWRs
International Nuclear Information System (INIS)
Hashemian, H.M.
1996-01-01
A data acquisition system that was originally developed for noise diagnostics in PWRs was expanded to include DC signal analysis in addition to noise analysis. The system has been used in PWRs for reactor diagnostics, determination of root cause of process anomalies, instrument calibration verification, measurement of drop time of control and shutdown rods, testing of timing and sequencing of control rod drive mechanisms, emergency diesel generator monitoring, etc. These applications are reviewed in this paper. (author)
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.
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...
Speech Denoising in White Noise Based on Signal Subspace Low-rank Plus Sparse Decomposition
Directory of Open Access Journals (Sweden)
yuan Shuai
2017-01-01
Full Text Available In this paper, a new subspace speech enhancement method using low-rank and sparse decomposition is presented. In the proposed method, we firstly structure the corrupted data as a Toeplitz matrix and estimate its effective rank for the underlying human speech signal. Then the low-rank and sparse decomposition is performed with the guidance of speech rank value to remove the noise. Extensive experiments have been carried out in white Gaussian noise condition, and experimental results show the proposed method performs better than conventional speech enhancement methods, in terms of yielding less residual noise and lower speech distortion.
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.
Gao, Feng-Yin; Kang, Yan-Mei; Chen, Xi; Chen, Guanrong
2018-05-01
This paper reveals the effect of fractional Gaussian noise with Hurst exponent H ∈(1 /2 ,1 ) on the information capacity of a general nonlinear neuron model with binary signal input. The fGn and its corresponding fractional Brownian motion exhibit long-range, strong-dependent increments. It extends standard Brownian motion to many types of fractional processes found in nature, such as the synaptic noise. In the paper, for the subthreshold binary signal, sufficient conditions are given based on the "forbidden interval" theorem to guarantee the occurrence of stochastic resonance, while for the suprathreshold binary signal, the simulated results show that additive fGn with Hurst exponent H ∈(1 /2 ,1 ) could increase the mutual information or bits count. The investigation indicated that the synaptic noise with the characters of long-range dependence and self-similarity might be the driving factor for the efficient encoding and decoding of the nervous system.
Huang, Lei
2015-01-01
To solve the problem in which the conventional ARMA modeling methods for gyro random noise require a large number of samples and converge slowly, an ARMA modeling method using a robust Kalman filtering is developed. The ARMA model parameters are employed as state arguments. Unknown time-varying estimators of observation noise are used to achieve the estimated mean and variance of the observation noise. Using the robust Kalman filtering, the ARMA model parameters are estimated accurately. The developed ARMA modeling method has the advantages of a rapid convergence and high accuracy. Thus, the required sample size is reduced. It can be applied to modeling applications for gyro random noise in which a fast and accurate ARMA modeling method is required. PMID:26437409
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.
A Denoising Scheme for Randomly Clustered Noise Removal in ICCD Sensing Image
Directory of Open Access Journals (Sweden)
Fei Wang
2017-01-01
Full Text Available An Intensified Charge-Coupled Device (ICCD image is captured by the ICCD image sensor in extremely low-light conditions. Its noise has two distinctive characteristics. (a Different from the independent identically distributed (i.i.d. noise in natural image, the noise in the ICCD sensing image is spatially clustered, which induces unexpected structure information; (b The pattern of the clustered noise is formed randomly. In this paper, we propose a denoising scheme to remove the randomly clustered noise in the ICCD sensing image. First, we decompose the image into non-overlapped patches and classify them into flat patches and structure patches according to if real structure information is included. Then, two denoising algorithms are designed for them, respectively. For each flat patch, we simulate multiple similar patches for it in pseudo-time domain and remove its noise by averaging all the simulated patches, considering that the structure information induced by the noise varies randomly over time. For each structure patch, we design a structure-preserved sparse coding algorithm to reconstruct the real structure information. It reconstructs each patch by describing it as a weighted summation of its neighboring patches and incorporating the weights into the sparse representation of the current patch. Based on all the reconstructed patches, we generate a reconstructed image. After that, we repeat the whole process by changing relevant parameters, considering that blocking artifacts exist in a single reconstructed image. Finally, we obtain the reconstructed image by merging all the generated images into one. Experiments are conducted on an ICCD sensing image dataset, which verifies its subjective performance in removing the randomly clustered noise and preserving the real structure information in the ICCD sensing image.
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
Multichannel active control of random noise in a small reverberant room
DEFF Research Database (Denmark)
Laugesen, Søren; Elliott, Stephen J.
1993-01-01
An algorithm for multichannel adaptive IIR (infinite impulse response) filtering is presented and applied to the active control of broadband random noise in a small reverberant room. Assuming complete knowledge of the primary noise, the theoretically optimal reductions of acoustic energy are init...... with the primary noise field generated by a panel excited by a loudspeaker in an adjoining room. These results show that far better performances are provided by IIR and FIR filters when the primary source has a lightly damped dynamic behavior which the active controller must model...
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.
Noise is all around you, from televisions and radios to lawn mowers and washing machines. Normally, you ... sensitive structures of the inner ear and cause noise-induced hearing loss. More than 30 million Americans ...
No-signaling, perfect bipartite dichotomic correlations and local randomness
International Nuclear Information System (INIS)
Seevinck, M. P.
2011-01-01
The no-signaling constraint on bi-partite correlations is reviewed. It is shown that in order to obtain non-trivial Bell-type inequalities that discern no-signaling correlations from more general ones, one must go beyond considering expectation values of products of observables only. A new set of nontrivial no-signaling inequalities is derived which have a remarkably close resemblance to the CHSH inequality, yet are fundamentally different. A set of inequalities by Roy and Singh and Avis et al., which is claimed to be useful for discerning no-signaling correlations, is shown to be trivially satisfied by any correlation whatsoever. Finally, using the set of newly derived no-signaling inequalities a result with potential cryptographic consequences is proven: if different parties use identical devices, then, once they have perfect correlations at spacelike separation between dichotomic observables, they know that because of no-signaling the local marginals cannot but be completely random.
Signal-noise separation based on self-similarity testing in 1D-timeseries data
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.
Evaluation of signal processing for boiling noise detection
International Nuclear Information System (INIS)
Black, J.L.; Ledwidge, T.J.
1989-01-01
As part of the co-ordinated research programme on the detection of sodium boiling some further analysis has been performed on the data from the test loop in Karlsruhe and some preliminary analysis of the data from the BOR 60 experiment. The work on the Karlsruhe data is concerned with the search for a reliable method by which the quality of signal processing strategies may be compared. The results show that the three novel methods previously reported are all markedly superior to the mean square method which is used as a benchmark. The three novel methods are nth order differentiation in the frequency domain, the mean square prediction based on nth order conditional expectation and the nth order probability density function. A preliminary analysis on the data from the BOR 60 reactor shows that 4th order differentiation is adequate for the detection of signals derived from a pressure transducer and that the map of spurious trip probability (S) and the probability of missing an event (M) is consistent with the theoretical model proposed herein, and the suggested procedures for evaluating the quality of detection strategies. (author). 15 figs, 1 tab
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.
A method for discrimination of noise and EMG signal regions recorded during rhythmic behaviors.
Ying, Rex; Wall, Christine E
2016-12-08
Analyses of muscular activity during rhythmic behaviors provide critical data for biomechanical studies. Electrical potentials measured from muscles using electromyography (EMG) require discrimination of noise regions as the first step in analysis. An experienced analyst can accurately identify the onset and offset of EMG but this process takes hours to analyze a short (10-15s) record of rhythmic EMG bursts. Existing computational techniques reduce this time but have limitations. These include a universal threshold for delimiting noise regions (i.e., a single signal value for identifying the EMG signal onset and offset), pre-processing using wide time intervals that dampen sensitivity for EMG signal characteristics, poor performance when a low frequency component (e.g., DC offset) is present, and high computational complexity leading to lack of time efficiency. We present a new statistical method and MATLAB script (EMG-Extractor) that includes an adaptive algorithm to discriminate noise regions from EMG that avoids these limitations and allows for multi-channel datasets to be processed. We evaluate the EMG-Extractor with EMG data on mammalian jaw-adductor muscles during mastication, a rhythmic behavior typified by low amplitude onsets/offsets and complex signal pattern. The EMG-Extractor consistently and accurately distinguishes noise from EMG in a manner similar to that of an experienced analyst. It outputs the raw EMG signal region in a form ready for further analysis. Copyright © 2016 Elsevier Ltd. All rights reserved.
Early detection of structual changes in random signal
International Nuclear Information System (INIS)
Kuroda, Yoshiteru; Yokota, Katsuhiro
1981-01-01
Early detection of structual changes in observed random signal is very important from the point of system diagnosis. In this paper, the following procedures are applied to this problem and the results are compared. (1) auto-regressive model to random signal to calculate the prediction error, i.e., the defference between observed and predicted values. (2) auto-regressive method to caluculate the sum of the prediction error. (3) a method is based on AIC (Akaike Information Criterion). Simulation is made of these procedures, indicating their merits and demerits as a diagostic tools. (author)
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.
Computer evaluation of random signals from vibration acoustic diagnostics
International Nuclear Information System (INIS)
Bahna, J.
1979-01-01
Definitions and relations are shown for the calculation of the characteristics of random signals used, such as the amplitude probability density, correlation functions and power spectral densities. The methods are described of digitizing a continuous signal for calculating the above characteristics. The algorithm of the fast Fourier transformation was used in the calculation. The design is described of a system whose essential part is an analog-to-digital converter. The system software is also described. (J.B.)
Suppression of thermal noise in a non-Markovian random velocity field
International Nuclear Information System (INIS)
Ueda, Masahiko
2016-01-01
We study the diffusion of Brownian particles in a Gaussian random velocity field with short memory. By extending the derivation of an effective Fokker–Planck equation for the Lanvegin equation with weakly colored noise to a random velocity-field problem, we find that the effect of thermal noise on particles is suppressed by the existence of memory. We also find that the renormalization effect for the relative diffusion of two particles is stronger than that for single-particle diffusion. The results are compared with those of molecular dynamics simulations. (paper: classical statistical mechanics, equilibrium and non-equilibrium)
Real Time Phase Noise Meter Based on a Digital Signal Processor
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.
International Nuclear Information System (INIS)
Phelps, M.E.; Huang, S.C.; Hoffman, E.J.; Plummer, D.; Carson, R.
1981-01-01
Spatial resolution improvements in computed tomography (CT) have been limited by the large and unique error propagation properties of this technique. The desire to provide maximum image resolution has resulted in the use of reconstruction filter functions designed to produce tomographic images with resolution as close as possible to the intrinsic detector resolution. Thus, many CT systems produce images with excessive noise with the system resolution determined by the detector resolution rather than the reconstruction algorithm. CT is a rigorous mathematical technique which applies an increasing amplification to increasing spatial frequencies in the measured data. This mathematical approach to spatial frequency amplification cannot distinguish between signal and noise and therefore both are amplified equally. We report here a method in which tomographic resolution is improved by using very small detectors to selectively amplify the signal and not noise. Thus, this approach is referred to as the signal amplification technique (SAT). SAT can provide dramatic improvements in image resolution without increases in statistical noise or dose because increases in the cutoff frequency of the reconstruction algorithm are not required to improve image resolution. Alternatively, in cases where image counts are low, such as in rapid dynamic or receptor studies, statistical noise can be reduced by lowering the cutoff frequency while still maintaining the best possible image resolution. A possible system design for a positron CT system with SAT is described
Noise estimation for remote sensing image data analysis
Du, Qian
2004-01-01
Noise estimation does not receive much attention in remote sensing society. It may be because normally noise is not large enough to impair image analysis result. Noise estimation is also very challenging due to the randomness nature of the noise (for random noise) and the difficulty of separating the noise component from the signal in each specific location. We review and propose seven different types of methods to estimate noise variance and noise covariance matrix in a remotely sensed image. In the experiment, it is demonstrated that a good noise estimate can improve the performance of an algorithm via noise whitening if this algorithm assumes white noise.
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.
Signal Processing for MoC brake rattle noise of moving vehicles using prony analysis
Energy Technology Data Exchange (ETDEWEB)
Lee, Jae Cheol; Kwak, Yun Sang; Park, Jun Hong [Dept. of Mechanical Convergence Engineering, Hanyang University, Seoul (Korea, Republic of)
2015-08-15
To verify the possibility of generating rattling noise from a motor on caliper brake system, a test was conducted using a caliper excited with vibrations similar to that in a vehicle running on actual roads; this test was conducted using a quiet shaker installed in an anechoic room. After several hours of external excitation, the test assembly was loosened, and the frequency of rattling noise generation increased. A microphone was used to record the generated noise. The measured signals were analyzed by conventional spectrum analysis. Since the noise is generated as an impact response, the advantages of employing Prony analysis was discussed, and the results were compared to those obtained using conventional fast Fourier transforms. The accuracy of Prony analysis was through endurance tests on different brake systems.
Energy Technology Data Exchange (ETDEWEB)
Hoogenboom, J.E.; van Dam, H.; Kleiss, E.B.J.; van Uitert, G.C.; Veldhuis, D.
1982-01-01
The measured cross power spectral densities of the signals from three neutron detectors and the displacement of the control rod of the 2 MW research reactor HOR at Delft have been used to determine the space-dependent reactor transfer function, the transfer function of the automatic reactor control system and the noise sources influencing the measured signals. From a block diagram of the reactor with control system and noise sources expressions were derived for the measured cross power spectral densities, which were adjusted to satisfy the requirements following from the adopted model. Then for each frequency point the required transfer functions and noise sources could be derived. The results are in agreement with those of autoregressive modelling of the reactor control feed-back loop. A method has been developed to determine the non-linear characteristics of the automatic reactor control system by analysing the non-gaussian probability density function of the power fluctuations.
International Nuclear Information System (INIS)
Hoogenboom, J.E.
1982-01-01
The measured cross power spectral densities of the signals from three neutron detectors and the displacement of the control rod of the 2 MW research reactor HOR at Delft have been used to determine the space-dependent reactor transfer function, the transfer function of the automatic reactor control system and the noise sources influencing the measured signals. From a block diagram of the reactor with control system and noise sources expressions were derived for the measured cross power spectral densities, which were adjusted to satisfy the requirements following from the adopted model. Then for each frequency point the required transfer functions and noise sources could be derived. The results are in agreement with those of autoregressive modelling of the reactor control feed-back loop. A method has been developed to determine the non-linear characteristics of the automatic reactor control system by analysing the non-gaussian probability density function of the power fluctuations. (author)
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.
Bruns, S.; Stipp, S. L. S.; Sørensen, H. O.
2017-07-01
X-ray micro- and nanotomography has evolved into a quantitative analysis tool rather than a mere qualitative visualization technique for the study of porous natural materials. Tomographic reconstructions are subject to noise that has to be handled by image filters prior to quantitative analysis. Typically, denoising filters are designed to handle random noise, such as Gaussian or Poisson noise. In tomographic reconstructions, noise has been projected from Radon space to Euclidean space, i.e. post reconstruction noise cannot be expected to be random but to be correlated. Reconstruction artefacts, such as streak or ring artefacts, aggravate the filtering process so algorithms performing well with random noise are not guaranteed to provide satisfactory results for X-ray tomography reconstructions. With sufficient image resolution, the crystalline origin of most geomaterials results in tomography images of objects that are untextured. We developed a denoising framework for these kinds of samples that combines a noise level estimate with iterative nonlocal means denoising. This allows splitting the denoising task into several weak denoising subtasks where the later filtering steps provide a controlled level of texture removal. We describe a hands-on explanation for the use of this iterative denoising approach and the validity and quality of the image enhancement filter was evaluated in a benchmarking experiment with noise footprints of a varying level of correlation and residual artefacts. They were extracted from real tomography reconstructions. We found that our denoising solutions were superior to other denoising algorithms, over a broad range of contrast-to-noise ratios on artificial piecewise constant signals.
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
Signal-to-noise ratio analysis and evaluation of the Hadamard imaging technique
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.
Using hyperentanglement to enhance resolution, signal-to-noise ratio, and measurement time
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.
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 ...
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...
Characterization of transient noise in Advanced LIGO relevant to gravitational wave signal GW150914
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
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Siva Kotipalli
2014-01-01
(SCA resistance. These designs are based on a delay-insensitive (DI logic paradigm known as null convention logic (NCL, which supports useful properties for resisting SCAs including dual-rail encoding, clock-free operation, and monotonic transitions. Potential benefits include reduced and more uniform switching activities and reduced signal-to-noise (SNR ratio. A novel method to further augment NCL AES hardware with random voltage scaling technique is also presented for additional security. Thereby, the proposed components leak significantly less side-channel information than conventional clocked approaches. To quantitatively verify such improvements, functional verification and WASSO (weighted average simultaneous switching output analysis have been carried out on both conventional synchronous approach and the proposed NCL based approach using Mentor Graphics ModelSim and Xilinx simulation tools. Hardware implementation has been carried out on both designs exploiting a specified side-channel attack standard evaluation FPGA board, called SASEBO-GII, and the corresponding power waveforms for both designs have been collected. Along with the results of software simulations, we have analyzed the collected waveforms to validate the claims related to benefits of the proposed cryptohardware design approach.
An Application of Reassigned Time-Frequency Representations for Seismic Noise/Signal Decomposition
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
Benchmarking the Algorithms to Detect Seasonal Signals Under Different Noise Conditions
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.
Approximations to camera sensor noise
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.
Random attractors for stochastic lattice reversible Gray-Scott systems with additive noise
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Hongyan Li
2015-10-01
Full Text Available In this article, we prove the existence of a random attractor of the stochastic three-component reversible Gray-Scott system on infinite lattice with additive noise. We use a transformation of addition involved with Ornstein-Uhlenbeck process, for proving the pullback absorbing property and the pullback asymptotic compactness of the reaction diffusion system with cubic nonlinearity.
Robustness of digitally modulated signal features against variation in HF noise model
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Shoaib Mobien
2011-01-01
Full Text Available Abstract High frequency (HF band has both military and civilian uses. It can be used either as a primary or backup communication link. Automatic modulation classification (AMC is of an utmost importance in this band for the purpose of communications monitoring; e.g., signal intelligence and spectrum management. A widely used method for AMC is based on pattern recognition (PR. Such a method has two main steps: feature extraction and classification. The first step is generally performed in the presence of channel noise. Recent studies show that HF noise could be modeled by Gaussian or bi-kappa distributions, depending on day-time. Therefore, it is anticipated that change in noise model will have impact on features extraction stage. In this article, we investigate the robustness of well known digitally modulated signal features against variation in HF noise. Specifically, we consider temporal time domain (TTD features, higher order cumulants (HOC, and wavelet based features. In addition, we propose new features extracted from the constellation diagram and evaluate their robustness against the change in noise model. This study is targeting 2PSK, 4PSK, 8PSK, 16QAM, 32QAM, and 64QAM modulations, as they are commonly used in HF communications.
Samoilov, Michael; Plyasunov, Sergey; Arkin, Adam P.
2005-02-01
Stochastic effects in biomolecular systems have now been recognized as a major physiologically and evolutionarily important factor in the development and function of many living organisms. Nevertheless, they are often thought of as providing only moderate refinements to the behaviors otherwise predicted by the classical deterministic system description. In this work we show by using both analytical and numerical investigation that at least in one ubiquitous class of (bio)chemical-reaction mechanisms, enzymatic futile cycles, the external noise may induce a bistable oscillatory (dynamic switching) behavior that is both quantitatively and qualitatively different from what is predicted or possible deterministically. We further demonstrate that the noise required to produce these distinct properties can itself be caused by a set of auxiliary chemical reactions, making it feasible for biological systems of sufficient complexity to generate such behavior internally. This new stochastic dynamics then serves to confer additional functional modalities on the enzymatic futile cycle mechanism that include stochastic amplification and signaling, the characteristics of which could be controlled by both the type and parameters of the driving noise. Hence, such noise-induced phenomena may, among other roles, potentially offer a novel type of control mechanism in pathways that contain these cycles and the like units. In particular, observations of endogenous or externally driven noise-induced dynamics in regulatory networks may thus provide additional insight into their topology, structure, and kinetics. network motif | signal transduction | chemical reaction | synthetic biology | systems biology
Noise-assisted data processing with empirical mode decomposition in biomedical signals.
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.
Symbol signal-to-noise ratio loss in square-wave subcarrier downconversion
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.
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.
Random Deep Belief Networks for Recognizing Emotions from Speech Signals
Directory of Open Access Journals (Sweden)
Guihua Wen
2017-01-01
Full Text Available Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition.
FPGA implementation of ICA algorithm for blind signal separation and adaptive noise canceling.
Kim, Chang-Min; Park, Hyung-Min; Kim, Taesu; Choi, Yoon-Kyung; Lee, Soo-Young
2003-01-01
An field programmable gate array (FPGA) implementation of independent component analysis (ICA) algorithm is reported for blind signal separation (BSS) and adaptive noise canceling (ANC) in real time. In order to provide enormous computing power for ICA-based algorithms with multipath reverberation, a special digital processor is designed and implemented in FPGA. The chip design fully utilizes modular concept and several chips may be put together for complex applications with a large number of noise sources. Experimental results with a fabricated test board are reported for ANC only, BSS only, and simultaneous ANC/BSS, which demonstrates successful speech enhancement in real environments in real time.
International Nuclear Information System (INIS)
Fegeant, Olivier
1999-01-01
The growing interest in wind energy has increased the need of accuracy in wind turbine noise immission measurements and thus, the need of new measurement techniques. This paper shows that mounting the microphone on a vertical board improves the signal-to-noise ratio over the whole frequency range compared to the free microphone technique. Indeed, the wind turbine is perceived two times noisier by the microphone due to the signal reflection by the board while, in addition, the wind noise is reduced. Furthermore, the board shielding effect allows the measurements to be carried out in the presence of reflecting surfaces such as building facades
Experimentally generated randomness certified by the impossibility of superluminal signals.
Bierhorst, Peter; Knill, Emanuel; Glancy, Scott; Zhang, Yanbao; Mink, Alan; Jordan, Stephen; Rommal, Andrea; Liu, Yi-Kai; Christensen, Bradley; Nam, Sae Woo; Stevens, Martin J; Shalm, Lynden K
2018-04-01
From dice to modern electronic circuits, there have been many attempts to build better devices to generate random numbers. Randomness is fundamental to security and cryptographic systems and to safeguarding privacy. A key challenge with random-number generators is that it is hard to ensure that their outputs are unpredictable 1-3 . For a random-number generator based on a physical process, such as a noisy classical system or an elementary quantum measurement, a detailed model that describes the underlying physics is necessary to assert unpredictability. Imperfections in the model compromise the integrity of the device. However, it is possible to exploit the phenomenon of quantum non-locality with a loophole-free Bell test to build a random-number generator that can produce output that is unpredictable to any adversary that is limited only by general physical principles, such as special relativity 1-11 . With recent technological developments, it is now possible to carry out such a loophole-free Bell test 12-14,22 . Here we present certified randomness obtained from a photonic Bell experiment and extract 1,024 random bits that are uniformly distributed to within 10 -12 . These random bits could not have been predicted according to any physical theory that prohibits faster-than-light (superluminal) signalling and that allows independent measurement choices. To certify and quantify the randomness, we describe a protocol that is optimized for devices that are characterized by a low per-trial violation of Bell inequalities. Future random-number generators based on loophole-free Bell tests may have a role in increasing the security and trust of our cryptographic systems and infrastructure.
Tückmantel, Joachim
2008-01-01
Artificial creation of arbitrary noise signals is used in accelerator physics to reproduce a measured perturbation spectrum for simulations but also to generate real-time shaped noise spectra for controlled emittance blow-up giving tailored properties to the final bunch shape. It is demonstrated here how one can produce numerically what is, for all practical purposes, an unlimited quantity of non-periodic noise data having any predefined spectral density. This spectral density may be constant or varying with time. The noise output never repeats and has excellent statistical properties, important for very long-term applications. It is difficult to obtain such flexibility and spectral cleanliness using analogue techniques. This algorithm was applied both in computer simulations of bunch behaviour in the presence of RF noise in the PS, SPS and LHC and also to generate real-time noise, tracking the synchrotron frequency change during the energy ramp of the SPS and producing controlled longitudinal emittance blow-...
Schwent, V. L.; Hillyard, S. A.; Galambos, R.
1975-01-01
A randomized sequence of tone bursts was delivered to subjects at short inter-stimulus intervals with the tones originating from one of three spatially and frequency specific channels. The subject's task was to count the tones in one of the three channels at a time, ignoring the other two, and press a button after each tenth tone. In different conditions, tones were given at high and low intensities and with or without a background white noise to mask the tones. The N sub 1 component of the auditory vertex potential was found to be larger in response to attended channel tones in relation to unattended tones. This selective enhancement of N sub 1 was minimal for loud tones presented without noise and increased markedly for the lower tone intensity and in noise added conditions.
Spectral data de-noising using semi-classical signal analysis: application to localized MRS
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
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.
Measuring multielectron beam imaging fidelity with a signal-to-noise ratio analysis
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.
Noise removal in extended depth of field microscope images through nonlinear signal processing.
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.
International Nuclear Information System (INIS)
Theodorsen, A; Garcia, O E; Rypdal, M
2017-01-01
Filtered Poisson processes are often used as reference models for intermittent fluctuations in physical systems. Such a process is here extended by adding a noise term, either as a purely additive term to the process or as a dynamical term in a stochastic differential equation. The lowest order moments, probability density function, auto-correlation function and power spectral density are derived and used to identify and compare the effects of the two different noise terms. Monte-Carlo studies of synthetic time series are used to investigate the accuracy of model parameter estimation and to identify methods for distinguishing the noise types. It is shown that the probability density function and the three lowest order moments provide accurate estimations of the model parameters, but are unable to separate the noise types. The auto-correlation function and the power spectral density also provide methods for estimating the model parameters, as well as being capable of identifying the noise type. The number of times the signal crosses a prescribed threshold level in the positive direction also promises to be able to differentiate the noise type. (paper)
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
International Nuclear Information System (INIS)
Okura, Yuki; Futamase, Toshifumi
2013-01-01
This is the third paper on the improvement of systematic errors in weak lensing analysis using an elliptical weight function, referred to as E-HOLICs. In previous papers, we succeeded in avoiding errors that depend on the ellipticity of the background image. In this paper, we investigate the systematic error that depends on the signal-to-noise ratio of the background image. We find that the origin of this error is the random count noise that comes from the Poisson noise of sky counts. The random count noise makes additional moments and centroid shift error, and those first-order effects are canceled in averaging, but the second-order effects are not canceled. We derive the formulae that correct this systematic error due to the random count noise in measuring the moments and ellipticity of the background image. The correction formulae obtained are expressed as combinations of complex moments of the image, and thus can correct the systematic errors caused by each object. We test their validity using a simulated image and find that the systematic error becomes less than 1% in the measured ellipticity for objects with an IMCAT significance threshold of ν ∼ 11.7.
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)
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.
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)
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.
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...
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
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
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.
Conditional Random Fields for Morphological Analysis of Wireless ECG Signals
Natarajan, Annamalai; Gaiser, Edward; Angarita, Gustavo; Malison, Robert; Ganesan, Deepak; Marlin, Benjamin
2015-01-01
Thanks to advances in mobile sensing technologies, it has recently become practical to deploy wireless electrocardiograph sensors for continuous recording of ECG signals. This capability has diverse applications in the study of human health and behavior, but to realize its full potential, new computational tools are required to effectively deal with the uncertainty that results from the noisy and highly non-stationary signals collected using these devices. In this work, we present a novel approach to the problem of extracting the morphological structure of ECG signals based on the use of dynamically structured conditional random field (CRF) models. We apply this framework to the problem of extracting morphological structure from wireless ECG sensor data collected in a lab-based study of habituated cocaine users. Our results show that the proposed CRF-based approach significantly out-performs independent prediction models using the same features, as well as a widely cited open source toolkit. PMID:26726321
Wan, Renzhi; Zu, Yunxiao; Shao, Lin
2018-04-01
The blood echo signal maintained through Medical ultrasound Doppler devices would always include vascular wall pulsation signal .The traditional method to de-noise wall signal is using high-pass filter, which will also remove the lowfrequency part of the blood flow signal. Some scholars put forward a method based on region selective reduction, which at first estimates of the wall pulsation signals and then removes the wall signal from the mixed signal. Apparently, this method uses the correlation between wavelet coefficients to distinguish blood signal from wall signal, but in fact it is a kind of wavelet threshold de-noising method, whose effect is not so much ideal. In order to maintain a better effect, this paper proposes an improved method based on wavelet coefficient correlation to separate blood signal and wall signal, and simulates the algorithm by computer to verify its validity.
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.
Enhancement of the Signal-to-Noise Ratio in Sonic Logging Waveforms by Seismic Interferometry
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.
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 ...
Effect of uncompensated SPN detector cables on neutron noise signals measured in VVER-440 reactors
Energy Technology Data Exchange (ETDEWEB)
Kiss, S. E-mail: kisss@sunserv.kfki.hu; Lipcsei, S. E-mail: lipcsei@sunserv.kfki.hu; Hazi, G. E-mail: gah@sunserv.kfki.hu
2003-03-01
The Self Powered Neutron Detector (SPND) noise measurements of an operating VVER-440 nuclear reactor are described and characterised. Signal characteristics may be radically influenced by the geometrical properties of the detector and the cable, and by the measuring arrangement. Simulator is used as a means of studying the structure of those phase spectra that show propagating perturbations measured on uncompensated SPN detectors. The paper presents measurements with detectors of very different sizes (i.e. 20 cm length SPNDs and the 200 cm length compensation cables), where the ratios of the global and local component differ significantly for the different detector sizes. This phenomenon is used up for signal compensation.
Subspace-Based Noise Reduction for Speech Signals via Diagonal and Triangular Matrix Decompositions
DEFF Research Database (Denmark)
Hansen, Per Christian; Jensen, Søren Holdt
We survey the definitions and use of rank-revealing matrix decompositions in single-channel noise reduction algorithms for speech signals. Our algorithms are based on the rank-reduction paradigm and, in particular, signal subspace techniques. The focus is on practical working algorithms, using both...... diagonal (eigenvalue and singular value) decompositions and rank-revealing triangular decompositions (ULV, URV, VSV, ULLV and ULLIV). In addition we show how the subspace-based algorithms can be evaluated and compared by means of simple FIR filter interpretations. The algorithms are illustrated...... with working Matlab code and applications in speech processing....
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.
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)
High-frequency signal and noise estimates of CSR GRACE RL04
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.
Reddy, V R; Reddy, T G; Reddy, P Y; Reddy, K R
2003-01-01
An AC modulation technique is described to convert stochastic signal variations into an amplitude variation and its retrieval through Fourier analysis. It is shown that this AC detection of signals of stochastic processes when processed through auto- and cross-correlation techniques improve the signal-to-noise ratio; the correlation techniques serve a similar purpose of frequency and phase filtering as that of phase-sensitive detection. A few model calculations applied to nuclear spectroscopy measurements such as Angular Correlations, Mossbauer spectroscopy and Pulse Height Analysis reveal considerable improvement in the sensitivity of signal detection. Experimental implementation of the technique is presented in terms of amplitude variations of harmonics representing the derivatives of normal spectra. Improved detection sensitivity to spectral variations is shown to be significant. These correlation techniques are general and can be made applicable to all the fields of particle counting where measurements ar...
Chuang, Jason; Ausloos, Emily C; Schwebach, Courtney A; Huang, Xin
2016-12-01
The perception of visual motion can be profoundly influenced by visual context. To gain insight into how the visual system represents motion speed, we investigated how a background stimulus that did not move in a net direction influenced the perceived speed of a center stimulus. Visual stimuli were two overlapping random-dot patterns. The center stimulus moved coherently in a fixed direction, whereas the background stimulus moved randomly. We found that human subjects perceived the speed of the center stimulus to be significantly faster than its veridical speed when the background contained motion noise. Interestingly, the perceived speed was tuned to the noise level of the background. When the speed of the center stimulus was low, the highest perceived speed was reached when the background had a low level of motion noise. As the center speed increased, the peak perceived speed was reached at a progressively higher background noise level. The effect of speed overestimation required the center stimulus to overlap with the background. Increasing the background size within a certain range enhanced the effect, suggesting spatial integration. The speed overestimation was significantly reduced or abolished when the center stimulus and the background stimulus had different colors, or when they were placed at different depths. When the center- and background-stimuli were perceptually separable, speed overestimation was correlated with perceptual similarity between the center- and background-stimuli. These results suggest that integration of motion energy from random motion noise has a significant impact on speed perception. Our findings put new constraints on models regarding the neural basis of speed perception. Copyright © 2016 the American Physiological Society.
A semi-supervised method to detect seismic random noise with fuzzy GK clustering
International Nuclear Information System (INIS)
Hashemi, Hosein; Javaherian, Abdolrahim; Babuska, Robert
2008-01-01
We present a new method to detect random noise in seismic data using fuzzy Gustafson–Kessel (GK) clustering. First, using an adaptive distance norm, a matrix is constructed from the observed seismic amplitudes. The next step is to find centres of ellipsoidal clusters and construct a partition matrix which determines the soft decision boundaries between seismic events and random noise. The GK algorithm updates the cluster centres in order to iteratively minimize the cluster variance. Multiplication of the fuzzy membership function with values of each sample yields new sections; we name them 'clustered sections'. The seismic amplitude values of the clustered sections are given in a way to decrease the level of noise in the original noisy seismic input. In pre-stack data, it is essential to study the clustered sections in a f–k domain; finding the quantitative index for weighting the post-stack data needs a similar approach. Using the knowledge of a human specialist together with the fuzzy unsupervised clustering, the method is a semi-supervised random noise detection. The efficiency of this method is investigated on synthetic and real seismic data for both pre- and post-stack data. The results show a significant improvement of the input noisy sections without harming the important amplitude and phase information of the original data. The procedure for finding the final weights of each clustered section should be carefully done in order to keep almost all the evident seismic amplitudes in the output section. The method interactively uses the knowledge of the seismic specialist in detecting the noise
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
Statistical Angles on the Lattice QCD Signal-to-Noise Problem
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
Reduction of Musical Noise in Spectral Subtraction Method Using Subframe Phase Randomization
Energy Technology Data Exchange (ETDEWEB)
Seok, J.W.; Bae, K.S. [Kyungpook National University, Taegu (Korea)
1999-06-01
The Subframe phase randomization method is applied to the spectral subtraction method to reduce the musical noise in nonvoicing region after speech enhancement. The musical noise in the spectral subtraction method is the result of the narrowband tonal components that appearing somewhat periodically in the spectrogram of unvoiced and silence regions. Thus each synthesis frame in nonvoicing region is divided into several subframes to broaden the narrowband spectrum, and then phases of silence and unvoiced regions are randomized to eliminate the tonal components in the spectrum while keeping the shape of the amplitude spectrum. Performance assessments based on visual inspection of spectrogram, objective measure, and informal subjective listening tests demonstrate the superiority of the proposed algorithm. (author). 7 refs., 5 figs.
Noise and DC balanced outlet temperature signals for monitoring coolant flow in LMFBR fuel elements
International Nuclear Information System (INIS)
Edelmann, M.
1977-01-01
Local cooling disturbances in LMFBR fuel elements may have serious safety implications for the whole reactor core. They have to be detected reliably in an early stage of their formation therefore. This can be accomplished in principle by individual monitoring of the coolant flow rate or the coolant outlet temperature of the sub-assemblies with high precision. In this paper a method is proposed to increase the sensitivity of outlet temperature signals to cooling disturbances. Using balanced temperature signals provides a means for eliminating the normal variations from the original signals which limit the sensitivity and speed of response to cooling disturbances. It is shown that a balanced signal can be derived easily from the original temperature signal by subtracting an inlet temperature and a neutron detector signal with appropriate time shift. The method was tested with tape-recorded noise signals of the KNK I reactor at Karlsruhe. The experimental results confirm the theoretical predictions. A significant reduction of the uncertainty of measured outlet temperatures was achieved. This enables very sensitive and fast response monitoring of coolant flow. Furthermore, it was found that minimizing the variance of the balanced signal offers the possibility for a rough determination of the heat transfer coefficient of the fuel rods during normal reactor operation at power. (author)
Noise texture and signal detectability in propagation-based x-ray phase-contrast tomography
International Nuclear Information System (INIS)
Chou, Cheng-Ying; Anastasio, Mark A.
2010-01-01
Purpose: X-ray phase-contrast tomography (PCT) is a rapidly emerging imaging modality for reconstructing estimates of an object's three-dimensional x-ray refractive index distribution. Unlike conventional x-ray computed tomography methods, the statistical properties of the reconstructed images in PCT remain unexplored. The purpose of this work is to quantitatively investigate noise propagation in PCT image reconstruction. Methods: The authors derived explicit expressions for the autocovariance of the reconstructed absorption and refractive index images to characterize noise texture and understand how the noise properties are influenced by the imaging geometry. Concepts from statistical detection theory were employed to understand how the imaging geometry-dependent statistical properties affect the signal detection performance in a signal-known-exactly/background-known-exactly task. Results: The analytical formulas for the phase and absorption autocovariance functions were implemented numerically and compared to the corresponding empirical values, and excellent agreement was found. They observed that the reconstructed refractive images are highly spatially correlated, while the absorption images are not. The numerical results confirm that the strength of the covariance is scaled by the detector spacing. Signal detection studies were conducted, employing a numerical observer. The detection performance was found to monotonically increase as the detector-plane spacing was increased. Conclusions: The authors have conducted the first quantitative investigation of noise propagation in PCT image reconstruction. The reconstructed refractive images were found to be highly spatially correlated, while absorption images were not. This is due to the presence of a Fourier space singularity in the reconstruction formula for the refraction images. The statistical analysis may facilitate the use of task-based image quality measures to further develop and optimize this emerging
Noise texture and signal detectability in propagation-based x-ray phase-contrast tomography
Energy Technology Data Exchange (ETDEWEB)
Chou, Cheng-Ying; Anastasio, Mark A. [Department of Bio-Industrial Mechatronics Engineering, National Taiwan University, 1, Section 4, Roosevelt Road, Taipei, Taiwan 106, Taiwan (China); Department of Biomedical Engineering, Medical Imaging Research Center, Illinois Institute of Technology, 3440 S. Dearborn Street, E1-116, Chicago, Illinois 60616 (United States)
2010-01-15
Purpose: X-ray phase-contrast tomography (PCT) is a rapidly emerging imaging modality for reconstructing estimates of an object's three-dimensional x-ray refractive index distribution. Unlike conventional x-ray computed tomography methods, the statistical properties of the reconstructed images in PCT remain unexplored. The purpose of this work is to quantitatively investigate noise propagation in PCT image reconstruction. Methods: The authors derived explicit expressions for the autocovariance of the reconstructed absorption and refractive index images to characterize noise texture and understand how the noise properties are influenced by the imaging geometry. Concepts from statistical detection theory were employed to understand how the imaging geometry-dependent statistical properties affect the signal detection performance in a signal-known-exactly/background-known-exactly task. Results: The analytical formulas for the phase and absorption autocovariance functions were implemented numerically and compared to the corresponding empirical values, and excellent agreement was found. They observed that the reconstructed refractive images are highly spatially correlated, while the absorption images are not. The numerical results confirm that the strength of the covariance is scaled by the detector spacing. Signal detection studies were conducted, employing a numerical observer. The detection performance was found to monotonically increase as the detector-plane spacing was increased. Conclusions: The authors have conducted the first quantitative investigation of noise propagation in PCT image reconstruction. The reconstructed refractive images were found to be highly spatially correlated, while absorption images were not. This is due to the presence of a Fourier space singularity in the reconstruction formula for the refraction images. The statistical analysis may facilitate the use of task-based image quality measures to further develop and optimize this emerging
Enhancing scatterometry CD signal-to-noise ratio for 1x logic and memory challenges
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.
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.
Jousselme, Chloé; Vialet, Renaud; Jouve, Elisabeth; Lagier, Pierre; Martin, Claude; Michel, Fabrice
2011-03-01
To determine whether a sound-activated light-alarm device could reduce the noise in the central area of our pediatric intensive care unit and to determine whether this reduction was significant enough to decrease the noise that could be perceived by a patient located in a nearby room. The secondary objective was to determine the mode of action of the device. In a 16-bed pediatric and neonatal intensive care unit, a large and clearly noticeable sound-activated light device was set in the noisiest part of the central area of our unit, and noise measurements were made in the central area and in a nearby room. In a prospective, quasi-experimental design, sound levels were compared across three different situations--no device present, device present and turned on, and device present but turned off--and noise level measurements were made over a total of 18 days. None. Setting a sound-activated light device on or off. When the device was present, the noise was about 2 dB lower in the central area and in a nearby room, but there was no difference in noise level with the device turned on vs. turned off. The noise decrease in the central area was of limited importance but was translated in a nearby room. The sound-activated light device did not directly decrease noise when turned on, but repetition of the visual signal throughout the day raised staff awareness of noise levels over time.
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
International Nuclear Information System (INIS)
Collatz, S.
1982-01-01
Reactor noise spectra of in core neutron detectors are measured in the low frequency range (0.03 Hz to 1 Hz) and evaluated. The increase of the effective noise signal value is due to pressure oscillations or oscillations of special steam volume portions. Thus boiling monitoring of reactor cores in PWR type reactors may be possible, if the low frequency noise of the whole set of in core detectors is taken into account
Directory of Open Access Journals (Sweden)
Hong-Wei Ma
2016-09-01
Full Text Available In order to reduce the noise of a defect electromagnetic signal of the steel cord conveyor belt used in coal mines, a new signal noise reduction method by combined use of the improved threshold wavelet and Empirical Mode Decomposition (EMD is proposed. Firstly, the denoising method based on the improved threshold wavelet is applied to reduce the noise of a defect electromagnetic signal obtained by an electromagnetic testing system. Then, the EMD is used to decompose the denoised signal and then the effective Intrinsic Mode Function (IMF is extracted by the dominant eigenvalue strategy. Finally, the signal reconstruction is carried out by utilizing the obtained IMF. In order to verify the proposed noise reduction method, the experiments are carried out in two cases including the defective joint and steel wire rope break. The experimental results show that the proposed method in this paper obtains the higher Signal to Noise Ratio (SNR for the defect electromagnetic signal noise reduction of steel cord conveyor belts.
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.
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.
Institute of Scientific and Technical Information of China (English)
Liu Li; Zhang Liang-Ying; Cao Li
2009-01-01
The diffusion in a harmonic oscillator driven by coloured noises ζ(t) and η(t) with coloured cross-correlation in which one of the noises is modulated by a biased periodic signal is investigated. The exact expression of diffusion coefficient d as a function of noise parameter, signal parameter, and oscillator frequency is derived. The findings in this paper are as follows. 1) The curves of d versus noise intensity D and d versus noises cross-correlation time τ_3 exist as two different phases. The transition between the two phases arises from the change of the cross-correlation coefficient λ of the two Orustein-Uhlenbeck (O-U) noises. 2) Changing the value of τ3, the curves of d versus Q, the intensity of colored noise that is modulated by the signal, can transform from a phase having a minimum to a monotonic phase. 3)Changing the value of signal amplitude A, d versus Q curves can transform from a phase having a minimum to a monotonic phase. The above-mentioned results demonstrate that a like noise-induced transition appears in the model.
International Nuclear Information System (INIS)
Li, Liu; Li, Cao; Liang-Ying, Zhang
2009-01-01
The diffusion in a harmonic oscillator driven by coloured noises ζ(t) and η(t) with coloured cross-correlation in which one of the noises is modulated by a biased periodic signal is investigated. The exact expression of diffusion coefficient d as a function of noise parameter, signal parameter, and oscillator frequency is derived. The findings in this paper are as follows. 1) The curves of d versus noise intensity D and d versus noises cross-correlation time τ 3 exist as two different phases. The transition between the two phases arises from the change of the cross-correlation coefficient λ of the two Ornstein–Uhlenbeck (O-U) noises. 2) Changing the value of τ 3 , the curves of d versus Q, the intensity of colored noise that is modulated by the signal, can transform from a phase having a minimum to a monotonic phase. 3) Changing the value of signal amplitude A, d versus Q curves can transform from a phase having a minimum to a monotonic phase. The above-mentioned results demonstrate that a like noise-induced transition appears in the model. (general)
Song, Shuang; Rooijakkers, M.J.; Harpe, P.; Rabotti, C.; Mischi, M.; Van Roermund, A.H.M.; Cantatore, E.
2016-01-01
This paper presents a noise-reconfigurable resistive feedback amplifier with current-reuse technique for fetal ECG monitoring. The proposed amplifier allows for both tuning of the noise level and changing the power consumption according to the signal properties, minimizing the total power
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.
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...
Correlated cone noise decreases rod signal contributions to the post-receptoral pathways.
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.
Signal-to-noise ratio application to seismic marker analysis and fracture detection
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.
Listening to the Deep: live monitoring of ocean noise and cetacean acoustic signals.
André, M; van der Schaar, M; Zaugg, S; Houégnigan, L; Sánchez, A M; Castell, J V
2011-01-01
The development and broad use of passive acoustic monitoring techniques have the potential to help assessing the large-scale influence of artificial noise on marine organisms and ecosystems. Deep-sea observatories have the potential to play a key role in understanding these recent acoustic changes. LIDO (Listening to the Deep Ocean Environment) is an international project that is allowing the real-time long-term monitoring of marine ambient noise as well as marine mammal sounds at cabled and standalone observatories. Here, we present the overall development of the project and the use of passive acoustic monitoring (PAM) techniques to provide the scientific community with real-time data at large spatial and temporal scales. Special attention is given to the extraction and identification of high frequency cetacean echolocation signals given the relevance of detecting target species, e.g. beaked whales, in mitigation processes, e.g. during military exercises. Copyright © 2011. Published by Elsevier Ltd.
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
Lugli, Marco
2015-12-07
Animal acoustic communication commonly takes place under masked conditions. For instance, sound signals relevant for mating and survival are very often masked by background noise, which makes their detection and recognition by organisms difficult. Ambient noise (AN) varies in level and shape among different habitats, but also remarkable variations in time and space occurs within the same habitat. Variable AN conditions mask hearing thresholds of the receiver in complex and unpredictable ways, thereby causing distortions in sound perception. When communication takes place in a noisy environment, a highly sensitive system might confer no advantage to the receiver compared to a less sensitive one. The effects of noise masking on auditory thresholds and hearing-related functions are well known, and the potential role of AN in the evolution of the species' auditory sensitivity has been recognized by few authors. The mechanism of the underlying selection process has never been explored, however. Here I present a simple fitness model that seeks for the best sensitivity of a hearing system performing the detection and recognition of the sound under variable AN conditions. The model predicts higher sensitivity (i.e. lower hearing thresholds) as best strategy for species living in quiet habitats and lower sensitivity (i.e. higher hearing thresholds) as best strategy for those living in noisy habitats provided the cost of incorrect recognition is not low. The tradeoff between detection and recognition of acoustic signals appears to be a key factor determining the best level of hearing sensitivity of a species when acoustic communication is corrupted by noise. Copyright © 2015 Elsevier Ltd. All rights reserved.
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.
Modeling Signal-Noise Processes Supports Student Construction of a Hierarchical Image of Sample
Lehrer, Richard
2017-01-01
Grade 6 (modal age 11) students invented and revised models of the variability generated as each measured the perimeter of a table in their classroom. To construct models, students represented variability as a linear composite of true measure (signal) and multiple sources of random error. Students revised models by developing sampling…
Directory of Open Access Journals (Sweden)
Dongyan Chen
2015-01-01
Full Text Available This paper is concerned with the optimal Kalman filtering problem for a class of discrete stochastic systems with multiplicative noises and random two-step sensor delays. Three Bernoulli distributed random variables with known conditional probabilities are introduced to characterize the phenomena of the random two-step sensor delays which may happen during the data transmission. By using the state augmentation approach and innovation analysis technique, an optimal Kalman filter is constructed for the augmented system in the sense of the minimum mean square error (MMSE. Subsequently, the optimal Kalman filtering is derived for corresponding augmented system in initial instants. Finally, a simulation example is provided to demonstrate the feasibility and effectiveness of the proposed filtering method.
Brain-computer interfaces increase whole-brain signal to noise.
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.
International Nuclear Information System (INIS)
Glockler, O.; Cooke, D.F.; Tulett, M.V.
1995-01-01
In 1992, a program was initiated to establish reactor noise analysis as a practical tool for plant performance monitoring and system diagnostics in Ontario Hydro's CANDU reactors. Since then, various CANDU-specific noise analysis applications have been developed and validated. The noise-based statistical techniques are being successfully applied as powerful troubleshooting and diagnostic tools to a wide variety of actual operational I and C problems. Critical plant components, instrumentation and processes are monitored on a regular basis, and their dynamic characteristics are verified on-power. Recent applications of noise analysis include (1) validating the dynamics of in-core flux detectors (ICFDS) and ion chambers, (2) estimating the prompt fraction ICFDs in noise measurements at full power and in power rundown tests, (3) identifying the cause of excessive signal fluctuations in certain flux detectors, (4) validating the dynamic coupling between liquid zone control signals, (5) detecting and monitoring mechanical vibrations of detector tubes, reactivity devices and fuel channels induced by moderator/coolant flow, (6) estimating the dynamics and response time of RTD temperature signals, (7) isolating the cause of RTD signal anomalies, (8) investigating the source of abnormal flow signal behaviour, (9) estimating the overall response time of flow and pressure signals, (1 0) detecting coolant boiling in fully instrumented fuel channels, (1 1) monitoring moderator circulation via temperature noise, and (12) predicting the performance of shut-off rods. Some of these applications are performed on an as needed basis. The noise analysis program, in the Pickering-B station alone, has saved Ontario Hydro millions of dollars during its first three years. The results of the noise analysis program have been also reviewed by the regulator (Atomic Energy Control Board of Canada) with favorable results. The AECB have expressed interest in Ontario Hydro further exploiting the
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.
Soury, Hamza
2013-07-01
This paper considers the average symbol error probability of square Quadrature Amplitude Modulation (QAM) coherent signaling over flat fading channels subject to additive generalized Gaussian noise. More specifically, a generic closedform expression in terms of the Fox H function and the bivariate Fox H function is offered for the extended generalized-K fading case. Simplifications for some special fading distributions such as generalized-K fading, Nakagami-m fading, and Rayleigh fading and special additive noise distributions such as Gaussian and Laplacian noise are then presented. Finally, the mathematical formalism is illustrated by some numerical examples verified by computer based simulations for a variety of fading and additive noise parameters.
Seismic signal and noise on Europa and how to use it
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.
Stimulation of the Locus Ceruleus Modulates Signal-to-Noise Ratio in the Olfactory Bulb.
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.
MIMO Radar Transceiver Design for High Signal-to-Interference-Plus-Noise Ratio
Lipor, John
2013-05-12
Multiple-input multiple-output (MIMO) radar employs orthogonal or partially correlated transmit signals to achieve performance benefits over its phased-array counterpart. It has been shown that MIMO radar can achieve greater spatial resolution, improved signal-to-noise ratio (SNR) and target localization, and greater clutter resolution using space-time adaptive processing (STAP). This thesis explores various methods to improve the signal-to-interference-plus-noise ratio (SINR) via transmit and receive beamforming. In MIMO radar settings, it is often desirable to transmit power only to a given location or set of locations defined by a beampattern. Current methods involve a two- step process of designing the transmit covariance matrix R via iterative solutions and then using R to generate waveforms that fulfill practical constraints such as having a constant-envelope or drawing from a finite alphabet. In this document, a closed- form method to design R is proposed that utilizes the discrete Fourier transform (DFT) coefficients and Toeplitz matrices. The resulting covariance matrix fulfills the practical constraints such as positive semidefiniteness and the uniform elemental power constraint and provides performance similar to that of iterative methods, which require a much greater computation time. Next, a transmit architecture is presented that exploits the orthogonality of frequencies at discrete DFT values to transmit a sum of orthogonal signals from each antenna. The resulting waveforms provide a lower mean-square error than current methods at a much lower computational cost, and a simulated detection scenario demonstrates the performance advantages achieved. It is also desirable to receive signal power only from a given set of directions defined by a beampattern. In a later chapter of this document, the problem of receive beampattern matching is formulated and three solutions to this problem are demonstrated. We show that partitioning the received data vector
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
Random signal tomographical analysis of two-phase flow
International Nuclear Information System (INIS)
Han, P.; Wesser, U.
1990-01-01
This paper reports on radiation tomography which is a useful tool for studying the internal structures of two-phase flow. However, general tomography analysis gives only time-averaged results, hence much information is lost. As a result, it is sometimes difficult to identify the flow regime; for example, the time-averaged picture does not significantly change as an annual flow develops from a slug flow. A two-phase flow diagnostic technique based on random signal tomographical analysis is developed. It extracts more information by studying the statistical variation of the measured signal with time. Local statistical parameters, including mean value, variance, skewness and flatness etc., are reconstructed from the information obtained by a general tomography technique. More important information are provided by the results. Not only the void fraction can be easily calculated, but also the flow pattern can be identified more objectively and more accurately. The experimental setup is introduced. It consisted of a two-phase flow loop, an X-ray system, a fan-like five-beam detector system and a signal acquisition and processing system. In the experiment, for both horizontal and vertical test sections (aluminum and steel tube with Di/Do = 40/45 mm), different flow situations are realized by independently adjusting air and water mass flow. Through a glass tube connected with the test section, some typical flow patterns are visualized and used for comparing with the reconstruction results
Random noise suppression of seismic data using non-local Bayes algorithm
Chang, De-Kuan; Yang, Wu-Yang; Wang, Yi-Hui; Yang, Qing; Wei, Xin-Jian; Feng, Xiao-Ying
2018-02-01
For random noise suppression of seismic data, we present a non-local Bayes (NL-Bayes) filtering algorithm. The NL-Bayes algorithm uses the Gaussian model instead of the weighted average of all similar patches in the NL-means algorithm to reduce the fuzzy of structural details, thereby improving the denoising performance. In the denoising process of seismic data, the size and the number of patches in the Gaussian model are adaptively calculated according to the standard deviation of noise. The NL-Bayes algorithm requires two iterations to complete seismic data denoising, but the second iteration makes use of denoised seismic data from the first iteration to calculate the better mean and covariance of the patch Gaussian model for improving the similarity of patches and achieving the purpose of denoising. Tests with synthetic and real data sets demonstrate that the NL-Bayes algorithm can effectively improve the SNR and preserve the fidelity of seismic data.
Dwivedi, Prashant Povel; Choi, Hee Joo; Kim, Byoung Joo; Cha, Myoungsik
2013-12-16
Random duty-cycle errors (RDE) in ferroelectric quasi-phase-matching (QPM) devices not only affect the frequency conversion efficiency, but also generate non-phase-matched parasitic noise that can be detrimental to some applications. We demonstrate an accurate but simple method for measuring the RDE in periodically poled lithium niobate. Due to the equivalence between the undepleted harmonic generation spectrum and the diffraction pattern from the QPM grating, we employed linear diffraction measurement which is much simpler than tunable harmonic generation experiments [J. S. Pelc, et al., Opt. Lett.36, 864-866 (2011)]. As a result, we could relate the RDE for the QPM device to the relative noise intensity between the diffraction orders.
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
Brown, Patrick T.; Li, Wenhong; Cordero, Eugene C.; Mauget, Steven A.
2015-01-01
The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20th century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal. PMID:25898351
Brown, Patrick T; Li, Wenhong; Cordero, Eugene C; Mauget, Steven A
2015-04-21
The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20(th) century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal.
International Nuclear Information System (INIS)
Vinogradov, S.
2012-01-01
Silicon Photomultipliers (SiPM), also called Solid State Photomultipliers (SSPM), are based on Geiger mode avalanche breakdown that is limited by a strong negative feedback. An SSPM can detect and resolve single photons due to the high gain and ultra-low excess noise of avalanche multiplication in this mode. Crosstalk and afterpulsing processes associated with the high gain introduce specific excess noise and deteriorate the photon number resolution of the SSPM. The probabilistic features of these processes are widely studied because of its significance for the SSPM design, characterization, optimization and application, but the process modeling is mostly based on Monte Carlo simulations and numerical methods. In this study, crosstalk is considered to be a branching Poisson process, and analytical models of probability distribution and excess noise factor (ENF) of SSPM signals based on the Borel distribution as an advance on the geometric distribution models are presented and discussed. The models are found to be in a good agreement with the experimental probability distributions for dark counts and a few photon spectrums in a wide range of fired pixels number as well as with observed super-linear behavior of crosstalk ENF.
Intrinsic low pass filtering improves signal-to-noise ratio in critical-point flexure biosensors
International Nuclear Information System (INIS)
Jain, Ankit; Alam, Muhammad Ashraful
2014-01-01
A flexure biosensor consists of a suspended beam and a fixed bottom electrode. The adsorption of the target biomolecules on the beam changes its stiffness and results in change of beam's deflection. It is now well established that the sensitivity of sensor is maximized close to the pull-in instability point, where effective stiffness of the beam vanishes. The question: “Do the signal-to-noise ratio (SNR) and the limit-of-detection (LOD) also improve close to the instability point?”, however remains unanswered. In this article, we systematically analyze the noise response to evaluate SNR and establish LOD of critical-point flexure sensors. We find that a flexure sensor acts like an effective low pass filter close to the instability point due to its relatively small resonance frequency, and rejects high frequency noise, leading to improved SNR and LOD. We believe that our conclusions should establish the uniqueness and the technological relevance of critical-point biosensors.
Speech perception at positive signal-to-noise ratios using adaptive adjustment of time compression.
Schlueter, Anne; Brand, Thomas; Lemke, Ulrike; Nitzschner, Stefan; Kollmeier, Birger; Holube, Inga
2015-11-01
Positive signal-to-noise ratios (SNRs) characterize listening situations most relevant for hearing-impaired listeners in daily life and should therefore be considered when evaluating hearing aid algorithms. For this, a speech-in-noise test was developed and evaluated, in which the background noise is presented at fixed positive SNRs and the speech rate (i.e., the time compression of the speech material) is adaptively adjusted. In total, 29 younger and 12 older normal-hearing, as well as 24 older hearing-impaired listeners took part in repeated measurements. Younger normal-hearing and older hearing-impaired listeners conducted one of two adaptive methods which differed in adaptive procedure and step size. Analysis of the measurements with regard to list length and estimation strategy for thresholds resulted in a practical method measuring the time compression for 50% recognition. This method uses time-compression adjustment and step sizes according to Versfeld and Dreschler [(2002). J. Acoust. Soc. Am. 111, 401-408], with sentence scoring, lists of 30 sentences, and a maximum likelihood method for threshold estimation. Evaluation of the procedure showed that older participants obtained higher test-retest reliability compared to younger participants. Depending on the group of listeners, one or two lists are required for training prior to data collection.
A complex symbol signal-to-noise ratio estimator and its performance
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.
Park, H K; Bradley, J S
2009-09-01
Subjective ratings of the audibility, annoyance, and loudness of music and speech sounds transmitted through 20 different simulated walls were used to identify better single number ratings of airborne sound insulation. The first part of this research considered standard measures such as the sound transmission class the weighted sound reduction index (R(w)) and variations of these measures [H. K. Park and J. S. Bradley, J. Acoust. Soc. Am. 126, 208-219 (2009)]. This paper considers a number of other measures including signal-to-noise ratios related to the intelligibility of speech and measures related to the loudness of sounds. An exploration of the importance of the included frequencies showed that the optimum ranges of included frequencies were different for speech and music sounds. Measures related to speech intelligibility were useful indicators of responses to speech sounds but were not as successful for music sounds. A-weighted level differences, signal-to-noise ratios and an A-weighted sound transmission loss measure were good predictors of responses when the included frequencies were optimized for each type of sound. The addition of new spectrum adaptation terms to R(w) values were found to be the most practical approach for achieving more accurate predictions of subjective ratings of transmitted speech and music sounds.
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
The impact of signal-to-noise ratio on contextual cueing in children and adults.
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.
Free Energy Adjusted Peak Signal to Noise Ratio (FEA-PSNR) for Image Quality Assessment
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.
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)
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.
Oeftiger, U; Caspers, Fritz
1992-01-01
For the measurement of Beam Transfer Functions the signal-to-noise ratio is of great importance. In order to get a reasonable quality of the measured data one may apply averaging and smoothing. In the following another technique called time gating to improve the quality of the measurement will be described. By this technique the measurement data are Fourier transformed and then modified in time domain. Tune gating suppresses signal contributions that are correlated to a time interval when no interesting information is expected. Afterivards an inverse Fourier transform leads to data in frequency domain with an improved signal to noise ratio.
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....
Techniques and software tools for estimating ultrasonic signal-to-noise ratios
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
Ronacher, Bernhard; Wohlgemuth, Sandra; Vogel, Astrid; Krahe, Rüdiger
2008-08-01
A characteristic feature of hearing systems is their ability to resolve both fast and subtle amplitude modulations of acoustic signals. This applies also to grasshoppers, which for mate identification rely mainly on the characteristic temporal patterns of their communication signals. Usually the signals arriving at a receiver are contaminated by various kinds of noise. In addition to extrinsic noise, intrinsic noise caused by stochastic processes within the nervous system contributes to making signal recognition a difficult task. The authors asked to what degree intrinsic noise affects temporal resolution and, particularly, the discrimination of similar acoustic signals. This study aims at exploring the neuronal basis for sexual selection, which depends on exploiting subtle differences between basically similar signals. Applying a metric, by which the similarities of spike trains can be assessed, the authors investigated how well the communication signals of different individuals of the same species could be discriminated and correctly classified based on the responses of auditory neurons. This spike train metric yields clues to the optimal temporal resolution with which spike trains should be evaluated. (c) 2008 APA, all rights reserved
International Nuclear Information System (INIS)
Stekelenburg, A.J.C.; Hagen, T.H.J.J. van der
1996-01-01
In this paper, the state of the art of the measurement of two-phase flow variables in a boiling water reactor (BWR) by analysis of in-core neutron detector noise signals is given. It is concluded that the neutronic processes involved in neutron noise are quite well understood, but that little is known about the density fluctuations in two-phase flow which are the main cause of the neutron noise. For this reason, the neutron noise measurements, like the well known two-detector velocity measurements, are still difficult to interpret. By analyzing neutron noise measurements in a natural circulation cooled BWR, it is illustrated that, once a theory on the density fluctuations is developed, two-phase flow can be monitored with a single in-core detector. (author). 70 refs, 4 figs
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
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.
Sams-Dodd, F; Capranica, R R
1996-10-01
Acoustic signals are generally encoded in the peripheral auditory system of vertebrates by a duality scheme. For frequency components that fall within the excitatory tuning curve, individual eighth nerve fibers can encode the effective spectral energy by a spike-rate code, while simultaneously preserving the signal waveform periodicity of lower frequency components by phase-locked spike-train discharges. To explore how robust this duality of representation may be in the presence of noise, we recorded the responses of auditory fibers in the eighth nerve of the Tokay gecko to tonal stimuli when masking noise was added simultaneously. We found that their spike-rate functions reached plateau levels fairly rapidly in the presence of noise, so the ability to signal the presence of a tone by a concomitant change in firing rate was quickly lost. On the other hand, their synchronization functions maintained a high degree of phase-locked firings to the tone even in the presence of high-intensity masking noise, thus enabling a robust detection of the tonal signal. Critical ratios (CR) and critical bandwidths showed that in the frequency range where units are able to phaselock to the tonal periodicity, the CR bands were relatively narrow and the bandwidths were independent of noise level. However, to higher frequency tones where phaselocking fails and only spike-rate codes apply, the CR bands were much wider and depended upon noise level, so that their ability to filter tones out of a noisy background degraded with increasing noise levels. The greater robustness of phase-locked temporal encoding contrasted with spike-rate coding verifies a important advantage in using lower frequency signals for communication in noisy environments.
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
From noise to signal - a new approach to LHCb muon optimization
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...
Separation of pulsar signals from noise using supervised machine learning algorithms
Bethapudi, S.; Desai, S.
2018-04-01
We evaluate the performance of four different machine learning (ML) algorithms: an Artificial Neural Network Multi-Layer Perceptron (ANN MLP), Adaboost, Gradient Boosting Classifier (GBC), and XGBoost, for the separation of pulsars from radio frequency interference (RFI) and other sources of noise, using a dataset obtained from the post-processing of a pulsar search pipeline. This dataset was previously used for the cross-validation of the SPINN-based machine learning engine, obtained from the reprocessing of the HTRU-S survey data (Morello et al., 2014). We have used the Synthetic Minority Over-sampling Technique (SMOTE) to deal with high-class imbalance in the dataset. We report a variety of quality scores from all four of these algorithms on both the non-SMOTE and SMOTE datasets. For all the above ML methods, we report high accuracy and G-mean for both the non-SMOTE and SMOTE cases. We study the feature importances using Adaboost, GBC, and XGBoost and also from the minimum Redundancy Maximum Relevance approach to report algorithm-agnostic feature ranking. From these methods, we find that the signal to noise of the folded profile to be the best feature. We find that all the ML algorithms report FPRs about an order of magnitude lower than the corresponding FPRs obtained in Morello et al. (2014), for the same recall value.
Grosveld, Ferdinand W.
1990-01-01
The feasibility of predicting interior noise due to random acoustic or turbulent boundary layer excitation was investigated in experiments in which a statistical energy analysis model (VAPEPS) was used to analyze measurements of the acceleration response and sound transmission of flat aluminum, lucite, and graphite/epoxy plates exposed to random acoustic or turbulent boundary layer excitation. The noise reduction of the plate, when backed by a shallow cavity and excited by a turbulent boundary layer, was predicted using a simplified theory based on the assumption of adiabatic compression of the fluid in the cavity. The predicted plate acceleration response was used as input in the noise reduction prediction. Reasonable agreement was found between the predictions and the measured noise reduction in the frequency range 315-1000 Hz.
International Nuclear Information System (INIS)
Lu, Guangfeng; Wang, Zhiguo; Fan, Zhenfang; Luo, Hui
2014-01-01
Periodic rotation noise in the outputs of multi-oscillator ring laser gyros (MRLGs) is investigated in this paper for the first time. It is proved theoretically and experimentally that noise is induced by the crosstalk between two beat-frequency signals, which are combined from the left and right circularly polarized counter-propagating beams in MRLGs. Theoretical analysis and experimental results also indicate that the fundamental frequency of this noise is equal to the frequency difference between the two beat-frequency signals and the amplitude of the fundamental component is proportional to the crosstalk ratio between the two beat-frequency signals. Further, the amplitude of the nth-order component is proportional to the nth power of the crosstalk ratio. (paper)
Macromolecular 3D SEM reconstruction strategies: Signal to noise ratio and resolution
International Nuclear Information System (INIS)
Woodward, J.D.; Wepf, R.A.
2014-01-01
Three-dimensional scanning electron microscopy generates quantitative volumetric structural data from SEM images of macromolecules. This technique provides a quick and easy way to define the quaternary structure and handedness of protein complexes. Here, we apply a variety of preparation and imaging methods to filamentous actin in order to explore the relationship between resolution, signal-to-noise ratio, structural preservation and dataset size. This information can be used to define successful imaging strategies for different applications. - Highlights: • F-actin SEM datasets were collected using 8 different preparation/ imaging techniques. • Datasets were reconstructed by back projection and compared/analyzed • 3DSEM actin reconstructions can be produced with <100 views of the asymmetric unit. • Negatively stained macromolecules can be reconstructed by 3DSEM to ∼3 nm resolution
DEFF Research Database (Denmark)
Schmidt, Erik
2007-01-01
sounds, has found that both normal-hearing and hearing-impaired listeners prefer loud sounds to be closer to the most comfortable loudness-level, than suggested by common non-linear fitting rules. During this project, two listening experiments were carried out. In the first experiment, hearing aid users......Hearing aid processing of loud speech and noise signals: Consequences for loudness perception and listening comfort. Sound processing in hearing aids is determined by the fitting rule. The fitting rule describes how the hearing aid should amplify speech and sounds in the surroundings......, such that they become audible again for the hearing impaired person. The general goal is to place all sounds within the hearing aid users’ audible range, such that speech intelligibility and listening comfort become as good as possible. Amplification strategies in hearing aids are in many cases based on empirical...
Combining of Direct Search and Signal-to-Noise Ratio for economic dispatch optimization
International Nuclear Information System (INIS)
Lin, Whei-Min; Gow, Hong-Jey; Tsai, Ming-Tang
2011-01-01
This paper integrated the ideas of Direct Search and Signal-to-Noise Ratio (SNR) to develop a Novel Direct Search (NDS) method for solving the non-convex economic dispatch problems. NDS consists of three stages: Direct Search (DS), Global SNR (GSNR) and Marginal Compensation (MC) stages. DS provides a basic solution. GSNR searches the point with optimization strategy. MC fulfills the power balance requirement. With NDS, the infinite solution space becomes finite. Furthermore, a same optimum solution can be repeatedly reached. Effectiveness of NDS is demonstrated with three examples and the solutions were compared with previously published results. Test results show that the proposed method is simple, robust, and more effective than many other previously developed algorithms.
Shuttle bit rate synchronizer. [signal to noise ratios and error analysis
Huey, D. C.; Fultz, G. L.
1974-01-01
A shuttle bit rate synchronizer brassboard unit was designed, fabricated, and tested, which meets or exceeds the contractual specifications. The bit rate synchronizer operates at signal-to-noise ratios (in a bit rate bandwidth) down to -5 dB while exhibiting less than 0.6 dB bit error rate degradation. The mean acquisition time was measured to be less than 2 seconds. The synchronizer is designed around a digital data transition tracking loop whose phase and data detectors are integrate-and-dump filters matched to the Manchester encoded bits specified. It meets the reliability (no adjustments or tweaking) and versatility (multiple bit rates) of the shuttle S-band communication system through an implementation which is all digital after the initial stage of analog AGC and A/D conversion.
Attitude determination for small satellites using GPS signal-to-noise ratio
Peters, Daniel
An embedded system for GPS-based attitude determination (AD) using signal-to-noise (SNR) measurements was developed for CubeSat applications. The design serves as an evaluation testbed for conducting ground based experiments using various computational methods and antenna types to determine the optimum AD accuracy. Raw GPS data is also stored to non-volatile memory for downloading and post analysis. Two low-power microcontrollers are used for processing and to display information on a graphic screen for real-time performance evaluations. A new parallel inter-processor communication protocol was developed that is faster and uses less power than existing standard protocols. A shorted annular patch (SAP) antenna was fabricated for the initial ground-based AD experiments with the testbed. Static AD estimations with RMS errors in the range of 2.5° to 4.8° were achieved over a range of off-zenith attitudes.
Signal-to-noise analysis of a birefringent spectral zooming imaging spectrometer
Li, Jie; Zhang, Xiaotong; Wu, Haiying; Qi, Chun
2018-05-01
Study of signal-to-noise ratio (SNR) of a novel spectral zooming imaging spectrometer (SZIS) based on two identical Wollaston prisms is conducted. According to the theory of radiometry and Fourier transform spectroscopy, we deduce the theoretical equations of SNR of SZIS in spectral domain with consideration of the incident wavelength and the adjustable spectral resolution. An example calculation of SNR of SZIS is performed over 400-1000 nm. The calculation results indicate that SNR with different spectral resolutions of SZIS can be optionally selected by changing the spacing between the two identical Wollaston prisms. This will provide theoretical basis for the design, development and engineering of the developed imaging spectrometer for broad spectrum and SNR requirements.
Miles, Jeffrey Hilton
2010-01-01
Combustion noise from turbofan engines has become important, as the noise from sources like the fan and jet are reduced. An aligned and un-aligned coherence technique has been developed to determine a threshold level for the coherence and thereby help to separate the coherent combustion noise source from other noise sources measured with far-field microphones. This method is compared with a statistics based coherence threshold estimation method. In addition, the un-aligned coherence procedure at the same time also reveals periodicities, spectral lines, and undamped sinusoids hidden by broadband turbofan engine noise. In calculating the coherence threshold using a statistical method, one may use either the number of independent records or a larger number corresponding to the number of overlapped records used to create the average. Using data from a turbofan engine and a simulation this paper shows that applying the Fisher z-transform to the un-aligned coherence can aid in making the proper selection of samples and produce a reasonable statistics based coherence threshold. Examples are presented showing that the underlying tonal and coherent broad band structure which is buried under random broadband noise and jet noise can be determined. The method also shows the possible presence of indirect combustion noise. Copyright 2011 Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America.
Random resampling masks: a non-Bayesian one-shot strategy for noise reduction in digital holography.
Bianco, V; Paturzo, M; Memmolo, P; Finizio, A; Ferraro, P; Javidi, B
2013-03-01
Holographic imaging may become severely degraded by a mixture of speckle and incoherent additive noise. Bayesian approaches reduce the incoherent noise, but prior information is needed on the noise statistics. With no prior knowledge, one-shot reduction of noise is a highly desirable goal, as the recording process is simplified and made faster. Indeed, neither multiple acquisitions nor a complex setup are needed. So far, this result has been achieved at the cost of a deterministic resolution loss. Here we propose a fast non-Bayesian denoising method that avoids this trade-off by means of a numerical synthesis of a moving diffuser. In this way, only one single hologram is required as multiple uncorrelated reconstructions are provided by random complementary resampling masks. Experiments show a significant incoherent noise reduction, close to the theoretical improvement bound, resulting in image-contrast improvement. At the same time, we preserve the resolution of the unprocessed image.
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
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.
Reactor dynamics experiment of N.S. Mutsu using pseudo random signal. 1
International Nuclear Information System (INIS)
Hayashi, Koji; Nabeshima, Kunihiko; Shinohara, Yoshikuni; Shimazaki, Junya; Inoue, Kimihiko; Ochiai, Masaaki.
1993-10-01
In order to investigate dynamics of the reactor plant of the nuclear ship Mutsu, reactor noise experiments using pseudo random binary sequences (PRBS) have been planned, and a preliminary experiment was performed on March 4, 1991 in the first experimental navigation with the aim of checking the experimental procedures and conditions. The experiments using both reactivity and load disturbances were performed at 70 % of reactor power and under a quiet sea condition. Each PRBS was applied by manual operation of the control rod or the main steam valve. Various signals of the plant responses and of the acceleration of ship motion were measured. From the results obtained, we confirmed that (1) the procedures and experimental conditions determined prior to the experiment were suitable for performing the PRBS experiments, (2) when the PRBS disturbances were applied, the plant state remained quite stable, and (3) the quality of the measured data is adequate for the purpose of dynamics analysis. This paper summarizes the planning and preparation of the experiment, the instruction for the experiment and logs, the data recording conditions, recorded signal wave forms and the results of power spectral analysis. (author)
Data-driven gating in PET: Influence of respiratory signal noise on motion resolution.
Büther, Florian; Ernst, Iris; Frohwein, Lynn Johann; Pouw, Joost; Schäfers, Klaus Peter; Stegger, Lars
2018-05-21
Data-driven gating (DDG) approaches for positron emission tomography (PET) are interesting alternatives to conventional hardware-based gating methods. In DDG, the measured PET data themselves are utilized to calculate a respiratory signal, that is, subsequently used for gating purposes. The success of gating is then highly dependent on the statistical quality of the PET data. In this study, we investigate how this quality determines signal noise and thus motion resolution in clinical PET scans using a center-of-mass-based (COM) DDG approach, specifically with regard to motion management of target structures in future radiotherapy planning applications. PET list mode datasets acquired in one bed position of 19 different radiotherapy patients undergoing pretreatment [ 18 F]FDG PET/CT or [ 18 F]FDG PET/MRI were included into this retrospective study. All scans were performed over a region with organs (myocardium, kidneys) or tumor lesions of high tracer uptake and under free breathing. Aside from the original list mode data, datasets with progressively decreasing PET statistics were generated. From these, COM DDG signals were derived for subsequent amplitude-based gating of the original list mode file. The apparent respiratory shift d from end-expiration to end-inspiration was determined from the gated images and expressed as a function of signal-to-noise ratio SNR of the determined gating signals. This relation was tested against additional 25 [ 18 F]FDG PET/MRI list mode datasets where high-precision MR navigator-like respiratory signals were available as reference signal for respiratory gating of PET data, and data from a dedicated thorax phantom scan. All original 19 high-quality list mode datasets demonstrated the same behavior in terms of motion resolution when reducing the amount of list mode events for DDG signal generation. Ratios and directions of respiratory shifts between end-respiratory gates and the respective nongated image were constant over all
Suliman, Mohamed Abdalla Elhag; Ballal, Tarig; Kammoun, Abla; Alnaffouri, Tareq Y.
2016-01-01
In this supplementary appendix we provide proofs and additional simulation results that complement the paper (constrained perturbation regularization approach for signal estimation using random matrix theory).
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.
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.
Errors due to random noise in velocity measurement using incoherent-scatter radar
Directory of Open Access Journals (Sweden)
P. J. S. Williams
1996-12-01
Full Text Available The random-noise errors involved in measuring the Doppler shift of an 'incoherent-scatter' spectrum are predicted theoretically for all values of Te/Ti from 1.0 to 3.0. After correction has been made for the effects of convolution during transmission and reception and the additional errors introduced by subtracting the average of the background gates, the rms errors can be expressed by a simple semi-empirical formula. The observed errors are determined from a comparison of simultaneous EISCAT measurements using an identical pulse code on several adjacent frequencies. The plot of observed versus predicted error has a slope of 0.991 and a correlation coefficient of 99.3%. The prediction also agrees well with the mean of the error distribution reported by the standard EISCAT analysis programme.
Lifting Transit Signals from the Kepler Noise Floor. I. Discovery of a Warm Neptune
Kunimoto, Michelle; Matthews, Jaymie M.; Rowe, Jason F.; Hoffman, Kelsey
2018-01-01
Light curves from the 4-year Kepler exoplanet hunting mission have been searched for transits by NASA’s Kepler team and others, but there are still important discoveries to be made. We have searched the light curves of 400 Kepler Objects of Interest (KOIs) to find transit signals down to signal-to-noise ratio (S/N) ∼ 6, which is under the limit of S/N ∼ 7.1 that has been commonly adopted as a strict threshold to distinguish between a transit candidate and false alarm. We detect four new and convincing planet candidates ranging in radius from near-Mercury-size to slightly larger than Neptune. We highlight the discovery of KOI-408.05 (period = 637 days; radius = 4.9 R ⊕ incident flux = 0.6 S ⊕), a planet candidate within its host star’s Habitable Zone. We dub this planet a “warm Neptune,” a likely volatile-rich world that deserves closer inspection. KOI-408.05 joins 21 other confirmed and candidate planets in the current Kepler sample with semimajor axes a > 1.4 au. These discoveries are significant as a demonstration that the S/N threshold for detection used by the Kepler project is open to debate.
Fractal properties of background noise and target signal enhancement using CSEM data
Benavides, Alfonso; Everett, Mark E.; Pierce, Carl; Nguyen, Cam
2003-09-01
Controlled-source electromagnetic (CSEM) spatial profiles and 2-D conductivity maps were obtained on the Brazos Valley, TX floodplain to study the fractal statistics of geological signals and effects of man-made conductive targets using Geonics EM34, EM31 and EM63. Using target-free areas, a consistent power-law power spectrum (|A(k)| ~ k ^-β) for the profiles was found with β values typical of fractional Brownian motion (fBm). This means that the spatial variation of conductivity does not correspond to Gaussian statistics, where there are spatial correlations at different scales. The presence of targets tends to flatten the power-law power spectrum (PS) at small wavenumbers. Detection and localization of targets can be achieved using short-time Fourier transform (STFT). The presence of targets is enhanced because the signal energy is spread to higher wavenumbers (small scale numbers) in the positions occupied by the targets. In the case of poor spatial sampling or small amount of data, the information available from the power spectrum is not enough to separate spatial correlations from target signatures. Advantages are gained by using the spatial correlations of the fBm in order to reject the background response, and to enhance the signals from highly conductive targets. This approach was tested for the EM31 using a pre-processing step that combines apparent conductivity readings from two perpendicular transmitter-receiver orientations at each station. The response obtained using time-domain CSEM is influence to a lesser degree by geological noise and the target response can be processed to recover target features. The homotopy method is proposed to solve the inverse problem using a set of possible target models and a dynamic library of responses used to optimize the starting model.
Effects of the physiological parameters on the signal-to-noise ratio of single myoelectric channel
Directory of Open Access Journals (Sweden)
Zhang YT
2007-08-01
Full Text Available Abstract Background An important measure of the performance of a myoelectric (ME control system for powered artificial limbs is the signal-to-noise ratio (SNR at the output of ME channel. However, few studies illustrated the neuron-muscular interactive effects on the SNR at ME control channel output. In order to obtain a comprehensive understanding on the relationship between the physiology of individual motor unit and the ME control performance, this study investigates the effects of physiological factors on the SNR of single ME channel by an analytical and simulation approach, where the SNR is defined as the ratio of the mean squared value estimation at the channel output and the variance of the estimation. Methods Mathematical models are formulated based on three fundamental elements: a motoneuron firing mechanism, motor unit action potential (MUAP module, and signal processor. Myoelectric signals of a motor unit are synthesized with different physiological parameters, and the corresponding SNR of single ME channel is numerically calculated. Effects of physiological multi factors on the SNR are investigated, including properties of the motoneuron, MUAP waveform, recruitment order, and firing pattern, etc. Results The results of the mathematical model, supported by simulation, indicate that the SNR of a single ME channel is associated with the voluntary contraction level. We showed that a model-based approach can provide insight into the key factors and bioprocess in ME control. The results of this modelling work can be potentially used in the improvement of ME control performance and for the training of amputees with powered prostheses. Conclusion The SNR of single ME channel is a force, neuronal and muscular property dependent parameter. The theoretical model provides possible guidance to enhance the SNR of ME channel by controlling physiological variables or conscious contraction level.
GPS Signal Offset Detection and Noise Strength Estimation in a Parallel Kalman Filter Algorithm
National Research Council Canada - National Science Library
Vanek, Barry
1999-01-01
.... The variance of the noise process is estimated and provided to the second algorithm, a parallel Kalman filter structure, which then adapts to changes in the real-world measurement noise strength...
International Nuclear Information System (INIS)
Zhang Zhuhong; Fan Diayuan
1993-01-01
The criterion for obtaining compressed chirp pulses with high signal-to-noise ratio is the shape of the power spectrum, a chirp pulse of Gaussian shaped power spectrum without modulation is needed in CPA system to get the clean compressed pulses. 4 refs., 2 figs
Influence of Signal-to-Noise Ratio and Point Spread Function on Limits of Super-Resolution
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
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.
DEFF Research Database (Denmark)
Deng, Lei; Pang, Xiaodan; Zhang, Xu
2013-01-01
We report on the transmission of 8 Gb/s 0 dB PAPR 16QAM-OFDM W-band (75-110 GHz) signals over 22.8km SMF without phase noise compensation by using a phase modulator in the optical heterodyne up-convertor....
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.
Fractals in Power Reactor Noise
International Nuclear Information System (INIS)
Aguilar Martinez, O.
1994-01-01
In this work the non- lineal dynamic problem of power reactor is analyzed using classic concepts of fractal analysis as: attractors, Hausdorff-Besikovics dimension, phase space, etc. A new non-linear problem is also analyzed: the discrimination of chaotic signals from random neutron noise signals and processing for diagnosis purposes. The advantages of a fractal analysis approach in the power reactor noise are commented in details
Sun, Jin; Xu, Xiaosu; Liu, Yiting; Zhang, Tao; Li, Yao
2016-07-12
In order to reduce the influence of fiber optic gyroscope (FOG) random drift error on inertial navigation systems, an improved auto regressive (AR) model is put forward in this paper. First, based on real-time observations at each restart of the gyroscope, the model of FOG random drift can be established online. In the improved AR model, the FOG measured signal is employed instead of the zero mean signals. Then, the modified Sage-Husa adaptive Kalman filter (SHAKF) is introduced, which can directly carry out real-time filtering on the FOG signals. Finally, static and dynamic experiments are done to verify the effectiveness. The filtering results are analyzed with Allan variance. The analysis results show that the improved AR model has high fitting accuracy and strong adaptability, and the minimum fitting accuracy of single noise is 93.2%. Based on the improved AR(3) model, the denoising method of SHAKF is more effective than traditional methods, and its effect is better than 30%. The random drift error of FOG is reduced effectively, and the precision of the FOG is improved.
International Nuclear Information System (INIS)
Dudetskiy, V Yu; Lariontsev, E G; Chekina, S N
2014-01-01
The effect of pump noise on the synchronisation of selfmodulation oscillations in a solid-state ring laser with periodic pump modulation is studied numerically and experimentally. It is found that, in contrast to desynchronisation that usually occurs under action of noise in the case of 1/1 synchronisation of self-oscillations by a periodic signal, the effect of noise on 1/2 synchronisation may be positive, namely, at a sufficiently low intensity, pump noise is favourable for synchronisation of self-oscillations, for narrowing of their spectrum, and for increasing the signal-to-noise ratio. (lasers)
Zhu, Lili; Wu, Jingping; Lin, Guimin; Hu, Liangjun; Li, Hui
2016-10-01
With high spatial resolution of ultrasonic location and high sensitivity of optical detection, ultrasound-modulated optical tomography (UOT) is a promising noninvasive biological tissue imaging technology. In biological tissue, the ultrasound-modulated light signals are very weak and are overwhelmed by the strong unmodulated light signals. It is a difficulty and key to efficiently pick out the weak modulated light from strong unmodulated light in UOT. Under the effect of an ultrasonic field, the scattering light intensity presents a periodic variation as the ultrasonic frequency changes. So the modulated light signals would be escape from the high unmodulated light signals, when the modulated light signals and the ultrasonic signal are processed cross correlation operation by a lock-in amplifier and without a chopper. Experimental results indicated that the signal-to-noise ratio of UOT is significantly improved by a lock-in amplifier, and the higher the repetition frequency of pulsed ultrasonic wave, the better the signal-to-noise ratio of UOT.
Ji, Yanju; Li, Dongsheng; Yu, Mingmei; Wang, Yuan; Wu, Qiong; Lin, Jun
2016-05-01
The ground electrical source airborne transient electromagnetic system (GREATEM) on an unmanned aircraft enjoys considerable prospecting depth, lateral resolution and detection efficiency, etc. In recent years it has become an important technical means of rapid resources exploration. However, GREATEM data are extremely vulnerable to stationary white noise and non-stationary electromagnetic noise (sferics noise, aircraft engine noise and other human electromagnetic noises). These noises will cause degradation of the imaging quality for data interpretation. Based on the characteristics of the GREATEM data and major noises, we propose a de-noising algorithm utilizing wavelet threshold method and exponential adaptive window width-fitting. Firstly, the white noise is filtered in the measured data using the wavelet threshold method. Then, the data are segmented using data window whose step length is even logarithmic intervals. The data polluted by electromagnetic noise are identified within each window based on the discriminating principle of energy detection, and the attenuation characteristics of the data slope are extracted. Eventually, an exponential fitting algorithm is adopted to fit the attenuation curve of each window, and the data polluted by non-stationary electromagnetic noise are replaced with their fitting results. Thus the non-stationary electromagnetic noise can be effectively removed. The proposed algorithm is verified by the synthetic and real GREATEM signals. The results show that in GREATEM signal, stationary white noise and non-stationary electromagnetic noise can be effectively filtered using the wavelet threshold-exponential adaptive window width-fitting algorithm, which enhances the imaging quality.
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.
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.
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.
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.
Reddy, C. P.; Gupta, S. C.
1973-01-01
An all digital phase locked loop which tracks the phase of the incoming sinusoidal signal once per carrier cycle is proposed. The different elements and their functions and the phase lock operation are explained in detail. The nonlinear difference equations which govern the operation of the digital loop when the incoming signal is embedded in white Gaussian noise are derived, and a suitable model is specified. The performance of the digital loop is considered for the synchronization of a sinusoidal signal. For this, the noise term is suitably modelled which allows specification of the output probabilities for the two level quantizer in the loop at any given phase error. The loop filter considered increases the probability of proper phase correction. The phase error states in modulo two-pi forms a finite state Markov chain which enables the calculation of steady state probabilities, RMS phase error, transient response and mean time for cycle skipping.
Energy Technology Data Exchange (ETDEWEB)
Liu, Jinzhen; Li, Gang; Lin, Ling, E-mail: linling@tju.edu.cn [State Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin, People' s Republic of China, and Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, Tianjin University, Tianjin (China); Qiao, Xiaoyan [College of Physics and Electronic Engineering, Shanxi University, Shanxi (China); Wang, Mengjun [School of Information Engineering, Hebei University of Technology, Tianjin (China); Zhang, Weibo [Institute of Acupuncture and Moxibustion China Academy of Chinese Medical Sciences, Beijing (China)
2014-05-15
The stability and signal to noise ratio (SNR) of the current source circuit are the important factors contributing to enhance the accuracy and sensitivity in bioimpedance measurement system. In this paper we propose a new differential Howland topology current source and evaluate its output characters by simulation and actual measurement. The results include (1) the output current and impedance in high frequencies are stabilized after compensation methods. And the stability of output current in the differential current source circuit (DCSC) is 0.2%. (2) The output impedance of two current circuits below the frequency of 200 KHz is above 1 MΩ, and below 1 MHz the output impedance can arrive to 200 KΩ. Then in total the output impedance of the DCSC is higher than that of the Howland current source circuit (HCSC). (3) The SNR of the DCSC are 85.64 dB and 65 dB in the simulation and actual measurement with 10 KHz, which illustrates that the DCSC effectively eliminates the common mode interference. (4) The maximum load in the DCSC is twice as much as that of the HCSC. Lastly a two-dimensional phantom electrical impedance tomography is well reconstructed with the proposed HCSC. Therefore, the measured performance shows that the DCSC can significantly improve the output impedance, the stability, the maximum load, and the SNR of the measurement system.
Signal and Noise Delineation for Prompt-Gamma Detection during Hadrontherapy
International Nuclear Information System (INIS)
Chin, M.-P.W.; Cerutti, F.; Ferrari, A.; Garcia-Ortega, P.; Sala, P.-R.
2013-06-01
Proton and carbon therapies of a human brain were simulated using FLUKA, with particular emphasis on treatment monitoring using the prompt gamma method where activities of the source proton/carbon in the patient's body are to be extracted from the positional profile of exit photons. Tissue heterogeneity ranging from hydrogen to zinc was represented in a VIP-Man anthropomorphic voxel phantom. Each photon exiting the head was scored with ancestry attributes such as the particle type of its parent, the originating collision type and site. These data, not accessible via physical detectors, were analysed to characterise the escaping photons, delineating signal from noise according to the gamma origin and scatter history. Combinations of energy, geometry, time and angle filters, aided by ray-tracing, were studied for the optimal compromise between a sufficiently featured exit profile and a statistically adequate count. These will be put in context with ongoing research in the field; our perspective for the prompt gamma method will be discussed in detail. (authors)
Signal-noise ratio of MR spectroscopy in the central gland of prostate
International Nuclear Information System (INIS)
Tong Yanjun; Wang Xiaoying; Li Feiyu; Jiang Xuexiang
2007-01-01
Objective: To analyze the signal to noise ratio (SNR) of the MRS of the prostate central gland, and study its relationship with the pathology of the lesions. Methods: Eighteen patients who underwent transurethral resection of prostate (TURP) for benign prostate hyperplasia (BPH) were enrolled in this study. They were divided into three groups according to the pathological findings: 7 cases of glandular-BPH (GBPH), 7 cases of stromal-BPH (SBPH) and 5 cases of incidentally detected prostate carcinoma (IDPC). The voxels in the central glands with SNR ≥5 and SNR < 5 were counted, and the relationship between the percentage of voxel with SNR < 5 and pathology was analyzed. Results: In the 18 cases, the total number of voxels measured in the regions of interest was 3632, and the voxels with SNR≥5 and SNR < 5 were 1579 (the percentage is 43%) and 1873, respectively. The percentage of voxels with SNR < 5 in SBPH group (67.6 ± 21.8)% was statistically higher than that in GBPH (37.1±14.5)% and IDPC (39.9±18.8)%. The difference between the group of GBPH and IDPC was not statistically significant. Conclusion: More than half of the voxels in the central gland could not be reliably analyzed in the prostate MRS examination because of its low SNR, especially in the case of SBPH. (authors)
Statistical process control: separating signal from noise in emergency department operations.
Pimentel, Laura; Barrueto, Fermin
2015-05-01
Statistical process control (SPC) is a visually appealing and statistically rigorous methodology very suitable to the analysis of emergency department (ED) operations. We demonstrate that the control chart is the primary tool of SPC; it is constructed by plotting data measuring the key quality indicators of operational processes in rationally ordered subgroups such as units of time. Control limits are calculated using formulas reflecting the variation in the data points from one another and from the mean. SPC allows managers to determine whether operational processes are controlled and predictable. We review why the moving range chart is most appropriate for use in the complex ED milieu, how to apply SPC to ED operations, and how to determine when performance improvement is needed. SPC is an excellent tool for operational analysis and quality improvement for these reasons: 1) control charts make large data sets intuitively coherent by integrating statistical and visual descriptions; 2) SPC provides analysis of process stability and capability rather than simple comparison with a benchmark; 3) SPC allows distinction between special cause variation (signal), indicating an unstable process requiring action, and common cause variation (noise), reflecting a stable process; and 4) SPC keeps the focus of quality improvement on process rather than individual performance. Because data have no meaning apart from their context, and every process generates information that can be used to improve it, we contend that SPC should be seriously considered for driving quality improvement in emergency medicine. Copyright © 2015 Elsevier Inc. All rights reserved.
Large signal-to-noise ratio quantification in MLE for ARARMAX models
Zou, Yiqun; Tang, Xiafei
2014-06-01
It has been shown that closed-loop linear system identification by indirect method can be generally transferred to open-loop ARARMAX (AutoRegressive AutoRegressive Moving Average with eXogenous input) estimation. For such models, the gradient-related optimisation with large enough signal-to-noise ratio (SNR) can avoid the potential local convergence in maximum likelihood estimation. To ease the application of this condition, the threshold SNR needs to be quantified. In this paper, we build the amplitude coefficient which is an equivalence to the SNR and prove the finiteness of the threshold amplitude coefficient within the stability region. The quantification of threshold is achieved by the minimisation of an elaborately designed multi-variable cost function which unifies all the restrictions on the amplitude coefficient. The corresponding algorithm based on two sets of physically realisable system input-output data details the minimisation and also points out how to use the gradient-related method to estimate ARARMAX parameters when local minimum is present as the SNR is small. Then, the algorithm is tested on a theoretical AutoRegressive Moving Average with eXogenous input model for the derivation of the threshold and a gas turbine engine real system for model identification, respectively. Finally, the graphical validation of threshold on a two-dimensional plot is discussed.
International Nuclear Information System (INIS)
Sakairi, M.; Shimoyama, Y.; Nagasawa, D.
2008-01-01
A new type of electrochemical random signal (electrochemical noise) analysis technique was applied to localized corrosion of anodic oxide film formed 1100 aluminum alloy in 0.5 kmol/m 3 H 3 BO 4 /0.05 kmol/m 3 Na 2 B 4 O 7 with 0.01 kmol/m 3 NaCl. The effect of anodic oxide film structure, barrier type, porous type, and composite type on galvanic corrosion resistance was also examined. Before localized corrosion started, incubation period for pitting corrosion, both current and potential slightly change as initial value with time. The incubation period of porous type anodic oxide specimens are longer than that of barrier type anodic oxide specimens. While pitting corrosion, the current and potential were changed with fluctuations and the potential and the current fluctuations show a good correlation. The records of the current and potential were processed by calculating the power spectrum density (PSD) by the Fast Fourier Transform (FFT) method. The potential and current PSD decrease with increasing frequency, and the slopes are steeper than or equal to minus one (-1). This technique allows observation of electrochemical impedance changes during localized corrosion
Bahaz, Mohamed; Benzid, Redha
2018-03-01
Electrocardiogram (ECG) signals are often contaminated with artefacts and noises which can lead to incorrect diagnosis when they are visually inspected by cardiologists. In this paper, the well-known discrete Fourier series (DFS) is re-explored and an efficient DFS-based method is proposed to reduce contribution of both baseline wander (BW) and powerline interference (PLI) noises in ECG records. In the first step, the determination of the exact number of low frequency harmonics contributing in BW is achieved. Next, the baseline drift is estimated by the sum of all associated Fourier sinusoids components. Then, the baseline shift is discarded efficiently by a subtraction of its approximated version from the original biased ECG signal. Concerning the PLI, the subtraction of the contributing harmonics calculated in the same manner reduces efficiently such type of noise. In addition of visual quality results, the proposed algorithm shows superior performance in terms of higher signal-to-noise ratio and smaller mean square error when faced to the DCT-based algorithm.
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.
The random signal generator of imitated nuclear radiation pulse
International Nuclear Information System (INIS)
Li Dongcang; Yang Lei; Yuan Shulin; Yang Yinghui; Zang Fujia
2007-01-01
Based in pseudo-random uniformity number, it produces random numbers of Gaussian distribution and exponential distribution by arithmetic. The hardware is the single-chip microcomputer of 89C51. Program language makes use of Keil C. The output pulse amplitude is Gaussian distribution, exponential distribution or uniformity distribution. Likewise, it has two mode or upwards two. The time alternation of output pulse is both periodic and exponential distribution. The generator has achieved output control of multi-mode distribution, imitated random characteristic of nuclear pulse in amplitude and in time. (authors)
Detection of a random signal in a multi-channel environment: a performance study
International Nuclear Information System (INIS)
Frenzel, K.Z.
1986-01-01
Performance of the optimal (likelihood ratio) test and suboptimal tests, including the normalized cross correlator and two energy detectors are compared for problems involving non-gaussian as well as gaussian statistics. Also, optimal one-channel processing is compared to optimal two-channel processing for equivalent total signal-to-noise ratios. Receiver operator characteristics (ROC) curves obtained by a combination of simulation and analytic methods are used to evaluate the performance of the processors. It was found that two-channel processing helps the detection performance the most when the noise levels are uncertain. This was true for all signal and noise densities studied. In cases where the noise levels and channel attenuations are known, or when only the attenuations are uncertain, the performance using optimal one-channel processing was close to that found using optimal two-channel processing. When comparing optimal processors to the three suboptimal processors, it was found that when the noise level in each channel is very uncertain, the performance of the normalized cross correlator is much closer to the optimal than that of either of the energy detectors. If, however, the noise levels are know with a fair degree of certainty, the performance of the energy detectors improves considerably, in some cases approaching the optimal performance
Detection Performance of Signals in Dependent Noise From a Gaussian Mixture Uncertainty Class
National Research Council Canada - National Science Library
Gerlach, K
1998-01-01
... (correlated) multivariate noise from a Gaussian mixture uncertainty class. This uncertainty class is defined using upper and lower bounding functions on the univariate Gaussian mixing distribution function...
A Method of Reducing Random Drift in the Combined Signal of an Array of Inertial Sensors
2015-09-30
stability of the collective output, Bayard et al, US Patent 6,882,964. The prior art methods rely upon the use of Kalman filtering and averaging...including scale-factor errors, quantization effects, temperature effects, random drift, and additive noise. A comprehensive account of all of these
International Nuclear Information System (INIS)
Narayan, P.; Suri, S.; Choudhary, S.R.
2001-01-01
In most general definition, noise in an image, is any variation that represents a deviation from truth. Noise sources in MRI can be systematic or random and statistical in nature. Data processing algorithms that smooth and enhance the edges by non-linear intensity assignments among other factors can affect the distribution of statistical noise. The SNR and image uniformity depends on the various parameters of NMR imaging system (viz. General system calibration, Gain coil tuning, AF shielding, coil loading, image processing and scan parameters like TE, TR, interslice distance, slice thickness, pixel size and matrix size). A study on SNR and image uniformity have been performed using standard head AF coil with different TR and the estimates of their variation are presented. A comparison between different techniques has also been evaluated using standard protocol of the Siemens Magnetom Vision Plus MRI system
Physical-layer security analysis of PSK quantum-noise randomized cipher in optically amplified links
Jiao, Haisong; Pu, Tao; Xiang, Peng; Zheng, Jilin; Fang, Tao; Zhu, Huatao
2017-08-01
The quantitative security of quantum-noise randomized cipher (QNRC) in optically amplified links is analyzed from the perspective of physical-layer advantage. Establishing the wire-tap channel models for both key and data, we derive the general expressions of secrecy capacities for the key against ciphertext-only attack and known-plaintext attack, and that for the data, which serve as the basic performance metrics. Further, the maximal achievable secrecy rate of the system is proposed, under which secrecy of both the key and data is guaranteed. Based on the same framework, the secrecy capacities of various cases can be assessed and compared. The results indicate perfect secrecy is potentially achievable for data transmission, and an elementary principle of setting proper number of photons and bases is given to ensure the maximal data secrecy capacity. But the key security is asymptotically perfect, which tends to be the main constraint of systemic maximal secrecy rate. Moreover, by adopting cascaded optical amplification, QNRC can realize long-haul transmission with secure rate up to Gb/s, which is orders of magnitude higher than the perfect secrecy rates of other encryption systems.
Surface detection performance evaluation of pseudo-random noise continuous wave laser radar
Mitev, Valentin; Matthey, Renaud; Pereira do Carmo, Joao
2017-11-01
A number of space missions (including in the ESA Exploration Programme) foreseen a use of laser radar sensor (or lidar) for determination of range between spacecrafts or between spacecraft and ground surface (altimetry). Such sensors need to be compact, robust and power efficient, at the same time with high detection performance. These requirements can be achieved with a Pseudo-Random Noise continuous wave lidar (PRN cw lidar). Previous studies have pointed to the advantages of this lidar with respect to space missions, but they also identified its limitations in high optical background. The progress of the lasers and the detectors in the near IR spectral range requires a re-evaluation of the PRN cw lidar potential. Here we address the performances of this lidar for surface detection (altimetry) in planetary missions. The evaluation is based on the following system configuration: (i) A cw fiber amplifier as lidar transmitter. The seeding laser exhibits a single-frequency spectral line, with subsequent amplitude modulation. The fiber amplifier allows high output power level, keeping the spectral characteristics and the modulation of the seeding light input. (ii) An avalanche photodiode in photon counting detection; (iii) Measurement scenarios representative for Earth, Mercury and Mars.
Directory of Open Access Journals (Sweden)
Hongtao Yang
2018-01-01
Full Text Available This paper proposes a novel strong tracking filter (STF, which is suitable for dealing with the filtering problem of nonlinear systems when the following cases occur: that is, the constructed model does not match the actual system, the measurements have the one-step random delay, and the process and measurement noises are correlated at the same epoch. Firstly, a framework of decoupling filter (DF based on equivalent model transformation is derived. Further, according to the framework of DF, a new extended Kalman filtering (EKF algorithm via using first-order linearization approximation is developed. Secondly, the computational process of the suboptimal fading factor is derived on the basis of the extended orthogonality principle (EOP. Thirdly, the ultimate form of the proposed STF is obtained by introducing the suboptimal fading factor into the above EKF algorithm. The proposed STF can automatically tune the suboptimal fading factor on the basis of the residuals between available and predicted measurements and further the gain matrices of the proposed STF tune online to improve the filtering performance. Finally, the effectiveness of the proposed STF has been proved through numerical simulation experiments.
Conditional Random Fields for Morphological Analysis of Wireless ECG Signals
Natarajan, Annamalai; Gaiser, Edward; Angarita, Gustavo; Malison, Robert; Ganesan, Deepak; Marlin, Benjamin
2014-01-01
Thanks to advances in mobile sensing technologies, it has recently become practical to deploy wireless electrocardiograph sensors for continuous recording of ECG signals. This capability has diverse applications in the study of human health and behavior, but to realize its full potential, new computational tools are required to effectively deal with the uncertainty that results from the noisy and highly non-stationary signals collected using these devices. In this work, we present a novel app...
International Nuclear Information System (INIS)
Adzhemyan, L.Ts.; Vasil'ev, A.N.; Pis'mak, Yu.M.
1988-01-01
The investigation of the infrared behavior of the propagator of a light wave in a randomly inhomogeneous medium with massless Gaussian noise is continued. The infrared representation of the propagator for correlation function D varphi (k)∼k -2 is generalized to the case of an arbitrary power-law noise correlation function is rigorously established in the first two orders of the infrared asymptotic behavior by construction of a suitable R operation. As a consequence, the results are generalized to the case of critical opalescence, when D varphi (k)∼k -2+η , where η ∼ 0.03 is the Fisher index
Random noise effects in pulse-mode digital multilayer neural networks.
Kim, Y C; Shanblatt, M A
1995-01-01
A pulse-mode digital multilayer neural network (DMNN) based on stochastic computing techniques is implemented with simple logic gates as basic computing elements. The pulse-mode signal representation and the use of simple logic gates for neural operations lead to a massively parallel yet compact and flexible network architecture, well suited for VLSI implementation. Algebraic neural operations are replaced by stochastic processes using pseudorandom pulse sequences. The distributions of the results from the stochastic processes are approximated using the hypergeometric distribution. Synaptic weights and neuron states are represented as probabilities and estimated as average pulse occurrence rates in corresponding pulse sequences. A statistical model of the noise (error) is developed to estimate the relative accuracy associated with stochastic computing in terms of mean and variance. Computational differences are then explained by comparison to deterministic neural computations. DMNN feedforward architectures are modeled in VHDL using character recognition problems as testbeds. Computational accuracy is analyzed, and the results of the statistical model are compared with the actual simulation results. Experiments show that the calculations performed in the DMNN are more accurate than those anticipated when Bernoulli sequences are assumed, as is common in the literature. Furthermore, the statistical model successfully predicts the accuracy of the operations performed in the DMNN.
Microwave noise detection of a quantum dot with stub impedance matching
Hasler, Thomas
2016-01-01
Noise is defined as random fluctuations of a signal in time. The fundamental requirement for noise is some sort of randomness. Noise is well-known and infamous to every experimentalist - whether he is working in the field of electronics, optics, acoustics or anywhere else - since such fluctuations are inherent and unavoidable in many systems. For most of us, the word noise has a negative connotation. It is considered to be an unwanted disturbance superposed on a useful signal, which tend...
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.
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.
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.
Marshburn, Thomas; Cole, Richard; Ebert, Doug; Bauer, Pete
2014-01-01
Introduction: Evaluation of heart, lung, and bowel sounds is routinely performed with the use of a stethoscope to help detect a broad range of medical conditions. Stethoscope acquired information is even more valuable in a resource limited environments such as the International Space Station (ISS) where additional testing is not available. The high ambient noise level aboard the ISS poses a specific challenge to auscultation by stethoscope. An electronic stethoscope's ambient noise-reduction, greater sound amplification, recording capabilities, and sound visualization software may be an advantage to a conventional stethoscope in this environment. Methods: A single operator rated signal-to-noise quality from a conventional stethoscope (Littman 2218BE) and an electronic stethoscope (Litmann 3200). Borborygmi, pulmonic, and cardiac sound quality was ranked with both stethoscopes. Signal-to-noise rankings were preformed on a 1 to 10 subjective scale with 1 being inaudible, 6 the expected quality in an emergency department, 8 the expected quality in a clinic, and 10 the clearest possible quality. Testing took place in the Japanese Pressurized Module (JPM), Unity (Node 2), Destiny (US Lab), Tranquility (Node 3), and the Cupola of the International Space Station. All examinations were conducted at a single point in time. Results: The electronic stethoscope's performance ranked higher than the conventional stethoscope for each body sound in all modules tested. The electronic stethoscope's sound quality was rated between 7 and 10 in all modules tested. In comparison, the traditional stethoscope's sound quality was rated between 4 and 7. The signal to noise ratio of borborygmi showed the biggest difference between stethoscopes. In the modules tested, the auscultation of borborygmi was rated between 5 and 7 by the conventional stethoscope and consistently 10 by the electronic stethoscope. Discussion: This stethoscope comparison was limited to a single operator. However, we
DEFF Research Database (Denmark)
Jeppesen, Palle
1997-01-01
Noise in optical amplifiers is discussed on the basis of photons and electromagntic fields. Formulas for quantum noise from spontaneous emission, signal-spontaneous beat noise and spontaneous-spontaneous beat noise are derived.......Noise in optical amplifiers is discussed on the basis of photons and electromagntic fields. Formulas for quantum noise from spontaneous emission, signal-spontaneous beat noise and spontaneous-spontaneous beat noise are derived....
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).
International Nuclear Information System (INIS)
Lee, Z.; Rose, H.; Lehtinen, O.; Biskupek, J.; Kaiser, U.
2014-01-01
In order to achieve the highest resolution in aberration-corrected (AC) high-resolution transmission electron microscopy (HRTEM) images, high electron doses are required which only a few samples can withstand. In this paper we perform dose-dependent AC-HRTEM image calculations, and study the dependence of the signal-to-noise ratio, atom contrast and resolution on electron dose and sampling. We introduce dose-dependent contrast, which can be used to evaluate the visibility of objects under different dose conditions. Based on our calculations, we determine optimum samplings for high and low electron dose imaging conditions. - Highlights: • The definition of dose-dependent atom contrast is introduced. • The dependence of the signal-to-noise ratio, atom contrast and specimen resolution on electron dose and sampling is explored. • The optimum sampling can be determined according to different dose conditions
International Nuclear Information System (INIS)
Faiz, Wali; Gao Kun; Wu Zhao; Wei Chen-Xi; Zan Gui-Bin; Tian Yang-Chao; Bao Yuan; Zhu Pei-Ping
2017-01-01
X-ray phase-contrast imaging is one of the novel techniques, and has potential to enhance image quality and provide the details of inner structures nondestructively. In this work, we investigate quantitatively signal-to-noise ratio (SNR) of grating-based x-ray phase contrast imaging (GBPCI) system by employing angular signal radiography (ASR). Moreover, photon statistics and mechanical error that is a major source of noise are investigated in detail. Results show the dependence of SNR on the system parameters and the effects on the extracted absorption, refraction and scattering images. Our conclusions can be used to optimize the system design for upcoming practical applications in the areas such as material science and biomedical imaging. (paper)
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.
Directory of Open Access Journals (Sweden)
Pasquale Borrelli
Full Text Available In susceptibility-weighted imaging (SWI, the high resolution required to obtain a proper contrast generation leads to a reduced signal-to-noise ratio (SNR. The application of a denoising filter to produce images with higher SNR and still preserve small structures from excessive blurring is therefore extremely desirable. However, as the distributions of magnitude and phase noise may introduce biases during image restoration, the application of a denoising filter is non-trivial. Taking advantage of the potential multispectral nature of MR images, a multicomponent approach using a Non-Local Means (MNLM denoising filter may perform better than a component-by-component image restoration method. Here we present a new MNLM-based method (Multicomponent-Imaginary-Real-SWI, hereafter MIR-SWI to produce SWI images with high SNR and improved conspicuity. Both qualitative and quantitative comparisons of MIR-SWI with the original SWI scheme and previously proposed SWI restoring pipelines showed that MIR-SWI fared consistently better than the other approaches. Noise removal with MIR-SWI also provided improvement in contrast-to-noise ratio (CNR and vessel conspicuity at higher factors of phase mask multiplications than the one suggested in the literature for SWI vessel imaging. We conclude that a proper handling of noise in the complex MR dataset may lead to improved image quality for SWI data.
Saito, S.; Kaida, D.; Hattori, K.; Febriani, F.; Yoshino, C.
2011-01-01
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 inten...
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.
A Data-Driven Noise Reduction Method and Its Application for the Enhancement of Stress Wave Signals
Directory of Open Access Journals (Sweden)
Hai-Lin Feng
2012-01-01
Full Text Available Ensemble empirical mode decomposition (EEMD has been recently used to recover a signal from observed noisy data. Typically this is performed by partial reconstruction or thresholding operation. In this paper we describe an efficient noise reduction method. EEMD is used to decompose a signal into several intrinsic mode functions (IMFs. The time intervals between two adjacent zero-crossings within the IMF, called instantaneous half period (IHP, are used as a criterion to detect and classify the noise oscillations. The undesirable waveforms with a larger IHP are set to zero. Furthermore, the optimum threshold in this approach can be derived from the signal itself using the consecutive mean square error (CMSE. The method is fully data driven, and it requires no prior knowledge of the target signals. This method can be verified with the simulative program by using Matlab. The denoising results are proper. In comparison with other EEMD based methods, it is concluded that the means adopted in this paper is suitable to preprocess the stress wave signals in the wood nondestructive testing.
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
Discriminality of statistically independent Gaussian noise tokens and random tone-burst complexes
Goossens, T.L.J.; Par, van de S.L.J.D.E.; Kohlrausch, A.G.; Kollmeier, B.; Klump, G.; Hohmann, V.; Langemann, U.; Mauermann, M.; Uppenkamp, S.; Verhey, J.
2007-01-01
Hanna (1984) has shown that noise tokens with a duration of 400 ms are harder to discriminate than noise tokens of 100 ms. This is remarkable because a 400-ms stimulus potentially contains four times as much information for judging dissimilarity than the 100-ms stimulus. Apparently, the ability to
On the ability to discriminate Gaussian-noise tokens or random tone-burst complexes
Goossens, T.L.J.; Par, van de S.L.J.D.E.; Kohlrausch, A.G.
2008-01-01
This study investigated factors that influence a listeners' ability to discriminate Gaussian-noise stimuli in a same-different discrimination paradigm. The first experiment showed that discrimination ability increased with bandwidth for noise durations up to 100 ms. Duration had a nonmonotonic
Methods for surveillance of noise signals from nuclear power plants using auto power spectra
International Nuclear Information System (INIS)
Streich, M.
1988-01-01
A survey of methods for noise diagnostics applied in the nuclear power plant 'Bruno Leuschner' for surveillance of primary circuit is given. Considering a special example concept of surveillance of standard deviations is explained. (author)
Listening to the Deep: Live monitoring of ocean noise and cetacean acoustic signals
André, Michel; Van der Schaar, Mike Connor Roger Malcolm; Zaugg, Serge Alain; Houégnigan, Ludwig; Sánchez, A.M.; Castell, Joan
2011-01-01
The development and broad use of passive acoustic monitoring techniques have the potential to help assessing the large-scale influence of artificial noise on marine organisms and ecosystems. Deep-sea observatories have the potential to play a key role in understanding these recent acoustic changes. LIDO(Listening to the Deep Ocean Environment) is an international project that is allowing the real-time longterm monitoring of marine ambient noise as well as marine mammal sounds at cabled and...
Nezhadhaghighi, Mohsen Ghasemi
2017-08-01
Here, we present results of numerical simulations and the scaling characteristics of one-dimensional random fluctuations with heavy-tailed probability distribution functions. Assuming that the distribution function of the random fluctuations obeys Lévy statistics with a power-law scaling exponent, we investigate the fractional diffusion equation in the presence of μ-stable Lévy noise. We study the scaling properties of the global width and two-point correlation functions and then compare the analytical and numerical results for the growth exponent β and the roughness exponent α. We also investigate the fractional Fokker-Planck equation for heavy-tailed random fluctuations. We show that the fractional diffusion processes in the presence of μ-stable Lévy noise display special scaling properties in the probability distribution function (PDF). Finally, we numerically study the scaling properties of the heavy-tailed random fluctuations by using the diffusion entropy analysis. This method is based on the evaluation of the Shannon entropy of the PDF generated by the random fluctuations, rather than on the measurement of the global width of the process. We apply the diffusion entropy analysis to extract the growth exponent β and to confirm the validity of our numerical analysis.
Nezhadhaghighi, Mohsen Ghasemi
2017-08-01
Here, we present results of numerical simulations and the scaling characteristics of one-dimensional random fluctuations with heavy-tailed probability distribution functions. Assuming that the distribution function of the random fluctuations obeys Lévy statistics with a power-law scaling exponent, we investigate the fractional diffusion equation in the presence of μ -stable Lévy noise. We study the scaling properties of the global width and two-point correlation functions and then compare the analytical and numerical results for the growth exponent β and the roughness exponent α . We also investigate the fractional Fokker-Planck equation for heavy-tailed random fluctuations. We show that the fractional diffusion processes in the presence of μ -stable Lévy noise display special scaling properties in the probability distribution function (PDF). Finally, we numerically study the scaling properties of the heavy-tailed random fluctuations by using the diffusion entropy analysis. This method is based on the evaluation of the Shannon entropy of the PDF generated by the random fluctuations, rather than on the measurement of the global width of the process. We apply the diffusion entropy analysis to extract the growth exponent β and to confirm the validity of our numerical analysis.
Comparison of Langevin and Markov channel noise models for neuronal signal generation.
Sengupta, B; Laughlin, S B; Niven, J E
2010-01-01
The stochastic opening and closing of voltage-gated ion channels produce noise in neurons. The effect of this noise on the neuronal performance has been modeled using either an approximate or Langevin model based on stochastic differential equations or an exact model based on a Markov process model of channel gating. Yet whether the Langevin model accurately reproduces the channel noise produced by the Markov model remains unclear. Here we present a comparison between Langevin and Markov models of channel noise in neurons using single compartment Hodgkin-Huxley models containing either Na+ and K+, or only K+ voltage-gated ion channels. The performance of the Langevin and Markov models was quantified over a range of stimulus statistics, membrane areas, and channel numbers. We find that in comparison to the Markov model, the Langevin model underestimates the noise contributed by voltage-gated ion channels, overestimating information rates for both spiking and nonspiking membranes. Even with increasing numbers of channels, the difference between the two models persists. This suggests that the Langevin model may not be suitable for accurately simulating channel noise in neurons, even in simulations with large numbers of ion channels.
Turning Noise into Signal: Utilizing Impressed Pipeline Currents for EM Exploration
Lindau, Tobias; Becken, Michael
2017-04-01
Impressed Current Cathodic Protection (ICCP) systems are extensively used for the protection of central Europe's dense network of oil-, gas- and water pipelines against destruction by electrochemical corrosion. While ICCP systems usually provide protection by injecting a DC current into the pipeline, mandatory pipeline integrity surveys demand a periodical switching of the current. Consequently, the resulting time varying pipe currents induce secondary electric- and magnetic fields in the surrounding earth. While these fields are usually considered to be unwanted cultural noise in electromagnetic exploration, this work aims at utilizing the fields generated by the ICCP system for determining the electrical resistivity of the subsurface. The fundamental period of the switching cycles typically amounts to 15 seconds in Germany and thereby roughly corresponds to periods used in controlled source EM applications (CSEM). For detailed studies we chose an approximately 30km long pipeline segment near Herford, Germany as a test site. The segment is located close to the southern margin of the Lower Saxony Basin (LSB) and part of a larger gas pipeline composed of multiple segments. The current injected into the pipeline segment originates in a rectified 50Hz AC signal which is periodically switched on and off. In contrast to the usual dipole sources used in CSEM surveys, the current distribution along the pipeline is unknown and expected to be non-uniform due to coating defects that cause current to leak into the surrounding soil. However, an accurate current distribution is needed to model the fields generated by the pipeline source. We measured the magnetic fields at several locations above the pipeline and used Biot-Savarts-Law to estimate the currents decay function. The resulting frequency dependent current distribution shows a current decay away from the injection point as well as a frequency dependent phase shift which is increasing with distance from the injection
Improving signal-to-noise in the direct imaging of exoplanets and circumstellar disks with MLOCI
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).
Low signal-to-noise FDEM in-phase data: Practical potential for magnetic susceptibility modelling
Delefortrie, Samuël; Hanssens, Daan; De Smedt, Philippe
2018-05-01
In this paper, we consider the use of land-based frequency-domain electromagnetics (FDEM) for magnetic susceptibility modelling. FDEM data comprises both out-of-phase and in-phase components, which can be related to the electrical conductivity and magnetic susceptibility of the subsurface. Though applying the FDEM method to obtain information on the subsurface conductivity is well established in various domains (e.g. through the low induction number approximation of subsurface apparent conductivity), the potential for susceptibility mapping is often overlooked. Especially given a subsurface with a low magnetite and maghemite content (e.g. most sedimentary environments), it is generally assumed that susceptibility is negligible. Nonetheless, the heterogeneity of the near surface and the impact of anthropogenic disturbances on the soil can cause sufficient variation in susceptibility for it to be detectable in a repeatable way. Unfortunately, it can be challenging to study the potential for susceptibility mapping due to systematic errors, an often poor low signal-to-noise ratio, and the intricacy of correlating in-phase responses with subsurface susceptibility and conductivity. Alongside use of an accurate forward model - accounting for out-of-phase/in-phase coupling - any attempt at relating the in-phase response with subsurface susceptibility requires overcoming instrument-specific limitations that burden the real-world application of FDEM susceptibility mapping. Firstly, the often erratic and drift-sensitive nature of in-phase responses calls for relative data levelling. In addition, a correction for absolute levelling offsets may be equally necessary: ancillary (subsurface) susceptibility data can be used to assess the importance of absolute in-phase calibration though hereby accurate in-situ data is required. To allow assessing the (importance of) in-phase calibration alongside the potential of FDEM data for susceptibility modelling, we consider an experimental
Noise is the new signal: Moving beyond zeroth-order geomorphology (Invited)
Jerolmack, D. J.
2010-12-01
The last several decades have witnessed a rapid growth in our understanding of landscape evolution, led by the development of geomorphic transport laws - time- and space-averaged equations relating mass flux to some physical process(es). In statistical mechanics this approach is called mean field theory (MFT), in which complex many-body interactions are replaced with an external field that represents the average effect of those interactions. Because MFT neglects all fluctuations around the mean, it has been described as a zeroth-order fluctuation model. The mean field approach to geomorphology has enabled the development of landscape evolution models, and led to a fundamental understanding of many landform patterns. Recent research, however, has highlighted two limitations of MFT: (1) The integral (averaging) time and space scales in geomorphic systems are sometimes poorly defined and often quite large, placing the mean field approximation on uncertain footing, and; (2) In systems exhibiting fractal behavior, an integral scale does not exist - e.g., properties like mass flux are scale-dependent. In both cases, fluctuations in sediment transport are non-negligible over the scales of interest. In this talk I will synthesize recent experimental and theoretical work that confronts these limitations. Discrete element models of fluid and grain interactions show promise for elucidating transport mechanics and pattern-forming instabilities, but require detailed knowledge of micro-scale processes and are computationally expensive. An alternative approach is to begin with a reasonable MFT, and then add higher-order terms that capture the statistical dynamics of fluctuations. In either case, moving beyond zeroth-order geomorphology requires a careful examination of the origins and structure of transport “noise”. I will attempt to show how studying the signal in noise can both reveal interesting new physics, and also help to formalize the applicability of geomorphic
Energy Technology Data Exchange (ETDEWEB)
Gongzhang, R.; Xiao, B.; Lardner, T.; Gachagan, A. [Centre for Ultrasonic Engineering, University of Strathclyde, Glasgow, G1 1XW (United Kingdom); Li, M. [School of Engineering, University of Glasgow, Glasgow, G12 8QQ (United Kingdom)
2014-02-18
This paper presents a robust frequency diversity based algorithm for clutter reduction in ultrasonic A-scan waveforms. The performance of conventional spectral-temporal techniques like Split Spectrum Processing (SSP) is highly dependent on the parameter selection, especially when the signal to noise ratio (SNR) is low. Although spatial beamforming offers noise reduction with less sensitivity to parameter variation, phased array techniques are not always available. The proposed algorithm first selects an ascending series of frequency bands. A signal is reconstructed for each selected band in which a defect is present when all frequency components are in uniform sign. Combining all reconstructed signals through averaging gives a probability profile of potential defect position. To facilitate data collection and validate the proposed algorithm, Full Matrix Capture is applied on the austenitic steel and high nickel alloy (HNA) samples with 5MHz transducer arrays. When processing A-scan signals with unrefined parameters, the proposed algorithm enhances SNR by 20dB for both samples and consequently, defects are more visible in B-scan images created from the large amount of A-scan traces. Importantly, the proposed algorithm is considered robust, while SSP is shown to fail on the austenitic steel data and achieves less SNR enhancement on the HNA data.
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.
International Nuclear Information System (INIS)
Park, Yulri; Choi, Dongil; Kim, Seong Hyun; Kim, Seung Hoon; Kim, Min Ju; Lee, Jongmee; Lim, Jae Hoon; Lee, Won Jae; Lim, Hyo K.
2006-01-01
Purpose: To verify changes in the signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) of hypervascular hepatocellular carcinomas (HCCs) on ferucarbotran-enhanced dynamic T1-weighted MR imaging. Materials and methods: Fifty-two patients with 61 hypervascular HCCs underwent ferucarbotran-enhanced dynamic MR imaging, and then hepatic resection. Hypervascular HCCs were identified when definite enhancement was noted during the arterial dominant phase of three-phase MDCT. Dynamic MR Images with T1-weighted fast multiplanar spoiled gradient-recalled echo sequence (TR200/TE4.2) were obtained before and 20 s, and 1, 3, 5, and 10 min, after bolus injection of ferucarbotran. We estimated the signal intensities of tumors and livers, and calculated the SNRs and CNRs of the tumors. Results: On ferucarbotran-enhanced dynamic MR imaging, SNR measurements showed a fluctuating pattern, namely, an increase in SNR followed by a decrease and a subsequent increase (or a decrease in SNR followed by a increase and a subsequent decrease) in 50 (82.0%) of 61 tumors, a single-peak SNR pattern (highest SNR on 20 s, 1, 3, or 5 min delayed images followed by a decrease) in seven (11.5%), and a decrease in SNR followed by an increase in four (6.6%). Maximum absolute CNRs with positive value were noted on 10 min delayed images in 41 (67.2%) tumors, and maximum absolute CNRs with negative value were observed on 20 s delayed images in 12 (19.7%) and on 1 min delayed images in eight (13.1%). Conclusion: Despite showing various SNR and CNR changes, the majority of hypervascular HCCs demonstrated a fluctuating SNR pattern on ferucarbotran-enhanced dynamic MR imaging and a highest CNR on 10 min delayed image, which differed from the classic enhancement pattern on multiphasic CT
A robust random number generator based on differential comparison of chaotic laser signals.
Zhang, Jianzhong; Wang, Yuncai; Liu, Ming; Xue, Lugang; Li, Pu; Wang, Anbang; Zhang, Mingjiang
2012-03-26
We experimentally realize a robust real-time random number generator by differentially comparing the signal from a chaotic semiconductor laser and its delayed signal through a 1-bit analog-to-digital converter. The probability density distribution of the output chaotic signal based on the differential comparison method possesses an extremely small coefficient of Pearson's median skewness (1.5 × 10⁻⁶), which can yield a balanced random sequence much easily than the previously reported method that compares the signal from the chaotic laser with a certain threshold value. Moveover, we experimently demonstrate that our method can stably generate good random numbers at rates of 1.44 Gbit/s with excellent immunity from external perturbations while the previously reported method fails.
Maugeri, L.; Moraschi, M.; Summers, P.; Favilla, S.; Mascali, D.; Cedola, A.; Porro, C. A.; Giove, F.; Fratini, M.
2018-02-01
Functional Magnetic Resonance Imaging (fMRI) based on Blood Oxygenation Level Dependent (BOLD) contrast has become one of the most powerful tools in neuroscience research. On the other hand, fMRI approaches have seen limited use in the study of spinal cord and subcortical brain regions (such as the brainstem and portions of the diencephalon). Indeed obtaining good BOLD signal in these areas still represents a technical and scientific challenge, due to poor control of physiological noise and to a limited overall quality of the functional series. A solution can be found in the combination of optimized experimental procedures at acquisition stage, and well-adapted artifact mitigation procedures in the data processing. In this framework, we studied two different data processing strategies to reduce physiological noise in cortical and subcortical brain regions and in the spinal cord, based on the aCompCor and RETROICOR denoising tools respectively. The study, performed in healthy subjects, was carried out using an ad hoc isometric motor task. We observed an increased signal to noise ratio in the denoised functional time series in the spinal cord and in the subcortical brain region.
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.
International Nuclear Information System (INIS)
Raupach, Rainer; Flohr, Thomas G
2011-01-01
We analyze the signal and noise propagation of differential phase-contrast computed tomography (PCT) compared with conventional attenuation-based computed tomography (CT) from a theoretical point of view. This work focuses on grating-based differential phase-contrast imaging. A mathematical framework is derived that is able to analytically predict the relative performance of both imaging techniques in the sense of the relative contrast-to-noise ratio for the contrast of any two materials. Two fundamentally different properties of PCT compared with CT are identified. First, the noise power spectra show qualitatively different characteristics implying a resolution-dependent performance ratio. The break-even point is derived analytically as a function of system parameters such as geometry and visibility. A superior performance of PCT compared with CT can only be achieved at a sufficiently high spatial resolution. Second, due to periodicity of phase information which is non-ambiguous only in a bounded interval statistical phase wrapping can occur. This effect causes a collapse of information propagation for low signals which limits the applicability of phase-contrast imaging at low dose.
Energy Technology Data Exchange (ETDEWEB)
Kostic, Lj [Institut za Nuklearne Nauke Boris Kidric, Belgrade (Yugoslavia); Runkel, J [Institut fuer Kerntechnik und Zerstoerungsfreie Pruefverfahren, Hannover (Germany)
1988-07-01
The neutron noise signals in a PWR power plant were analysed in terms of auto- and cross-power spectral densities, phases and coherences. Core barrel motion, fuel element vibrations and reactivity noise effect due to pressure variations have been monitored and analysed. (author)
The benefits of noise and nonlinearity: Extracting energy from random vibrations
Energy Technology Data Exchange (ETDEWEB)
Gammaitoni, Luca, E-mail: luca.gammaitoni@pg.infn.it [NiPS Laboratory, Universita di Perugia, I-06100 Perugia (Italy); Neri, Igor; Vocca, Helios [NiPS Laboratory, Universita di Perugia, I-06100 Perugia (Italy)
2010-10-05
Nonlinear behavior is the ordinary feature of the vast majority of dynamical systems and noise is commonly present in any finite temperature physical and chemical system. In this article we briefly review the potentially beneficial outcome of the interplay of noise and nonlinearity by addressing the novel field of vibration energy harvesting. The role of nonlinearity in a piezoelectric harvester oscillator dynamics is modeled with nonlinear stochastic differential equation.
A low noise photoelectric signal acquisition system applying in nuclear magnetic resonance gyroscope
Lu, Qilin; Zhang, Xian; Zhao, Xinghua; Yang, Dan; Zhou, Binquan; Hu, Zhaohui
2017-10-01
The nuclear magnetic resonance gyroscope serves as a new generation of strong support for the development of high-tech weapons, it solves the core problem that limits the development of the long-playing seamless navigation and positioning. In the NMR gyroscope, the output signal with atomic precession frequency is detected by the probe light, the final crucial photoelectric signal of the probe light directly decides the quality of the gyro signal. But the output signal has high sensitivity, resolution and measurement accuracy for the photoelectric detection system. In order to detect the measured signal better, this paper proposed a weak photoelectric signal rapid acquisition system, which has high SNR and the frequency of responded signal is up to 100 KHz to let the weak output signal with high frequency of the NMR gyroscope can be detected better.
Parks, Nathan A.; Gannon, Matthew A.; Long, Stephanie M.; Young, Madeleine E.
2016-01-01
Analysis of event-related potential (ERP) data includes several steps to ensure that ERPs meet an appropriate level of signal quality. One such step, subject exclusion, rejects subject data if ERP waveforms fail to meet an appropriate level of signal quality. Subject exclusion is an important quality control step in the ERP analysis pipeline as it ensures that statistical inference is based only upon those subjects exhibiting clear evoked brain responses. This critical quality control step is most often performed simply through visual inspection of subject-level ERPs by investigators. Such an approach is qualitative, subjective, and susceptible to investigator bias, as there are no standards as to what constitutes an ERP of sufficient signal quality. Here, we describe a standardized and objective method for quantifying waveform quality in individual subjects and establishing criteria for subject exclusion. The approach uses bootstrap resampling of ERP waveforms (from a pool of all available trials) to compute a signal-to-noise ratio confidence interval (SNR-CI) for individual subject waveforms. The lower bound of this SNR-CI (SNRLB) yields an effective and objective measure of signal quality as it ensures that ERP waveforms statistically exceed a desired signal-to-noise criterion. SNRLB provides a quantifiable metric of individual subject ERP quality and eliminates the need for subjective evaluation of waveform quality by the investigator. We detail the SNR-CI methodology, establish the efficacy of employing this approach with Monte Carlo simulations, and demonstrate its utility in practice when applied to ERP datasets. PMID:26903849
Ma, Liya; Skoblenick, Kevin; Seamans, Jeremy K; Everling, Stefan
2015-08-19
Working memory dysfunction is an especially debilitating symptom in schizophrenia. The NMDA antagonist ketamine has been successfully used to model working memory deficits in both rodents and nonhuman primates, but how it affects the strength and the consistency of working memory representations remains unclear. Here we recorded single-neuron activity in the lateral prefrontal cortex of macaque monkeys before and after the administration of subanesthetic doses of ketamine in a rule-based working memory task. The rule was instructed with a color cue before each delay period and dictated the correct prosaccadic or antisaccadic response to a peripheral stimulus appearing after the delay. We found that acute ketamine injections both weakened the rule signal across all delay periods and amplified the trial-to-trial variance in neural activities (i.e., noise), both within individual neurons and at the ensemble level, resulting in impaired performance. In the minority of postinjection trials when the animals responded correctly, the preservation of the signal strength during the delay periods was predictive of their subsequent success. Our findings suggest that NMDA receptor function may be critical for establishing the optimal signal-to-noise ratio in information representation by ensembles of prefrontal cortex neurons. In schizophrenia patients, working memory deficit is highly debilitating and currently without any efficacious treatment. An improved understanding of the pathophysiology of this symptom may provide critical information to treatment development. The NMDA antagonist ketamine, when injected at a subanesthetic dose, produces working memory deficit and other schizophrenia-like symptoms in humans and other animals. Here we investigated the effects of ketamine on the representation of abstract rules by prefrontal neurons, while macaque monkeys held the rules in working memory before responding accordingly. We found that ketamine weakened the signal-to-noise
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 ...
Energy Technology Data Exchange (ETDEWEB)
Klapper, Helmuth Sarmiento [Federal Institute for Materials Research and Testing, Unter den Eichen 87, 12205 Berlin (Germany)], E-mail: Helmuth.sarmiento-klapper@bam.de; Goellner, Joachim [Otto von Guericke University Magdeburg, P.O. Box 4120, Magdeburg (Germany); Heyn, Andreas [Federal Institute for Materials Research and Testing, Unter den Eichen 87, 12205 Berlin (Germany); Otto von Guericke University Magdeburg, P.O. Box 4120, Magdeburg (Germany)
2010-04-15
The use of electrochemical noise (EN) measurements for the investigation and monitoring of corrosion has allowed many interesting advances in the corrosion science in recent years. A special advantage of EN measurements includes the possibility to detect and study the early stages of localized corrosion. Nevertheless, the understanding of the electrochemical information included in the EN signal is actually very limited. The role of the cathodic process on the EN signals remains uncertain and has not been sufficiently investigated to date. Thus, an accurate understanding of the influence of the cathodic process on the EN signal is still lacking. On the basis of different kinetics of the oxygen reduction it was established that the anodic amplitude of transients arising from pitting corrosion on stainless steel can be decreased by the corresponding electron consumption of the cathodic process. Therefore, the stronger the electron consumption, the weaker the anodic amplitude of the EN signal becomes. EN signals arising from pitting corrosion on stainless steel can be measured because the cathodic process is inhibited by the passive layer. This was confirmed by means of EN measurements under cathodic polarisation. Since the cathodic process plays a decisive role on the form of transients arising from pitting corrosion, its influence must be considered in the evaluation and interpretation of the EN signals.
Novel active signal compression in low-noise analog readout at future X-ray FEL facilities
Manghisoni, M.; Comotti, D.; Gaioni, L.; Lodola, L.; Ratti, L.; Re, V.; Traversi, G.; Vacchi, C.
2015-04-01
This work presents the design of a low-noise front-end implementing a novel active signal compression technique. This feature can be exploited in the design of analog readout channels for application to the next generation free electron laser (FEL) experiments. The readout architecture includes the low-noise charge sensitive amplifier (CSA) with dynamic signal compression, a time variant shaper used to process the signal at the preamplifier output and a 10-bit successive approximation register (SAR) analog-to-digital converter (ADC). The channel will be operated in such a way to cope with the high frame rate (exceeding 1 MHz) foreseen for future XFEL machines. The choice of a 65 nm CMOS technology has been made in order to include all the building blocks in the target pixel pitch of 100 μm. This work has been carried out in the frame of the PixFEL Project funded by the Istituto Nazionale di Fisica Nucleare (INFN), Italy.
Seo, Min-Woong; Kawahito, Shoji
2017-12-01
A large full well capacity (FWC) for wide signal detection range and low temporal random noise for high sensitivity lock-in pixel CMOS image sensor (CIS) embedded with two in-pixel storage diodes (SDs) has been developed and presented in this paper. For fast charge transfer from photodiode to SDs, a lateral electric field charge modulator (LEFM) is used for the developed lock-in pixel. As a result, the time-resolved CIS achieves a very large SD-FWC of approximately 7ke-, low temporal random noise of 1.2e-rms at 20 fps with true correlated double sampling operation and fast intrinsic response less than 500 ps at 635 nm. The proposed imager has an effective pixel array of and a pixel size of . The sensor chip is fabricated by Dongbu HiTek 1P4M 0.11 CIS process.
International Nuclear Information System (INIS)
Boyers, D.; Ho, A.; Li, Q.; Piestrup, M.; Rice, M.; Tatchyn, R.
1993-08-01
In recent work, various design techniques were applied to investigate the feasibility of controlling the bandwidth and bandshape profiles of tungsten/boron-carbon (W/B 4 C) and tungsten/silicon (W/Si) multilayers for optimizing their performance in synchrotron radiation based angiographical imaging systems at 33 keV. Varied parameters included alternative spacing geometries, material thickness ratios, and numbers of layer pairs. Planar optics with nominal design reflectivities of 30%--94% and bandwidths ranging from 0.6%--10% were designed at the Stanford Radiation Laboratory, fabricated by the Ovonic Synthetic Materials Company, and characterized on Beam Line 4-3 at the Stanford Synchrotron Radiation Laboratory, in this paper we report selected results of these tests and review the possible use of the multilayers for determining optimal signal to noise vs. artifact signal ratios in practical Dual-Energy Digital Subtraction Angiography systems
International Nuclear Information System (INIS)
Steinbrecher, Gyoergy; Weyssow, B.
2004-01-01
The extreme heavy tail and the power-law decay of the turbulent flux correlation observed in hot magnetically confined plasmas are modeled by a system of coupled Langevin equations describing a continuous time linear randomly amplified stochastic process where the amplification factor is driven by a superposition of colored noises which, in a suitable limit, generate a fractional Brownian motion. An exact analytical formula for the power-law tail exponent β is derived. The extremely small value of the heavy tail exponent and the power-law distribution of laminar times also found experimentally are obtained, in a robust manner, for a wide range of input values, as a consequence of the (asymptotic) self-similarity property of the noise spectrum. As a by-product, a new representation of the persistent fractional Brownian motion is obtained
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
Freed, Michael A
2017-11-15
Bipolar and amacrine cells presynaptic to the ON sustained α cell of mouse retina provide currents with a higher signal-to-noise power ratio (SNR) than those presynaptic to the OFF sustained α cell. Yet the ON cell loses proportionately more SNR from synaptic inputs to spike output than the OFF cell does. The higher SNR of ON bipolar cells at the beginning of the ON pathway compensates for losses incurred by the ON ganglion cell, and improves the processing of positive contrasts. ON and OFF pathways in the retina include functional pairs of neurons that, at first glance, appear to have symmetrically similar responses to brightening and darkening, respectively. Upon careful examination, however, functional pairs exhibit asymmetries in receptive field size and response kinetics. Until now, descriptions of how light-adapted retinal circuitry maintains a preponderance of signal over the noise have not distinguished between ON and OFF pathways. Here I present evidence of marked asymmetries between members of a functional pair of sustained α ganglion cells in the mouse retina. The ON cell exhibited a proportionately greater loss of signal-to-noise power ratio (SNR) from its presynaptic arrays to its postsynaptic currents. Thus the ON cell combines signal and noise from its presynaptic arrays of bipolar and amacrine cells less efficiently than the OFF cell does. Yet the inefficiency of the ON cell is compensated by its presynaptic arrays providing a higher SNR than the arrays presynaptic to the OFF cell, apparently to improve visual processing of positive contrasts. Dynamic clamp experiments were performed that introduced synaptic conductances into ON and OFF cells. When the amacrine-modulated conductance was removed, the ON cell's spike train exhibited an increase in SNR. The OFF cell, however, showed the opposite effect of removing amacrine input, which was a decrease in SNR. Thus ON and OFF cells have different modes of synaptic integration with direct effects on
International Nuclear Information System (INIS)
Burgudzhiev, Z.; Koleva, D.
1986-01-01
A known theoretical model of an alternative use of silver-halogenid pnotographic emulsions in which the number of the granulas forming the photographic image is used as a detector output instead of the microdensiometric blackening density is applied to some real photographic emulsions. It is found that by this use the Signal-to-Noise ratio of the photographic detector can be increased to about 5 times while its detective quantum efficiency can reach about 20%, being close to that of some photomultipliers
Random genetic drift, natural selection, and noise in human cranial evolution.
Roseman, Charles C
2016-08-01
This study assesses the extent to which relationships among groups complicate comparative studies of adaptation in recent human cranial variation and the extent to which departures from neutral additive models of evolution hinder the reconstruction of population relationships among groups using cranial morphology. Using a maximum likelihood evolutionary model fitting approach and a mixed population genomic and cranial data set, I evaluate the relative fits of several widely used models of human cranial evolution. Moreover, I compare the goodness of fit of models of cranial evolution constrained by genomic variation to test hypotheses about population specific departures from neutrality. Models from population genomics are much better fits to cranial variation than are traditional models from comparative human biology. There is not enough evolutionary information in the cranium to reconstruct much of recent human evolution but the influence of population history on cranial variation is strong enough to cause comparative studies of adaptation serious difficulties. Deviations from a model of random genetic drift along a tree-like population history show the importance of environmental effects, gene flow, and/or natural selection on human cranial variation. Moreover, there is a strong signal of the effect of natural selection or an environmental factor on a group of humans from Siberia. The evolution of the human cranium is complex and no one evolutionary process has prevailed at the expense of all others. A holistic unification of phenome, genome, and environmental context, gives us a strong point of purchase on these problems, which is unavailable to any one traditional approach alone. Am J Phys Anthropol 160:582-592, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Pervasive randomness in physics: an introduction to its modelling and spectral characterisation
Howard, Roy
2017-10-01
An introduction to the modelling and spectral characterisation of random phenomena is detailed at a level consistent with a first exposure to the subject at an undergraduate level. A signal framework for defining a random process is provided and this underpins an introduction to common random processes including the Poisson point process, the random walk, the random telegraph signal, shot noise, information signalling random processes, jittered pulse trains, birth-death random processes and Markov chains. An introduction to the spectral characterisation of signals and random processes, via either an energy spectral density or a power spectral density, is detailed. The important case of defining a white noise random process concludes the paper.
Discriminality of statistically independent Gaussian noise tokens and random tone-burst complexes
Goossens, T.L.J.; Par, van de, S.L.J.D.E.; Kohlrausch, A.G.; Kollmeier, B.; Klump, G.; Hohmann, V.; Langemann, U.; Mauermann, M.; Uppenkamp, S.; Verhey, J.
2007-01-01
Hanna (1984) has shown that noise tokens with a duration of 400 ms are harder to discriminate than noise tokens of 100 ms. This is remarkable because a 400-ms stimulus potentially contains four times as much information for judging dissimilarity than the 100-ms stimulus. Apparently, the ability to use all information in a stimulus is impaired by some kind of limitation, e.g. a memory limitation (cf. Cowan 2000) or a limitation in the ability to allocate attentional resources (cf. Kidd and Wat...
A random-parametric reactor model with direct feedback and non-white noise
International Nuclear Information System (INIS)
Sako, O.; Taniguchi, A.; Kuroda, Y.
1982-01-01
The effects of multiplicative direct power feedback and non-white reactivity noise on the fluctuations of the neutron density are studied, based on the master equation using the cumulant expansion and the system-size expansion. The results obtained are the following: non-whiteness of reactivity noise reduces the variance of neutron density, as well as the level of the power spectral density. The nonlinear effect of power feedback gives rise to at least a pair of corner frequencies, in contrast to the single corner frequency in linearized case. (author)
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
Ding, Jiule; Xing, Wei; Chen, Jie; Dai, Yongming; Sun, Jun; Li, Dengfa
2014-01-21
To explore the influence of signal noise ratio (SNR) on analysis of clear cell renal cell carcinoma (CCRCC) using DWI with multi-b values. The images of 17 cases with CCRCC were analyzed, including 17 masses and 9 pure cysts. The signal intensity of the cysts and masses was measured separately on DWI for each b value. The minimal SNR, as the threshold, was recorded when the signal curve manifest as the single exponential line. The SNR of the CCRCC was calculated on DWI for each b value, and compared with the threshold by independent Two-sample t Test. The signal decreased on DWI with increased b factors for both pure cysts and CCRCC. The threshold is 1.29 ± 0.17, and the signal intensity of the cysts on DWI with multi-b values shown as a single exponential line when b ≤ 800 s/mm(2). For the CCRCC, the SNR is similar to the threshold when b = 1 000 s/mm(2) (t = 0.40, P = 0.69), and is lower when b = 1 200 s/mm(2) (t = -2.38, P = 0.03). The SNR should be sufficient for quantitative analysis of DWI, and the maximal b value is 1000 s/mm(2) for CCRCC.
Zavarygin, E. O.; Webb, J. K.; Dumont, V.; Riemer-Sørensen, S.
2018-04-01
The spectrum of the zem = 2.63 quasar Q1009+2956 has been observed extensively on the Keck telescope. The Lyman limit absorption system zabs = 2.504 was previously used to measure D/H by Burles & Tytler using a spectrum with signal to noise approximately 60 per pixel in the continuum near Ly α at zabs = 2.504. The larger dataset now available combines to form an exceptionally high signal to noise spectrum, around 147 per pixel. Several heavy element absorption lines are detected in this LLS, providing strong constraints on the kinematic structure. We explore a suite of absorption system models and find that the deuterium feature is likely to be contaminated by weak interloping Ly α absorption from a low column density H I cloud, reducing the expected D/H precision. We find D/H =2.48^{+0.41}_{-0.35} × 10^{-5} for this system. Combining this new measurement with others from the literature and applying the method of Least Trimmed Squares to a statistical sample of 15 D/H measurements results in a "reliable" sample of 13 values. This sample yields a primordial deuterium abundance of (D/H)p = (2.545 ± 0.025) × 10-5. The corresponding mean baryonic density of the Universe is Ωbh2 = 0.02174 ± 0.00025. The quasar absorption data is of the same precision as, and marginally inconsistent with, the 2015 CMB Planck (TT+lowP+lensing) measurement, Ωbh2 = 0.02226 ± 0.00023. Further quasar and more precise nuclear data are required to establish whether this is a random fluctuation.
Liang, Kun; Niu, Qunjie; Wu, Xiangkui; Xu, Jiaqi; Peng, Li; Zhou, Bo
2017-09-01
A lidar system with Fabry-Pérot etalon and an intensified charge coupled device can be used to obtain the scattering spectrum of the ocean and retrieve oceanic temperature profiles. However, the spectrum would be polluted by noise and result in a measurement error. To analyze the effect of signal to noise ratio (SNR) on the accuracy of measurements for Brillouin lidar in water, the theory model and characteristics of SNR are researched. The noise spectrums with different SNR are repetitiously measured based on simulation and experiment. The results show that accuracy is related to SNR, and considering the balance of time consumption and quality, the average of five measurements is adapted for real remote sensing under the pulse laser conditions of wavelength 532 nm, pulse energy 650 mJ, repetition rate 10 Hz, pulse width 8 ns and linewidth 0.003 cm-1 (90 MHz). Measuring with the Brillouin linewidth has a better accuracy at a lower temperature (15 °C), based on the classical retrieval model we adopt. The experimental results show that the temperature error is 0.71 °C and 0.06 °C based on shift and linewidth respectively when the image SNR is at the range of 3.2 dB-3.9 dB.
Zhang, Hua; Yang, Hui; Li, Hongxing; Huang, Guangnan; Ding, Zheyi
2018-04-01
The attenuation of random noise is important for improving the signal to noise ratio (SNR). However, the precondition for most conventional denoising methods is that the noisy data must be sampled on a uniform grid, making the conventional methods unsuitable for non-uniformly sampled data. In this paper, a denoising method capable of regularizing the noisy data from a non-uniform grid to a specified uniform grid is proposed. Firstly, the denoising method is performed for every time slice extracted from the 3D noisy data along the source and receiver directions, then the 2D non-equispaced fast Fourier transform (NFFT) is introduced in the conventional fast discrete curvelet transform (FDCT). The non-equispaced fast discrete curvelet transform (NFDCT) can be achieved based on the regularized inversion of an operator that links the uniformly sampled curvelet coefficients to the non-uniformly sampled noisy data. The uniform curvelet coefficients can be calculated by using the inversion algorithm of the spectral projected-gradient for ℓ1-norm problems. Then local threshold factors are chosen for the uniform curvelet coefficients for each decomposition scale, and effective curvelet coefficients are obtained respectively for each scale. Finally, the conventional inverse FDCT is applied to the effective curvelet coefficients. This completes the proposed 3D denoising method using the non-equispaced curvelet transform in the source-receiver domain. The examples for synthetic data and real data reveal the effectiveness of the proposed approach in applications to noise attenuation for non-uniformly sampled data compared with the conventional FDCT method and wavelet transformation.
A CMOS power-efficient low-noise current-mode front-end amplifier for neural signal recording.
Wu, Chung-Yu; Chen, Wei-Ming; Kuo, Liang-Ting
2013-04-01
In this paper, a new current-mode front-end amplifier (CMFEA) for neural signal recording systems is proposed. In the proposed CMFEA, a current-mode preamplifier with an active feedback loop operated at very low frequency is designed as the first gain stage to bypass any dc offset current generated by the electrode-tissue interface and to achieve a low high-pass cutoff frequency below 0.5 Hz. No reset signal or ultra-large pseudo resistor is required. The current-mode preamplifier has low dc operation current to enhance low-noise performance and decrease power consumption. A programmable current gain stage is adopted to provide adjustable gain for adaptive signal scaling. A following current-mode filter is designed to adjust the low-pass cutoff frequency for different neural signals. The proposed CMFEA is designed and fabricated in 0.18-μm CMOS technology and the area of the core circuit is 0.076 mm(2). The measured high-pass cutoff frequency is as low as 0.3 Hz and the low-pass cutoff frequency is adjustable from 1 kHz to 10 kHz. The measured maximum current gain is 55.9 dB. The measured input-referred current noise density is 153 fA /√Hz , and the power consumption is 13 μW at 1-V power supply. The fabricated CMFEA has been successfully applied to the animal test for recording the seizure ECoG of Long-Evan rats.
Orović, Irena; Stanković, Srdjan; Amin, Moeness
2013-05-01
A modified robust two-dimensional compressive sensing algorithm for reconstruction of sparse time-frequency representation (TFR) is proposed. The ambiguity function domain is assumed to be the domain of observations. The two-dimensional Fourier bases are used to linearly relate the observations to the sparse TFR, in lieu of the Wigner distribution. We assume that a set of available samples in the ambiguity domain is heavily corrupted by an impulsive type of noise. Consequently, the problem of sparse TFR reconstruction cannot be tackled using standard compressive sensing optimization algorithms. We introduce a two-dimensional L-statistics based modification into the transform domain representation. It provides suitable initial conditions that will produce efficient convergence of the reconstruction algorithm. This approach applies sorting and weighting operations to discard an expected amount of samples corrupted by noise. The remaining samples serve as observations used in sparse reconstruction of the time-frequency signal representation. The efficiency of the proposed approach is demonstrated on numerical examples that comprise both cases of monocomponent and multicomponent signals.
International Nuclear Information System (INIS)
Vashista, M.; Paul, S.
2011-01-01
The Barkhausen Noise Analysis (BNA) technique has been utilised to assess surface integrity of steels. But the BNA technique is not very successful in evaluating surface integrity of ground steels that exhibit poor micro-magnetic response. A new approach has been proposed for the processing of BN signal and two newly proposed parameters, namely 'count' and 'event', have been shown to correlate linearly with the residual stress upon grinding, with judicious choice of user defined 'threshold', even when the micro-magnetic response of the work material is poor. In the present study, residual stress induced upon conventional plunge surface grinding of hardened bearing steel has been investigated along with unhardened bearing steel for benchmarking. Moreover, similar correlation has been established, when primarily compressive stress is induced upon high speed grinding using cBN wheel with moderately deep cut suppressing the micro-magnetic response from the ground medium carbon steel as the work material. - Highlights: → The problem of work materials exhibiting poor BN response and poor Barkhausen Noise response is identified. → A novel signal processing strategy is introduced to address the issue of poor micro-magnetic response of some ferromagnetic material. → Potential of newly introduced BN parameters has been studied. → These two BN parameters exhibited linear correlation with residual stress for work material with poor micro-magnetic response.
Sibille, Nathalie; Bellot, Gaëtan; Wang, Jing; Déméné, Hélène
2012-11-01
Despite numerous developments in the past few years that aim to increase the sensitivity of NMR multidimensional experiments, NMR spectroscopy still suffers from intrinsic low sensitivity. In this report, we show that the combination of two developments in the field, the Band-selective Excitation Short-Transient (BEST) experiment [Schanda et al., J. Am. Chem. Soc., 128 (2006) 9042] and the addition of the nonionic paramagnetic gadolinium chelate gadodiamide into NMR samples, enhances the signal-to-noise ratio. This effect is shown here for four different proteins, three globular and one unfolded, of molecular weights ranging from 6.5 kDa to 40 kDa, using 2D BEST HSQC and 3D BEST triple resonance sequences. Moreover, we show that the increase in signal-to-noise ratio provided by the gadodiamide is higher for peak resonances with lower than average intensity in BEST experiments. It is interesting to note that these residues are on average the weakest ones in those experiments. In this case, the gadodiamide-mediated increase can reach a value of 60% for low and 30% for high molecular weight proteins respectively. An investigation into the origin of this “paramagnetic gain” in BEST experiments is presented.
Kousi, Evanthia; Borri, Marco; Dean, Jamie; Panek, Rafal; Scurr, Erica; Leach, Martin O.; Schmidt, Maria A.
2016-01-01
MRI has been extensively used in breast cancer staging, management and high risk screening. Detection sensitivity is paramount in breast screening, but variations of signal-to-noise ratio (SNR) as a function of position are often overlooked. We propose and demonstrate practical methods to assess spatial SNR variations in dynamic contrast-enhanced (DCE) breast examinations and apply those methods to different protocols and systems. Four different protocols in three different MRI systems (1.5 and 3.0 T) with receiver coils of different design were employed on oil-filled test objects with and without uniformity filters. Twenty 3D datasets were acquired with each protocol; each dataset was acquired in under 60 s, thus complying with current breast DCE guidelines. In addition to the standard SNR calculated on a pixel-by-pixel basis, we propose other regional indices considering the mean and standard deviation of the signal over a small sub-region centred on each pixel. These regional indices include effects of the spatial variation of coil sensitivity and other structured artefacts. The proposed regional SNR indices demonstrate spatial variations in SNR as well as the presence of artefacts and sensitivity variations, which are otherwise difficult to quantify and might be overlooked in a clinical setting. Spatial variations in SNR depend on protocol choice and hardware characteristics. The use of uniformity filters was shown to lead to a rise of SNR values, altering the noise distribution. Correlation between noise in adjacent pixels was associated with data truncation along the phase encoding direction. Methods to characterise spatial SNR variations using regional information were demonstrated, with implications for quality assurance in breast screening and multi-centre trials.
Chon, Deokiee; Beck, Kenneth C; Simon, Brett A; Shikata, Hidenori; Saba, Osama I; Hoffman, Eric A
2007-04-01
Xenon computed tomography (Xe-CT) is used to estimate regional ventilation by measuring regional attenuation changes over multiple breaths while rebreathing a constant Xe concentration ([Xe]). Xe-CT has potential human applications, although anesthetic properties limit [Xe] to krypton (Kr) combination, on time constant (TC) determination. Six anesthetized sheep were scanned prone and supine using multidetector row CT. Lungs were imaged by respiratory gating during washin of a 30%, 40%, 55% Xe, and a 30% Xe/30% Kr mixture. Using Kr avoids unwanted effects of Xe. Mean TCs, coefficients of variation (CV), and half confidence intervals (CI)/mean served as indexes of sensitivity to noise. Mean supine and prone TCs of three [Xe] values were not significantly different. Average CVs of TCs increased from 57% (55% Xe), 58% (40% Xe), and 73% (30% Xe) (P < 0.05: paired t-tests; 30% Xe vs. higher [Xe]). Monte Carlo simulation indicated a CV based on inherent image noise was 8% for 55% Xe and 17% for 30% Xe (P < 0.05). Adding 30% Kr to 30% Xe gave a washin signal equivalent to 40% Xe. Half CI/mean using the 30% Xe/30% Kr mixture was not significantly different from 55 and 40% Xe. Although average TCs were not affected by changes in [Xe], the higher CV and half CI/mean suggested reduced signal-to-noise ratio at the 30% [Xe]. The 30% Xe/30% Kr mixture was comparable to that of 40% Xe, providing an important agent for CT-based assessment of regional ventilation in humans.
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
Asenov, Asen; Balasubramaniam, R.; Brown, A. R.; Davies, J. H.; Saini, Subhash
2000-01-01
In this paper we use 3D simulations to study the amplitudes of random telegraph signals (RTS) associated with the trapping of a single carrier in interface states in the channel of sub 100 nm (decanano) MOSFETs. Both simulations using continuous doping charge and random discrete dopants in the active region of the MOSFETs are presented. We have studied the dependence of the RTS amplitudes on the position of the trapped charge in the channel and on the device design parameters. We have observed a significant increase in the maximum RTS amplitude when discrete random dopants are employed in the simulations.
DEFF Research Database (Denmark)
Deng, Lei; Pang, Xiaodan; Tafur Monroy, Idelfonso
2014-01-01
We propose a nonlinearity and phase noise tolerant orthogonal frequency division multiplexing (OFDM) W-band signal over fiber system based on phase modulation and photonic heterodyne up-conversion techniques. By heterodyne mixing the phase-modulated optical OFDM signal with a free-running laser i...
Experimentally Generated Random Numbers Certified by the Impossibility of Superluminal Signaling
Bierhorst, Peter; Shalm, Lynden K.; Mink, Alan; Jordan, Stephen; Liu, Yi-Kai; Rommal, Andrea; Glancy, Scott; Christensen, Bradley; Nam, Sae Woo; Knill, Emanuel
Random numbers are an important resource for applications such as numerical simulation and secure communication. However, it is difficult to certify whether a physical random number generator is truly unpredictable. Here, we exploit the phenomenon of quantum nonlocality in a loophole-free photonic Bell test experiment to obtain data containing randomness that cannot be predicted by any theory that does not also allow the sending of signals faster than the speed of light. To certify and quantify the randomness, we develop a new protocol that performs well in an experimental regime characterized by low violation of Bell inequalities. Applying an extractor function to our data, we obtain 256 new random bits, uniform to within 10- 3 .
SPDEs with α-Stable Lévy Noise: A Random Field Approach
Directory of Open Access Journals (Sweden)
Raluca M. Balan
2014-01-01
Full Text Available This paper is dedicated to the study of a nonlinear SPDE on a bounded domain in Rd, with zero initial conditions and Dirichlet boundary, driven by an α-stable Lévy noise Z with α∈(0,2, α≠1, and possibly nonsymmetric tails. To give a meaning to the concept of solution, we develop a theory of stochastic integration with respect to this noise. The idea is to first solve the equation with “truncated” noise (obtained by removing from Z the jumps which exceed a fixed value K, yielding a solution uK, and then show that the solutions uL,L>K coincide on the event t≤τK, for some stopping times τK converging to infinity. A similar idea was used in the setting of Hilbert-space valued processes. A major step is to show that the stochastic integral with respect to ZK satisfies a pth moment inequality. This inequality plays the same role as the Burkholder-Davis-Gundy inequality in the theory of integration with respect to continuous martingales.
Brousmiche, S.; Souris, K.; Orban de Xivry, J.; Lee, J. A.; Macq, B.; Seco, J.
2017-11-01
Proton range random and systematic uncertainties are the major factors undermining the advantages of proton therapy, namely, a sharp dose falloff and a better dose conformality for lower doses in normal tissues. The influence of CT artifacts such as beam hardening or scatter can easily be understood and estimated due to their large-scale effects on the CT image, like cupping and streaks. In comparison, the effects of weakly-correlated stochastic noise are more insidious and less attention is drawn on them partly due to the common belief that they only contribute to proton range uncertainties and not to systematic errors thanks to some averaging effects. A new source of systematic errors on the range and relative stopping powers (RSP) has been highlighted and proved not to be negligible compared to the 3.5% uncertainty reference value used for safety margin design. Hence, we demonstrate that the angular points in the HU-to-RSP calibration curve are an intrinsic source of proton range systematic error for typical levels of zero-mean stochastic CT noise. Systematic errors on RSP of up to 1% have been computed for these levels. We also show that the range uncertainty does not generally vary linearly with the noise standard deviation. We define a noise-dependent effective calibration curve that better describes, for a given material, the RSP value that is actually used. The statistics of the RSP and the range continuous slowing down approximation (CSDA) have been analytically derived for the general case of a calibration curve obtained by the stoichiometric calibration procedure. These models have been validated against actual CSDA simulations for homogeneous and heterogeneous synthetical objects as well as on actual patient CTs for prostate and head-and-neck treatment planning situations.
Directory of Open Access Journals (Sweden)
M Salmani Nodoushan
2014-09-01
Full Text Available Background: Noise-induced hearing loss (NIHL is one of the most common occupational diseases and the second most common cause of workers' claims for occupational injuries. Objective: Due to high prevalence of NIHL and several reports of improper use of hearing protective devices (HPDs, we conducted this study to compare the effect of face-to-face training in effective use of earplugs with appropriate NRR to overprotection of workers by using earplugs with higher than necessary noise reduction rating (NRR. Methods: In a randomized clinical trial, 150 workers referred to occupational medicine clinic were randomly allocated to three arms—a group wearing earplugs with an NRR of 25 with no training in appropriate use of the device; a group wearing earplugs with an NRR of 25 with training; another group wearing earplugs with an NRR of 30, with no training. Hearing threshold was measured in the study groups by real ear attenuation at threshold (REAT method. This trial is registered with Australian New Zealand clinical trials Registry, number ACTRN00363175. Results: The mean±SD age of the participants was 28±5 (range: 19–39 years. 42% of participants were female. The mean noise attenuation in the group with training was 13.88 dB, significantly higher than those observed in other groups. The highest attenuation was observed in high frequencies (4, 6, and 8 kHz in the group with training. Conclusion: Training in appropriate use of earplugs significantly affects the efficacy of earplugs—even more than using an earplug with higher NRR.
Directory of Open Access Journals (Sweden)
Yuichi eYamashita
2011-04-01
Full Text Available How the brain learns and generates temporal sequences is a fundamental issue in neuroscience. The production of birdsongs, a process which involves complex learned sequences, provides researchers with an excellent biological model for this topic. The Bengalese finch in particular learns a highly complex song with syntactical structure. The nucleus HVC (HVC, a premotor nucleus within the avian song system, plays a key role in generating the temporal structures of their songs. From lesion studies, the nucleus interfacialis (NIf projecting to the HVC is considered one of the essential regions that contribute to the complexity of their songs. However, the types of interaction between the HVC and the NIf that can produce complex syntactical songs remain unclear. In order to investigate the function of interactions between the HVC and NIf, we have proposed a neural network model based on previous biological evidence. The HVC is modeled by a recurrent neural network (RNN that learns to generate temporal patterns of songs. The NIf is modeled as a mechanism that provides auditory feedback to the HVC and generates random noise that feeds into the HVC. The model showed that complex syntactical songs can be replicated by simple interactions between deterministic dynamics of the RNN and random noise. In the current study, the plausibility of the model is tested by the comparison between the changes in the songs of actual birds induced by pharmacological inhibition of the NIf and the changes in the songs produced by the model resulting from modification of parameters representing NIf functions. The efficacy of the model demonstrates that the changes of songs induced by pharmacological inhibition of the NIf can be interpreted as a trade-off between the effects of noise and the effects of feedback on the dynamics of the RNN of the HVC. These facts suggest that the current model provides a convincing hypothesis for the functional role of NIf-HVC interaction.
Emergence of a signal from background noise in the "memory of water" experiments: how to explain it?
Beauvais, Francis
2012-01-01
After more than 20 years, the case of the "memory of water" still has not been resolved satisfactorily. After the affair with the journal Nature, Benveniste extended his results on high dilutions to an "electromagnetic biology" and then to a "digital biology," where electromagnetic signals supposed to be emitted from biologically active solutions were said to be stored on magnetic memories. Although the results obtained by Benveniste and coworkers were obvious, the difficulties in reproducibility by other teams created doubt of the reality of the alleged phenomenon. In a first step, we analyzed a set of experiments obtained by Benveniste's team in the 1990s. We quantified the relationship between "expected" effects (ie, labels of the tested samples) and apparatus outcomes, and we defined the experimental conditions to observe significant correlations. We concluded that the results of these experiments were related to experimenter-dependent correlations, which did not support the initial "memory of water" hypothesis. The fact that a signal emerged from background noise, however, remained puzzling. Therefore, in a second step, we described Benveniste's experiments according to the relational interpretation of quantum physics of C. Rovelli. In this interpretation, the state of a system is observer-dependent and the collapse of the wave function appears only in the states relative to a given observer. This interpretation allowed us to elaborate a model describing Benveniste's experiments in which the emergence of a signal from background noise was described by the entanglement of the experimenter with the observed system. In conclusion, the pursuit of the experimental "proof" to support the "memory of water" hypothesis has prevented other interpretations. Although our hypothesis does not definitely dismiss the possibility of "memory of water," the experimenter-dependent entanglement could be an attractive alternative interpretation of Benveniste's experiments
Kiani, M A; Sim, K S; Nia, M E; Tso, C P
2015-05-01
A new technique based on cubic spline interpolation with Savitzky-Golay smoothing using weighted least squares error filter is enhanced for scanning electron microscope (SEM) images. A diversity of sample images is captured and the performance is found to be better when compared with the moving average and the standard median filters, with respect to eliminating noise. This technique can be implemented efficiently on real-time SEM images, with all mandatory data for processing obtained from a single image. Noise in images, and particularly in SEM images, are undesirable. A new noise reduction technique, based on cubic spline interpolation with Savitzky-Golay and weighted least squares error method, is developed. We apply the combined technique to single image signal-to-noise ratio estimation and noise reduction for SEM imaging system. This autocorrelation-based technique requires image details to be correlated over a few pixels, whereas the noise is assumed to be uncorrelated from pixel to pixel. The noise component is derived from the difference between the image autocorrelation at zero offset, and the estimation of the corresponding original autocorrelation. In the few test cases involving different images, the efficiency of the developed noise reduction filter is proved to be significantly better than those obtained from the other methods. Noise can be reduced efficiently with appropriate choice of scan rate from real-time SEM images, without generating corruption or increasing scanning time. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.
A high speed digital noise generator
Obrien, J.; Gaffney, B.; Liu, B.
In testing of digital signal processing hardware, a high speed pseudo-random noise generator is often required to simulate an input noise source to the hardware. This allows the hardware to be exercised in a manner analogous to actual operating conditions. In certain radar and communication environments, a noise generator operating at speeds in excess of 60 MHz may be required. In this paper, a method of generating high speed pseudo-random numbers from an arbitrarily specified distribution (Gaussian, Log-Normal, etc.) using a transformation from a uniform noise source is described. A noise generator operating at 80 MHz has been constructed. Different distributions can be readily obtained by simply changing the ROM set. The hardware and test results will be described. Using this approach, the generation of pseudo-random sequences with arbitrary distributions at word rates in excess of 200 MHz can be readily achieved.
Optimum Boundaries of Signal-to-Noise Ratio for Adaptive Code Modulations
2017-11-14
possible ACM modes. This will decrease the searching time by half when compared to the mode search using a linear searching ( sequential ) method. The... simultaneously on with same 10 dB transmit power gain and parameters………………………………………………………………65 Fig. B-12. PSD when signal is transmitted from vector network...dB transmit power gain. Observe in Fig. B-11 that the peak height of the summed signal PSD increases when the second USRP 2932 is simultaneously
Daróczi, Lajos; Piros, Eszter; Tóth, László Z.; Beke, Dezső L.
2017-07-01
Jerky magnetic and acoustic noises were evoked in a single variant martensitic Ni2MnGa single crystal (produced by uniaxial compression) by application of an external magnetic field along the hard magnetization direction. It is shown that after reaching the detwinning threshold, spontaneous reorientation of martensite variants (twins) leads not only to acoustic emission but magnetic two-directional noises as well. At small magnetic fields, below the above threshold, unidirectional magnetic emission is also observed and attributed to a Barkhausen-type noise due to magnetic domain wall motions during magnetization along the hard direction. After the above first run, in cycles of decreasing and increasing magnetic field, at low-field values, weak, unidirectional Barkhausen noise is detected and attributed to the discontinuous motion of domain walls during magnetization along the easy magnetization direction. The magnetic noise is also measured by constraining the sample in the same initial variant state along the hard direction and, after the unidirectional noise (as obtained also in the first run), a two-directional noise package is developed and it is attributed to domain rotations. From the statistical analysis of the above noises, the critical exponents, characterizing the power-law behavior, are calculated and compared with each other and with the literature data. Time correlations within the magnetic as well as acoustic signals lead to a common scaled power function (with β =-1.25 exponent) for both types of signals.
An application of reactor noise techniques to neutron transport problems in a random medium
International Nuclear Information System (INIS)
Sahni, D.C.
1989-01-01
Neutron transport problems in a random medium are considered by defining a joint Markov process describing the fluctuations of one neutron population and the random changes in the medium. Backward Chapman-Kolmogorov equations are derived which yield an adjoint transport equation for the average neutron density. It is shown that this average density also satisfied the direct transport equation as given by the phenomenological model. (author)
Achieving high signal-to-noise performance for a velocity-map imaging experiment
International Nuclear Information System (INIS)
Roberts, E.H.; Cavanagh, S.J.; Gibson, S.T.; Lewis, B.R.; Dedman, C.J.; Picker, G.J.
2005-01-01
Since the publication of the pioneering paper on velocity-map imaging in 1997, by Eppink and Parker [A.T.J.B. Eppink, D.H. Parker, Rev. Sci. Instrum. 68 (1997) 3477], numerous groups have applied this method in a variety of ways and to various targets. However, despite this interest, little attention has been given to the inherent difficulties and problems associated with this method. In implementing a velocity-map imaging system for photoelectron spectroscopy for the photo-detachment of anion radicals, we have developed a coaxial velocity-map imaging spectrometer. Examined are the advantages and disadvantages of such a system, in particular the sources of noise and the methods used to reduce it
An evaluation of neural networks for identification of system parameters in reactor noise signals
International Nuclear Information System (INIS)
Miller, L.F.
1991-01-01
Several backpropagation neural networks for identifying fundamental mode eigenvalues were evaluated. The networks were trained and tested on analytical data and on results from other numerical methods. They were then used to predict first mode break frequencies for noise data from several sources. These predictions were, in turn, compared with analytical values and with results from alternative methods. Comparisons of results for some data sets suggest that the accuracy of predictions from neural networks are essentially equivalent to results from conventional methods while other evaluations indicate that either method may be superior. Experience gained from these numerical experiments provide insight for improving the performance of neural networks relative to other methods for identifying parameters associated with experimental data. Neural networks may also be used in support of conventional algorithms by providing starting points for nonlinear minimization algorithms
A terahertz EO detector with large dynamical range, high modulation depth and signal-noise ratio
Pan, Xinjian; Cai, Yi; Zeng, Xuanke; Zheng, Shuiqin; Li, Jingzhen; Xu, Shixiang
2017-05-01
The paper presents a novel design for terahertz (THz) free-space time domain electro-optic (EO) detection where the static birefringent phases of the two balanced arms are set close to zero but opposite to each other. Our theoretical and numerical analyses show this design has much stronger ability to cancel the optical background noise than both THz ellipsometer and traditional crossed polarizer geometry (CPG). Its optical modulation depth is about twice as high as that of traditional CPG, but about ten times as high as that of THz ellipsometer. As for the dynamical range, our improved design is comparable to the THz ellipsometer but obviously larger than the traditional CPG. Some experiments for comparing our improved CPG with traditional CPG agree well with the corresponding theoretical predictions. Our experiments also show that the splitting ratio of the used non-polarization beam splitter is critical for the performance of our design.
Gkoktsi, Kyriaki; Giaralis, Agathoklis; TauSiesakul, Bamrung
2016-04-01
Motivated by a need to reduce energy consumption in wireless sensors for vibration-based structural health monitoring (SHM) associated with data acquisition and transmission, this paper puts forth a novel approach for undertaking operational modal analysis (OMA) and damage localization relying on compressed vibrations measurements sampled at rates well below the Nyquist rate. Specifically, non-uniform deterministic sub-Nyquist multi-coset sampling of response acceleration signals in white noise excited linear structures is considered in conjunction with a power spectrum blind sampling/estimation technique which retrieves/samples the power spectral density matrix from arrays of sensors directly from the sub-Nyquist measurements (i.e., in the compressed domain) without signal reconstruction in the time-domain and without posing any signal sparsity conditions. The frequency domain decomposition algorithm is then applied to the power spectral density matrix to extract natural frequencies and mode shapes as a standard OMA step. Further, the modal strain energy index (MSEI) is considered for damage localization based on the mode shapes extracted directly from the compressed measurements. The effectiveness and accuracy of the proposed approach is numerically assessed by considering simulated vibration data pertaining to a white-noise excited simply supported beam in healthy and in 3 damaged states, contaminated with Gaussian white noise. Good accuracy is achieved in estimating mode shapes (quantified in terms of the modal assurance criterion) and natural frequencies from an array of 15 multi-coset devices sampling at a 70% slower than the Nyquist frequency rate for SNRs as low as 10db. Damage localization of equal level/quality is also achieved by the MSEI applied to mode shapes derived from noisy sub-Nyquist (70% compression) and Nyquist measurements for all damaged states considered. Overall, the furnished numerical results demonstrate that the herein considered sub
A multilevel system of algorithms for detecting and isolating signals in a background of noise
Gurin, L. S.; Tsoy, K. A.
1978-01-01
Signal information is processed with the help of algorithms, and then on the basis of such processing, a part of the information is subjected to further processing with the help of more precise algorithms. Such a system of algorithms is studied, a comparative evaluation of a series of lower level algorithms is given, and the corresponding algorithms of higher level are characterized.
On the Measurement of Criterion Noise in Signal Detection Theory: The Case of Recognition Memory
Kellen, David; Klauer, Karl Christoph; Singmann, Henrik
2012-01-01
Traditional approaches within the framework of signal detection theory (SDT; Green & Swets, 1966), especially in the field of recognition memory, assume that the positioning of response criteria is not a noisy process. Recent work (Benjamin, Diaz, & Wee, 2009; Mueller & Weidemann, 2008) has challenged this assumption, arguing not only…
The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible un...
Directory of Open Access Journals (Sweden)
A. L. Senyavskiy
2015-01-01
Full Text Available The article analyzes the robustness of the digital demodulator of the signal with the lowest frequency shift keying at a subcarrier frequency with respect to non-Gaussian interference type of atmospheric, industrial noise and interfering frequency -and phase-shift keyed signals. This type of demodulator is used for the transmission of navigation data in the systems of air traffic control with automatic dependent surveillance.
Wang, Feng-Fei; Luo, A-Li; Zhao, Yong-Heng
2014-02-01
The radial velocity of the star is very important for the study of the dynamics structure and chemistry evolution of the Milky Way, is also an useful tool for looking for variable or special objects. In the present work, we focus on calculating the radial velocity of different spectral types of low-resolution stellar spectra by adopting a template matching method, so as to provide effective and reliable reference to the different aspects of scientific research We choose high signal-to-noise ratio (SNR) spectra of different spectral type stellar from the Sloan Digital Sky Survey (SDSS), and add different noise to simulate the stellar spectra with different SNR. Then we obtain theradial velocity measurement accuracy of different spectral type stellar spectra at different SNR by employing a template matching method. Meanwhile, the radial velocity measurement accuracy of white dwarf stars is analyzed as well. We concluded that the accuracy of radial velocity measurements of early-type stars is much higher than late-type ones. For example, the 1-sigma standard error of radial velocity measurements of A-type stars is 5-8 times as large as K-type and M-type stars. We discuss the reason and suggest that the very narrow lines of late-type stars ensure the accuracy of measurement of radial velocities, while the early-type stars with very wide Balmer lines, such as A-type stars, become sensitive to noise and obtain low accuracy of radial velocities. For the spectra of white dwarfs stars, the standard error of radial velocity measurement could be over 50 km x s(-1) because of their extremely wide Balmer lines. The above conclusion will provide a good reference for stellar scientific study.
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.
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.
International Nuclear Information System (INIS)
Raymond, V; Mandel, I; Kalogera, V; Van der Sluys, M V; Roever, C; Christensen, N
2010-01-01
Gravitational-wave signals from inspirals of binary compact objects (black holes and neutron stars) are primary targets of the ongoing searches by ground-based gravitational-wave (GW) interferometers (LIGO, Virgo and GEO-600). We present parameter estimation results from our Markov-chain Monte Carlo code SPINspiral on signals from binaries with precessing spins. Two data sets are created by injecting simulated GW signals either into synthetic Gaussian noise or into LIGO detector data. We compute the 15-dimensional probability-density functions (PDFs) for both data sets, as well as for a data set containing LIGO data with a known, loud artefact ('glitch'). We show that the analysis of the signal in detector noise yields accuracies similar to those obtained using simulated Gaussian noise. We also find that while the Markov chains from the glitch do not converge, the PDFs would look consistent with a GW signal present in the data. While our parameter estimation results are encouraging, further investigations into how to differentiate an actual GW signal from noise are necessary.
Li, Bicen; Xu, Pengmei; Hou, Lizhou; Wang, Caiqin
2017-10-01
Taking the advantages of high spectral resolution, high sensitivity and wide spectral coverage, space borne Fourier transform infrared spectrometer (FTS) plays more and more important role in atmospheric composition sounding. The combination of solar occultation and FTS technique improves the sensitivity of instrument. To achieve both high spectral resolution and high signal to noise ratio (SNR), reasonable allocation and optimization for instrument parameters are the foundation and difficulty. The solar occultation FTS (SOFTS) is a high spectral resolution (0.03 cm-1) FTS operating from 2.4 to 13.3 μm (750-4100cm-1), which will determine the altitude profile information of typical 10-100km for temperature, pressure, and the volume mixing ratios for several dozens of atmospheric compositions. As key performance of SOFTS, SNR is crucially important to high accuracy retrieval of atmospheric composition, which is required to be no less than 100:1 at the radiance of 5800K blackbody. Based on the study of various parameters and its interacting principle, according to interference theory and operation principle of time modulated FTS, a simulation model of FTS SNR has been built, which considers satellite orbit, spectral radiometric features of sun and atmospheric composition, optical system, interferometer and its control system, measurement duration, detector sensitivity, noise of detector and electronic system and so on. According to the testing results of SNR at the illuminating of 1000 blackbody, the on-orbit SNR performance of SOFTS is estimated, which can meet the mission requirement.
Low-power low-noise analog circuits for on-focal-plane signal processing of infrared sensors
Pain, Bedabrata; Mendis, Sunetra K.; Schober, Robert C.; Nixon, Robert H.; Fossum, Eric R.
1993-10-01
On-focal-plane signal processing circuits for enhancement of IR imager performance are presented. To enable the detection of high background IR images, an in-pixel current-mode background suppression scheme is presented. The background suppression circuit consists of a current memory placed in the feedback loop of a CTIA and is designed for a thousand-fold suppression of the background flux, thereby easing circuit design constraints, and assuring BLIP operation even with detectors having large response non-uniformities. For improving the performance of low-background IR imagers, an on-chip column-parallel analog-to-digital converter (ADC) is presented. The design of a 10-bit ADC with 50 micrometers pitch and based on sigma-delta ((Sigma) -(Delta) ) modulation is presented. A novel IR imager readout technique featuring photoelectron counting in the unit cell is presented for ultra-low background applications. The output of the unit cell is a digital word corresponding to the incident flux density and the readout is noise free. The design of low-power (noise, high-gain (> 100,000), small real estate (60 micrometers pitch) self-biased CMOS amplifiers required for photon counting are presented.
Chen, Yanan; Qi, Jianguo; Huang, Jing; Zhou, Xiaomin; Niu, Linqiang; Yan, Zhijie; Wang, Jianhong
2018-01-01
Herein, we reported a yellow emission probe 1-methyl-4-(6-morpholino-1, 3-dioxo-1H-benzo[de]isoquinolin-2(3H)-yl) pyridin-1-ium iodide which could specifically stain mitochondria in living immortalized and normal cells. In comparison to the common mitochondria tracker (Mitotracker Deep Red, MTDR), this probe was nontoxic, photostable and ultrahigh signal-to-noise ratio, which could real-time monitor mitochondria for a long time. Moreover, this probe also showed high sensitivity towards mitochondrial membrane potential and intramitochondrial viscosity change. Consequently, this probe was used for imaging mitochondria, detecting changes in mitochondrial membrane potential and intramitochondrial viscosity in physiological and pathological processes.
Signal-to-noise optimization and evaluation of a home-made visible diode-array spectrophotometer
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
Directory of Open Access Journals (Sweden)
Kim Pansoo
2009-01-01
Full Text Available Recent standards for wireless transmission require reliable synchronization for channels with low signal-to-noise ratio (SNR as well as with a large amount of frequency offset, which necessitates a robust correlator structure for the initial frame synchronization process. In this paper, a new correlation strategy especially targeted for low SNR regions is proposed and its performance is analyzed. By utilizing a modified energy correction term, the proposed method effectively reduces the variance of the decision variable to enhance the detection performance. Most importantly, the method is demonstrated to outperform all previously reported schemes by a significant margin, for SNRs below 5 dB regardless of the existence of the frequency offsets. A variation of the proposed method is also presented for further enhancement over the channels with small frequency errors. The particular application considered for the performance verification is the second generation digital video broadcasting system for satellites (DVB-S2.
International Nuclear Information System (INIS)
Murakami, Koichi; Yoshida, Koji; Yanagimoto, Shinichi
2012-01-01
We studied the position dependent influence that sensitivity correction processing gave the signal-to-noise ratio (SNR) measurement of parallel imaging (PI). Sensitivity correction processing that referred to the sensitivity distribution of the body coil improved regional uniformity more than the sensitivity uniformity correction filter with a fixed correction factor. In addition, the position dependent influence to give the SNR measurement in PI was different from the sensitivity correction processing. Therefore, if we divide SNR of the sensitivity correction processing image by SNR of the original image in each pixel and calculate SNR ratio, we can show the position dependent influence that sensitivity correction processing gives the SNR measurement in PI. It is with an index of the sensitivity correction processing precision. (author)