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

Directory of Open Access Journals (Sweden)

Edward Nuhfer

2016-01-01

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

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

Science.gov (United States)

Kishoni, Doron; Pietsch, Benjamin E.

1989-01-01

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

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)

Realistic noise-tolerant randomness amplification using finite number of devices

Science.gov (United States)

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.

Audibility of modulation noise in stationary signals

NARCIS (Netherlands)

Neelen, J.J.M.

1970-01-01

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

Theory and Measurement of Signal-to-Noise Ratio in Continuous-Wave Noise Radar.

Science.gov (United States)

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.

Signal processing in noise waveform radar

CERN Document Server

Kulpa, Krzysztof

2013-01-01

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

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

Science.gov (United States)

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

2014-01-01

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

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)

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.

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

CERN Document Server

Zakareishvili, Tamar; The ATLAS collaboration

2017-01-01

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

The Signal Importance of Noise

Science.gov (United States)

Macy, Michael; Tsvetkova, Milena

2015-01-01

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

Orbiter CCTV video signal noise analysis

Science.gov (United States)

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

1977-01-01

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

Signal noise/interferer combiner unit programmable (SINCUP)

Science.gov (United States)

Martinezdepison, Emilio

1988-12-01

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

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)

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

Science.gov (United States)

Bordelon, D. L.

1977-01-01

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

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

Science.gov (United States)

Wang, Yuzhao; Luo, Pingping

2014-10-01

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

Advanced digital signal processing and noise reduction

CERN Document Server

Vaseghi, Saeed V

2008-01-01

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

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

Directory of Open Access Journals (Sweden)

Shuqiang Wang

2014-01-01

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

Covariance-Based Estimation from Multisensor Delayed Measurements with Random Parameter Matrices and Correlated Noises

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.

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.

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)

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

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...

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

Science.gov (United States)

Bordelon, D. L.

1976-01-01

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

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

Science.gov (United States)

Helton, William Stokely

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

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

Science.gov (United States)

Makra, Peter; Gingl, Zoltan

2003-05-01

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

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

Science.gov (United States)

Ma, Xin; Xiang, Chengzhi; Gong, Wei

2016-06-01

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

Removing Background Noise with Phased Array Signal Processing

Science.gov (United States)

Podboy, Gary; Stephens, David

2015-01-01

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

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

Science.gov (United States)

Kong, Dehui; Peng, Zhenming

2015-12-01

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

Empirical mode decomposition of the ECG signal for noise removal

Science.gov (United States)

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

2011-04-01

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

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

Science.gov (United States)

Knacke, R. F.

1978-01-01

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

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.

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

Science.gov (United States)

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

2015-07-15

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

Random Correlation Matrix and De-Noising

OpenAIRE

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...

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

Science.gov (United States)

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

2018-01-01

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

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.

Indirect estimation of signal-dependent noise with nonadaptive heterogeneous samples.

Science.gov (United States)

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.

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

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

Science.gov (United States)

Pain, Bedabrata

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

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...

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

Science.gov (United States)

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

2017-02-01

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

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

Science.gov (United States)

Kondo, K; Ichioka, Y; Suzuki, T

1977-09-01

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

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.

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

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

Science.gov (United States)

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

2018-01-01

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

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.

Comparison of methods for removing electromagnetic noise from electromyographic signals.

Science.gov (United States)

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

2012-02-01

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

Comparison of methods for removing electromagnetic noise from electromyographic signals

International Nuclear Information System (INIS)

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

2012-01-01

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

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

Science.gov (United States)

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

1997-01-01

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

Seismic signal and noise on Europa

Science.gov (United States)

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

2017-10-01

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

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

Science.gov (United States)

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

2010-01-01

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

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.

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.

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

Science.gov (United States)

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

2018-04-01

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

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...

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

Science.gov (United States)

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

1989-03-01

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

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)

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

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)

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

Directory of Open Access Journals (Sweden)

Shoji Kawahito

2016-11-01

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

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

Directory of Open Access Journals (Sweden)

Omar Eldwaik

2018-01-01

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

Photonic microwave signals with zeptosecond-level absolute timing noise

Science.gov (United States)

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

2017-01-01

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

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

Science.gov (United States)

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

2018-04-01

Agatha is a framework of periodograms to disentangle periodic signals from correlated noise and to solve the two-dimensional model selection problem: signal dimension and noise model dimension. These periodograms are calculated by applying likelihood maximization and marginalization and combined in a self-consistent way. Agatha can be used to select the optimal noise model and to test the consistency of signals in time and can be applied to time series analyses in other astronomical and scientific disciplines. An interactive web implementation of the software is also available at http://agatha.herts.ac.uk/.

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

Science.gov (United States)

Sundry, J. L.

1966-01-01

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

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

Science.gov (United States)

Jinxia, Feng; Yuanji, Li; Kuanshou, Zhang

2018-04-01

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

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)

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

Balanced detection for self-mixing interferometry to improve signal-to-noise ratio

Science.gov (United States)

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.

Channel noise enhances signal detectability in a model of acoustic neuron through the stochastic resonance paradigm.

Science.gov (United States)

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.

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.

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.

Microwave noise detection of a quantum dot with stub impedance matching

OpenAIRE

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...

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....

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

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

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.

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

Science.gov (United States)

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

2016-03-01

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

Noise estimation for remote sensing image data analysis

Science.gov (United States)

Du, Qian

2004-01-01

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

Reactor dynamics experiment of nuclear ship Mutsu using pseudo random signal (II). The second experiment

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)

Reactor dynamics experiment of nuclear ship Mutsu using pseudo random signal (III). The third experiment

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)

Reducing Noise by Repetition: Introduction to Signal Averaging

Science.gov (United States)

Hassan, Umer; Anwar, Muhammad Sabieh

2010-01-01

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

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

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

Science.gov (United States)

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

2017-07-01

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

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.

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.

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

Directory of Open Access Journals (Sweden)

Silke Neumann

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

Light field reconstruction robust to signal dependent noise

Science.gov (United States)

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

2014-11-01

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

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.

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.

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.

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

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

Science.gov (United States)

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

2017-02-07

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

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.

Measurement time and statistics for a noise thermometer with a synthetic-noise reference

Science.gov (United States)

White, D. R.; Benz, S. P.; Labenski, J. R.; Nam, S. W.; Qu, J. F.; Rogalla, H.; Tew, W. L.

2008-08-01

This paper describes methods for reducing the statistical uncertainty in measurements made by noise thermometers using digital cross-correlators and, in particular, for thermometers using pseudo-random noise for the reference signal. First, a discrete-frequency expression for the correlation bandwidth for conventional noise thermometers is derived. It is shown how an alternative frequency-domain computation can be used to eliminate the spectral response of the correlator and increase the correlation bandwidth. The corresponding expressions for the uncertainty in the measurement of pseudo-random noise in the presence of uncorrelated thermal noise are then derived. The measurement uncertainty in this case is less than that for true thermal-noise measurements. For pseudo-random sources generating a frequency comb, an additional small reduction in uncertainty is possible, but at the cost of increasing the thermometer's sensitivity to non-linearity errors. A procedure is described for allocating integration times to further reduce the total uncertainty in temperature measurements. Finally, an important systematic error arising from the calculation of ratios of statistical variables is described.

Approximations to camera sensor noise

Science.gov (United States)

Jin, Xiaodan; Hirakawa, Keigo

2013-02-01

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

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.

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)

ELLIPTICAL WEIGHTED HOLICs FOR WEAK LENSING SHEAR MEASUREMENT. III. THE EFFECT OF RANDOM COUNT NOISE ON IMAGE MOMENTS IN WEAK LENSING ANALYSIS

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.

A signal theoretic introduction to random processes

CERN Document Server

Howard, Roy M

2015-01-01

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

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)

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

Science.gov (United States)

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

2004-02-01

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

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

NARCIS (Netherlands)

van der Wel, A.P.

2005-01-01

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

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

Science.gov (United States)

Yasin, Ifat; Henning, G Bruce

2012-07-01

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

Benchmarking the Algorithms to Detect Seasonal Signals Under Different Noise Conditions

Science.gov (United States)

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

2017-12-01

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

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

Science.gov (United States)

Hultgren, Lennart S.; Arechiga, Rene O.

2016-01-01

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

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

International Nuclear Information System (INIS)

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

2008-01-01

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

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

CERN Document Server

Bottacchi, Stefano

2008-01-01

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

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

Directory of Open Access Journals (Sweden)

F. Bagheri

2013-02-01

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

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

Directory of Open Access Journals (Sweden)

Artur Zacniewski

2015-09-01

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

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

Science.gov (United States)

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

2007-10-01

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

New high resolution Random Telegraph Noise (RTN) characterization method for resistive RAM

Science.gov (United States)

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.

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

International Nuclear Information System (INIS)

Doherty, W.

2013-01-01

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

Measurement of MOSFET LF Noise Under Large Signal RF Excitation

NARCIS (Netherlands)

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

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

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

Fast random-number generation using a diode laser's frequency noise characteristic

Science.gov (United States)

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".

Signal Detection with Criterion Noise: Applications to Recognition Memory

Science.gov (United States)

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

2009-01-01

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

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).

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

National Research Council Canada - National Science Library

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

2008-01-01

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

A high speed digital noise generator

Science.gov (United States)

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.

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

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.

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.

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.

Effect of drain current on appearance probability and amplitude of random telegraph noise in low-noise CMOS image sensors

Science.gov (United States)

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.

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.

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

Science.gov (United States)

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

2016-12-01

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

Real Time Phase Noise Meter Based on a Digital Signal Processor

Science.gov (United States)

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

2006-01-01

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

Pervasive randomness in physics: an introduction to its modelling and spectral characterisation

Science.gov (United States)

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.

Is fMRI "noise" really noise? Resting state nuisance regressors remove variance with network structure.

Science.gov (United States)

Bright, Molly G; Murphy, Kevin

2015-07-01

Noise correction is a critical step towards accurate mapping of resting state BOLD fMRI connectivity. Noise sources related to head motion or physiology are typically modelled by nuisance regressors, and a generalised linear model is applied to regress out the associated signal variance. In this study, we use independent component analysis (ICA) to characterise the data variance typically discarded in this pre-processing stage in a cohort of 12 healthy volunteers. The signal variance removed by 24, 12, 6, or only 3 head motion parameters demonstrated network structure typically associated with functional connectivity, and certain networks were discernable in the variance extracted by as few as 2 physiologic regressors. Simulated nuisance regressors, unrelated to the true data noise, also removed variance with network structure, indicating that any group of regressors that randomly sample variance may remove highly structured "signal" as well as "noise." Furthermore, to support this we demonstrate that random sampling of the original data variance continues to exhibit robust network structure, even when as few as 10% of the original volumes are considered. Finally, we examine the diminishing returns of increasing the number of nuisance regressors used in pre-processing, showing that excessive use of motion regressors may do little better than chance in removing variance within a functional network. It remains an open challenge to understand the balance between the benefits and confounds of noise correction using nuisance regressors. Copyright © 2015. Published by Elsevier Inc.

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

Science.gov (United States)

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

2016-02-01

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

Listening to the Noise: Random Fluctuations Reveal Gene Network Parameters

Science.gov (United States)

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.

Stochastic model for detection of signals in noise

OpenAIRE

Klein, Stanley A.; Levi, Dennis M.

2009-01-01

Fifty years ago Birdsall, Tanner, and colleagues made rapid progress in developing signal detection theory into a powerful psychophysical tool. One of their major insights was the utility of adding external noise to the signals of interest. These methods have been enhanced in recent years by the addition of multipass and classification-image methods for opening up the black box. There remain a number of as yet unresolved issues. In particular, Birdsall developed a theorem that large amounts o...

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

Science.gov (United States)

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

2015-04-01

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

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.)

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.

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)

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

International Nuclear Information System (INIS)

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

2009-01-01

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

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

Science.gov (United States)

Chen, Szi-Wen; Chen, Yuan-Ho

2015-10-16

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

Noise Gating Solar Images

Science.gov (United States)

DeForest, Craig; Seaton, Daniel B.; Darnell, John A.

2017-08-01

I present and demonstrate a new, general purpose post-processing technique, "3D noise gating", that can reduce image noise by an order of magnitude or more without effective loss of spatial or temporal resolution in typical solar applications.Nearly all scientific images are, ultimately, limited by noise. Noise can be direct Poisson "shot noise" from photon counting effects, or introduced by other means such as detector read noise. Noise is typically represented as a random variable (perhaps with location- or image-dependent characteristics) that is sampled once per pixel or once per resolution element of an image sequence. Noise limits many aspects of image analysis, including photometry, spatiotemporal resolution, feature identification, morphology extraction, and background modeling and separation.Identifying and separating noise from image signal is difficult. The common practice of blurring in space and/or time works because most image "signal" is concentrated in the low Fourier components of an image, while noise is evenly distributed. Blurring in space and/or time attenuates the high spatial and temporal frequencies, reducing noise at the expense of also attenuating image detail. Noise-gating exploits the same property -- "coherence" -- that we use to identify features in images, to separate image features from noise.Processing image sequences through 3-D noise gating results in spectacular (more than 10x) improvements in signal-to-noise ratio, while not blurring bright, resolved features in either space or time. This improves most types of image analysis, including feature identification, time sequence extraction, absolute and relative photometry (including differential emission measure analysis), feature tracking, computer vision, correlation tracking, background modeling, cross-scale analysis, visual display/presentation, and image compression.I will introduce noise gating, describe the method, and show examples from several instruments (including SDO

Time response measurements of pressure sensors using pink noise technique

International Nuclear Information System (INIS)

Pereira, Iraci Martinez; Santos, Roberto Carlos dos

2009-01-01

This work presents an experimental setup for Pink Noise method application on pressure transmitters' response times. The Pink Noise method consists on injecting artificial pressure noise into the pressure transmitter. The artificial pressure noise is generated using a current-to-pressure (I-to-P) converter, which is driven by a random noise signal generator. The output pressure transmitter noise is then analyzed using conventional Noise Analysis Technique. Noise signals may be interpreted using spectral techniques or empirical time series models. The frequency domain method consists of evaluating the Power Spectral Density (PSD) function. The information needed for time constant estimation can be obtained by fitting an all-pole transfer function to this power spectral density. (author)

Noise Reduction of Steel Cord Conveyor Belt Defect Electromagnetic Signal by Combined Use of Improved Wavelet and EMD

Directory of Open Access Journals (Sweden)

Hong-Wei Ma

2016-09-01

Full Text Available In order to reduce the noise of a defect electromagnetic signal of the steel cord conveyor belt used in coal mines, a new signal noise reduction method by combined use of the improved threshold wavelet and Empirical Mode Decomposition (EMD is proposed. Firstly, the denoising method based on the improved threshold wavelet is applied to reduce the noise of a defect electromagnetic signal obtained by an electromagnetic testing system. Then, the EMD is used to decompose the denoised signal and then the effective Intrinsic Mode Function (IMF is extracted by the dominant eigenvalue strategy. Finally, the signal reconstruction is carried out by utilizing the obtained IMF. In order to verify the proposed noise reduction method, the experiments are carried out in two cases including the defective joint and steel wire rope break. The experimental results show that the proposed method in this paper obtains the higher Signal to Noise Ratio (SNR for the defect electromagnetic signal noise reduction of steel cord conveyor belts.

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

Directory of Open Access Journals (Sweden)

Liangliang Wei

2018-02-01

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

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

Science.gov (United States)

Rahmatillah, Akif; Ataulkarim

2017-05-01

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

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

Directory of Open Access Journals (Sweden)

Szi-Wen Chen

2015-10-01

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

Digital circuit for the introduction and later removal of dither from an analog signal

Science.gov (United States)

Borgen, Gary S.

1994-05-01

An electronics circuit is presented for accurately digitizing an analog audio or like data signal into a digital equivalent signal by introducing dither into the analog signal and then subsequently removing the dither from the digitized signal prior to its conversion to an analog signal which is a substantial replica of the incoming analog audio or like data signal. The electronics circuit of the present invention is characterized by a first pseudo-random number generator which generates digital random noise signals or dither for addition to the digital equivalent signal and a second pseudo-random number generator which generates subtractive digital random noise signals for the subsequent removal of dither from the digital equivalent signal prior its conversion to the analog replica signal.

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)

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

Science.gov (United States)

Smith, James F.

2017-03-01

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

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

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

Directory of Open Access Journals (Sweden)

Parvin Nassiri

2016-01-01

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

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

Science.gov (United States)

Bourdin, Philippe A.

2015-08-01

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

The psychosis-like effects of Δ(9)-tetrahydrocannabinol are associated with increased cortical noise in healthy humans.

Science.gov (United States)

Cortes-Briones, Jose A; Cahill, John D; Skosnik, Patrick D; Mathalon, Daniel H; Williams, Ashley; Sewell, R Andrew; Roach, Brian J; Ford, Judith M; Ranganathan, Mohini; D'Souza, Deepak Cyril

2015-12-01

Drugs that induce psychosis may do so by increasing the level of task-irrelevant random neural activity or neural noise. Increased levels of neural noise have been demonstrated in psychotic disorders. We tested the hypothesis that neural noise could also be involved in the psychotomimetic effects of delta-9-tetrahydrocannabinol (Δ(9)-THC), the principal active constituent of cannabis. Neural noise was indexed by measuring the level of randomness in the electroencephalogram during the prestimulus baseline period of an oddball task using Lempel-Ziv complexity, a nonlinear measure of signal randomness. The acute, dose-related effects of Δ(9)-THC on Lempel-Ziv complexity and signal power were studied in humans (n = 24) who completed 3 test days during which they received intravenous Δ(9)-THC (placebo, .015 and .03 mg/kg) in a double-blind, randomized, crossover, and counterbalanced design. Δ(9)-THC increased neural noise in a dose-related manner. Furthermore, there was a strong positive relationship between neural noise and the psychosis-like positive and disorganization symptoms induced by Δ(9)-THC, which was independent of total signal power. Instead, there was no relationship between noise and negative-like symptoms. In addition, Δ(9)-THC reduced total signal power during both active drug conditions compared with placebo, but no relationship was detected between signal power and psychosis-like symptoms. At doses that produced psychosis-like effects, Δ(9)-THC increased neural noise in humans in a dose-dependent manner. Furthermore, increases in neural noise were related with increases in Δ(9)-THC-induced psychosis-like symptoms but not negative-like symptoms. These findings suggest that increases in neural noise may contribute to the psychotomimetic effects of Δ(9)-THC. Published by Elsevier Inc.

Blind signal processing algorithms under DC biased Gaussian noise

Science.gov (United States)

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

2013-05-01

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

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

Science.gov (United States)

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

2018-03-01

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

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.

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

Science.gov (United States)

Feria, Y.; Statman, J.

1993-01-01

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

Attention-dependent modulation of cortical taste circuits revealed by Granger causality with signal-dependent noise.

Directory of Open Access Journals (Sweden)

Qiang Luo

2013-10-01

Full Text Available We show, for the first time, that in cortical areas, for example the insular, orbitofrontal, and lateral prefrontal cortex, there is signal-dependent noise in the fMRI blood-oxygen level dependent (BOLD time series, with the variance of the noise increasing approximately linearly with the square of the signal. Classical Granger causal models are based on autoregressive models with time invariant covariance structure, and thus do not take this signal-dependent noise into account. To address this limitation, here we describe a Granger causal model with signal-dependent noise, and a novel, likelihood ratio test for causal inferences. We apply this approach to the data from an fMRI study to investigate the source of the top-down attentional control of taste intensity and taste pleasantness processing. The Granger causality with signal-dependent noise analysis reveals effects not identified by classical Granger causal analysis. In particular, there is a top-down effect from the posterior lateral prefrontal cortex to the insular taste cortex during attention to intensity but not to pleasantness, and there is a top-down effect from the anterior and posterior lateral prefrontal cortex to the orbitofrontal cortex during attention to pleasantness but not to intensity. In addition, there is stronger forward effective connectivity from the insular taste cortex to the orbitofrontal cortex during attention to pleasantness than during attention to intensity. These findings indicate the importance of explicitly modeling signal-dependent noise in functional neuroimaging, and reveal some of the processes involved in a biased activation theory of selective attention.

Signal and noise modeling in confocal laser scanning fluorescence microscopy.

Science.gov (United States)

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

2012-01-01

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

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

CERN Document Server

Savaux, Vincent

2014-01-01

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

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

Institute of Scientific and Technical Information of China (English)

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

2007-01-01

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

Non-stationary least-squares complex decomposition for microseismic noise attenuation

Science.gov (United States)

Chen, Yangkang

2018-06-01

Microseismic data processing and imaging are crucial for subsurface real-time monitoring during hydraulic fracturing process. Unlike the active-source seismic events or large-scale earthquake events, the microseismic event is usually of very small magnitude, which makes its detection challenging. The biggest trouble of microseismic data is the low signal-to-noise ratio issue. Because of the small energy difference between effective microseismic signal and ambient noise, the effective signals are usually buried in strong random noise. I propose a useful microseismic denoising algorithm that is based on decomposing a microseismic trace into an ensemble of components using least-squares inversion. Based on the predictive property of useful microseismic event along the time direction, the random noise can be filtered out via least-squares fitting of multiple damping exponential components. The method is flexible and almost automated since the only parameter needed to be defined is a decomposition number. I use some synthetic and real data examples to demonstrate the potential of the algorithm in processing complicated microseismic data sets.

Musical noise reduction using an adaptive filter

Science.gov (United States)

Hanada, Takeshi; Murakami, Takahiro; Ishida, Yoshihisa; Hoya, Tetsuya

2003-10-01

This paper presents a method for reducing a particular noise (musical noise). The musical noise is artificially produced by Spectral Subtraction (SS), which is one of the most conventional methods for speech enhancement. The musical noise is the tin-like sound and annoying in human auditory. We know that the duration of the musical noise is considerably short in comparison with that of speech, and that the frequency components of the musical noise are random and isolated. In the ordinary SS-based methods, the musical noise is removed by the post-processing. However, the output of the ordinary post-processing is delayed since the post-processing uses the succeeding frames. In order to improve this problem, we propose a novel method using an adaptive filter. In the proposed system, the observed noisy signal is used as the input signal to the adaptive filter and the output of SS is used as the reference signal. In this paper we exploit the normalized LMS (Least Mean Square) algorithm for the adaptive filter. Simulation results show that the proposed method has improved the intelligibility of the enhanced speech in comparison with the conventional method.

A homology sound-based algorithm for speech signal interference

Science.gov (United States)

Jiang, Yi-jiao; Chen, Hou-jin; Li, Ju-peng; Zhang, Zhan-song

2015-12-01

Aiming at secure analog speech communication, a homology sound-based algorithm for speech signal interference is proposed in this paper. We first split speech signal into phonetic fragments by a short-term energy method and establish an interference noise cache library with the phonetic fragments. Then we implement the homology sound interference by mixing the randomly selected interferential fragments and the original speech in real time. The computer simulation results indicated that the interference produced by this algorithm has advantages of real time, randomness, and high correlation with the original signal, comparing with the traditional noise interference methods such as white noise interference. After further studies, the proposed algorithm may be readily used in secure speech communication.

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

Science.gov (United States)

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

2009-03-15

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

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.

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

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...

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.

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

Science.gov (United States)

Wagman, Michael L.

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

FOG Random Drift Signal Denoising Based on the Improved AR Model and Modified Sage-Husa Adaptive Kalman Filter.

Science.gov (United States)

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.

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

Science.gov (United States)

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

2014-01-01

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

A note on errors and signal to noise ratio of binary cross-correlation measurements of system impulse response

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)

A note on errors and signal to noise ratio of binary cross-correlation measurements of system impulse response

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)

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.

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

Science.gov (United States)

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

2016-01-01

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

Lidar signal-to-noise ratio improvements: Considerations and techniques

Science.gov (United States)

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

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.

High-frequency signal and noise estimates of CSR GRACE RL04

Science.gov (United States)

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

2012-12-01

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

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.)

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

Science.gov (United States)

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

2015-03-01

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

Study of improving signal-noise ratio for fluorescence channel

Science.gov (United States)

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

2017-10-01

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

Noise reduction in Lidar signal using correlation-based EMD combined with soft thresholding and roughness penalty

Science.gov (United States)

Chang, Jianhua; Zhu, Lingyan; Li, Hongxu; Xu, Fan; Liu, Binggang; Yang, Zhenbo

2018-01-01

Empirical mode decomposition (EMD) is widely used to analyze the non-linear and non-stationary signals for noise reduction. In this study, a novel EMD-based denoising method, referred to as EMD with soft thresholding and roughness penalty (EMD-STRP), is proposed for the Lidar signal denoising. With the proposed method, the relevant and irrelevant intrinsic mode functions are first distinguished via a correlation coefficient. Then, the soft thresholding technique is applied to the irrelevant modes, and the roughness penalty technique is applied to the relevant modes to extract as much information as possible. The effectiveness of the proposed method was evaluated using three typical signals contaminated by white Gaussian noise. The denoising performance was then compared to the denoising capabilities of other techniques, such as correlation-based EMD partial reconstruction, correlation-based EMD hard thresholding, and wavelet transform. The use of EMD-STRP on the measured Lidar signal resulted in the noise being efficiently suppressed, with an improved signal to noise ratio of 22.25 dB and an extended detection range of 11 km.

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

NARCIS (Netherlands)

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

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

Effects of signal modulation and coloured cross-correlation of coloured noises on the diffusion of a harmonic oscillator

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.

Effects of signal modulation and coloured cross-correlation of coloured noises on the diffusion of a harmonic oscillator

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)

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.

Multifractal detrended fluctuation analysis of analog random multiplicative processes

Energy Technology Data Exchange (ETDEWEB)

Silva, L.B.M.; Vermelho, M.V.D. [Instituto de Fisica, Universidade Federal de Alagoas, Maceio - AL, 57072-970 (Brazil); Lyra, M.L. [Instituto de Fisica, Universidade Federal de Alagoas, Maceio - AL, 57072-970 (Brazil)], E-mail: marcelo@if.ufal.br; Viswanathan, G.M. [Instituto de Fisica, Universidade Federal de Alagoas, Maceio - AL, 57072-970 (Brazil)

2009-09-15

We investigate non-Gaussian statistical properties of stationary stochastic signals generated by an analog circuit that simulates a random multiplicative process with weak additive noise. The random noises are originated by thermal shot noise and avalanche processes, while the multiplicative process is generated by a fully analog circuit. The resulting signal describes stochastic time series of current interest in several areas such as turbulence, finance, biology and environment, which exhibit power-law distributions. Specifically, we study the correlation properties of the signal by employing a detrended fluctuation analysis and explore its multifractal nature. The singularity spectrum is obtained and analyzed as a function of the control circuit parameter that tunes the asymptotic power-law form of the probability distribution function.

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

Directory of Open Access Journals (Sweden)

Shoaib Mobien

2011-01-01

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

White Gaussian Noise - Models for Engineers

Science.gov (United States)

Jondral, Friedrich K.

2018-04-01

This paper assembles some information about white Gaussian noise (WGN) and its applications. It starts from a description of thermal noise, i. e. the irregular motion of free charge carriers in electronic devices. In a second step, mathematical models of WGN processes and their most important parameters, especially autocorrelation functions and power spectrum densities, are introduced. In order to proceed from mathematical models to simulations, we discuss the generation of normally distributed random numbers. The signal-to-noise ratio as the most important quality measure used in communications, control or measurement technology is accurately introduced. As a practical application of WGN, the transmission of quadrature amplitude modulated (QAM) signals over additive WGN channels together with the optimum maximum likelihood (ML) detector is considered in a demonstrative and intuitive way.

Theoretical and experimental signal-to-noise ratio assessment in new direction sensing continuous-wave Doppler lidar

DEFF Research Database (Denmark)

Pedersen, Anders Tegtmeier; Foroughi Abari, Farzad; Mann, Jakob

2014-01-01

A new direction sensing continuous-wave Doppler lidar based on an image-reject homodyne receiver has recently been demonstrated at DTU Wind Energy, Technical University of Denmark. In this contribution we analyse the signal-to-noise ratio resulting from two different data processing methods both...... leading to the direction sensing capability. It is found that using the auto spectrum of the complex signal to determine the wind speed leads to a signal-to-noise ratio equivalent to that of a standard self-heterodyne receiver. Using the imaginary part of the cross spectrum to estimate the Doppler shift...... has the benefit of a zero-mean background spectrum, but comes at the expense of a decrease in the signal-to noise ratio by a factor of √2....

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

Science.gov (United States)

Karagiannis, Alexandros; Constantinou, Philip

2011-01-01

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

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.

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

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

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

Science.gov (United States)

Ying, Rex; Wall, Christine E

2016-12-08

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

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

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 ...

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)

Measurements of noise immission from wind turbines at receptor locations: Use of a vertical microphone board to improve the signal-to-noise ratio

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

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...

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

LENUS (Irish Health Repository)

Murphy, Peter J

2008-03-01

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

Accurate estimation of camera shot noise in the real-time

Science.gov (United States)

Cheremkhin, Pavel A.; Evtikhiev, Nikolay N.; Krasnov, Vitaly V.; Rodin, Vladislav G.; Starikov, Rostislav S.

2017-10-01

Nowadays digital cameras are essential parts of various technological processes and daily tasks. They are widely used in optics and photonics, astronomy, biology and other various fields of science and technology such as control systems and video-surveillance monitoring. One of the main information limitations of photo- and videocameras are noises of photosensor pixels. Camera's photosensor noise can be divided into random and pattern components. Temporal noise includes random noise component while spatial noise includes pattern noise component. Temporal noise can be divided into signal-dependent shot noise and signal-nondependent dark temporal noise. For measurement of camera noise characteristics, the most widely used methods are standards (for example, EMVA Standard 1288). It allows precise shot and dark temporal noise measurement but difficult in implementation and time-consuming. Earlier we proposed method for measurement of temporal noise of photo- and videocameras. It is based on the automatic segmentation of nonuniform targets (ASNT). Only two frames are sufficient for noise measurement with the modified method. In this paper, we registered frames and estimated shot and dark temporal noises of cameras consistently in the real-time. The modified ASNT method is used. Estimation was performed for the cameras: consumer photocamera Canon EOS 400D (CMOS, 10.1 MP, 12 bit ADC), scientific camera MegaPlus II ES11000 (CCD, 10.7 MP, 12 bit ADC), industrial camera PixeLink PL-B781F (CMOS, 6.6 MP, 10 bit ADC) and video-surveillance camera Watec LCL-902C (CCD, 0.47 MP, external 8 bit ADC). Experimental dependencies of temporal noise on signal value are in good agreement with fitted curves based on a Poisson distribution excluding areas near saturation. Time of registering and processing of frames used for temporal noise estimation was measured. Using standard computer, frames were registered and processed during a fraction of second to several seconds only. Also the

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.

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...

Transform Domain Robust Variable Step Size Griffiths' Adaptive Algorithm for Noise Cancellation in ECG

Science.gov (United States)

Hegde, Veena; Deekshit, Ravishankar; Satyanarayana, P. S.

2011-12-01

The electrocardiogram (ECG) is widely used for diagnosis of heart diseases. Good quality of ECG is utilized by physicians for interpretation and identification of physiological and pathological phenomena. However, in real situations, ECG recordings are often corrupted by artifacts or noise. Noise severely limits the utility of the recorded ECG and thus needs to be removed, for better clinical evaluation. In the present paper a new noise cancellation technique is proposed for removal of random noise like muscle artifact from ECG signal. A transform domain robust variable step size Griffiths' LMS algorithm (TVGLMS) is proposed for noise cancellation. For the TVGLMS, the robust variable step size has been achieved by using the Griffiths' gradient which uses cross-correlation between the desired signal contaminated with observation or random noise and the input. The algorithm is discrete cosine transform (DCT) based and uses symmetric property of the signal to represent the signal in frequency domain with lesser number of frequency coefficients when compared to that of discrete Fourier transform (DFT). The algorithm is implemented for adaptive line enhancer (ALE) filter which extracts the ECG signal in a noisy environment using LMS filter adaptation. The proposed algorithm is found to have better convergence error/misadjustment when compared to that of ordinary transform domain LMS (TLMS) algorithm, both in the presence of white/colored observation noise. The reduction in convergence error achieved by the new algorithm with desired signal decomposition is found to be lower than that obtained without decomposition. The experimental results indicate that the proposed method is better than traditional adaptive filter using LMS algorithm in the aspects of retaining geometrical characteristics of ECG signal.

Validation of the dynamics of SDS and RRS flux, flow, pressure and temperature signals using noise analysis technique

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

A Noise Reduction Method for Dual-Mass Micro-Electromechanical Gyroscopes Based on Sample Entropy Empirical Mode Decomposition and Time-Frequency Peak Filtering.

Science.gov (United States)

Shen, Chong; Li, Jie; Zhang, Xiaoming; Shi, Yunbo; Tang, Jun; Cao, Huiliang; Liu, Jun

2016-05-31

The different noise components in a dual-mass micro-electromechanical system (MEMS) gyroscope structure is analyzed in this paper, including mechanical-thermal noise (MTN), electronic-thermal noise (ETN), flicker noise (FN) and Coriolis signal in-phase noise (IPN). The structure equivalent electronic model is established, and an improved white Gaussian noise reduction method for dual-mass MEMS gyroscopes is proposed which is based on sample entropy empirical mode decomposition (SEEMD) and time-frequency peak filtering (TFPF). There is a contradiction in TFPS, i.e., selecting a short window length may lead to good preservation of signal amplitude but bad random noise reduction, whereas selecting a long window length may lead to serious attenuation of the signal amplitude but effective random noise reduction. In order to achieve a good tradeoff between valid signal amplitude preservation and random noise reduction, SEEMD is adopted to improve TFPF. Firstly, the original signal is decomposed into intrinsic mode functions (IMFs) by EMD, and the SE of each IMF is calculated in order to classify the numerous IMFs into three different components; then short window TFPF is employed for low frequency component of IMFs, and long window TFPF is employed for high frequency component of IMFs, and the noise component of IMFs is wiped off directly; at last the final signal is obtained after reconstruction. Rotation experimental and temperature experimental are carried out to verify the proposed SEEMD-TFPF algorithm, the verification and comparison results show that the de-noising performance of SEEMD-TFPF is better than that achievable with the traditional wavelet, Kalman filter and fixed window length TFPF methods.

A Noise Reduction Method for Dual-Mass Micro-Electromechanical Gyroscopes Based on Sample Entropy Empirical Mode Decomposition and Time-Frequency Peak Filtering

Directory of Open Access Journals (Sweden)

Chong Shen

2016-05-01

Full Text Available The different noise components in a dual-mass micro-electromechanical system (MEMS gyroscope structure is analyzed in this paper, including mechanical-thermal noise (MTN, electronic-thermal noise (ETN, flicker noise (FN and Coriolis signal in-phase noise (IPN. The structure equivalent electronic model is established, and an improved white Gaussian noise reduction method for dual-mass MEMS gyroscopes is proposed which is based on sample entropy empirical mode decomposition (SEEMD and time-frequency peak filtering (TFPF. There is a contradiction in TFPS, i.e., selecting a short window length may lead to good preservation of signal amplitude but bad random noise reduction, whereas selecting a long window length may lead to serious attenuation of the signal amplitude but effective random noise reduction. In order to achieve a good tradeoff between valid signal amplitude preservation and random noise reduction, SEEMD is adopted to improve TFPF. Firstly, the original signal is decomposed into intrinsic mode functions (IMFs by EMD, and the SE of each IMF is calculated in order to classify the numerous IMFs into three different components; then short window TFPF is employed for low frequency component of IMFs, and long window TFPF is employed for high frequency component of IMFs, and the noise component of IMFs is wiped off directly; at last the final signal is obtained after reconstruction. Rotation experimental and temperature experimental are carried out to verify the proposed SEEMD-TFPF algorithm, the verification and comparison results show that the de-noising performance of SEEMD-TFPF is better than that achievable with the traditional wavelet, Kalman filter and fixed window length TFPF methods.

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

Directory of Open Access Journals (Sweden)

S. Saito

2011-07-01

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

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

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

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.

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

International Nuclear Information System (INIS)

Ehrhardt, J.

1975-09-01

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

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

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

CERN Document Server

Shynk, John J

2012-01-01

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

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 ...

Discrete random signal processing and filtering primer with Matlab

CERN Document Server

Poularikas, Alexander D

2013-01-01

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

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.

Science.gov (United States)

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

1988-03-15

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

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

Science.gov (United States)

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

2017-02-01

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

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.

Digital Generation of Noise-Signals with Arbitrary Constant or Time-Varying Spectra (A noise generation software package and its application)

CERN Document Server

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-...

Generation of on-line test signals for nuclear instrumentation for PFBR

International Nuclear Information System (INIS)

Ram, Rajit; Bhatnagar, P.V.; Rajesh, M.G.; Das, Debashis

2010-01-01

Neutron flux monitoring system for PFBR employs pulse signal processing in start up and intermediate power range of reactor operation and Campbell signal processing in intermediate and full power range of reactor operation. Pulse signal processing unit as well as Campbell signal processing unit incorporates FPGA that generates pulse/white noise signal for on-line testing and diagnostic of the channels. In pulse channel fixed/linearly/exponentially varying pulse rate signal is generated over three decades of reactor operation. In the Campbell channel, Poisson distributed noise varying linearly/exponentially is generated over four decades of reactor operation. Multiple numbers of Poisson distributed random pulse trains are summed and amplified to get the white noise signal. Exponentially increasing gain pattern, generated by MATLAB is used to increase the RMS value of the generated noise. The paper discuses the successful testing and validation of pulse and Campbell channel by making use of the generated pulse/white noise signal over wide range of operation for nuclear instrumentation. (author)

Digital signal processing

CERN Document Server

O'Shea, Peter; Hussain, Zahir M

2011-01-01

In three parts, this book contributes to the advancement of engineering education and that serves as a general reference on digital signal processing. Part I presents the basics of analog and digital signals and systems in the time and frequency domain. It covers the core topics: convolution, transforms, filters, and random signal analysis. It also treats important applications including signal detection in noise, radar range estimation for airborne targets, binary communication systems, channel estimation, banking and financial applications, and audio effects production. Part II considers sel

Brain-computer interfaces increase whole-brain signal to noise.

Science.gov (United States)

Papageorgiou, T Dorina; Lisinski, Jonathan M; McHenry, Monica A; White, Jason P; LaConte, Stephen M

2013-08-13

Brain-computer interfaces (BCIs) can convert mental states into signals to drive real-world devices, but it is not known if a given covert task is the same when performed with and without BCI-based control. Using a BCI likely involves additional cognitive processes, such as multitasking, attention, and conflict monitoring. In addition, it is challenging to measure the quality of covert task performance. We used whole-brain classifier-based real-time functional MRI to address these issues, because the method provides both classifier-based maps to examine the neural requirements of BCI and classification accuracy to quantify the quality of task performance. Subjects performed a covert counting task at fast and slow rates to control a visual interface. Compared with the same task when viewing but not controlling the interface, we observed that being in control of a BCI improved task classification of fast and slow counting states. Additional BCI control increased subjects' whole-brain signal-to-noise ratio compared with the absence of control. The neural pattern for control consisted of a positive network comprised of dorsal parietal and frontal regions and the anterior insula of the right hemisphere as well as an expansive negative network of regions. These findings suggest that real-time functional MRI can serve as a platform for exploring information processing and frontoparietal and insula network-based regulation of whole-brain task signal-to-noise ratio.

Discrimination of acoustic communication signals by grasshoppers (Chorthippus biguttulus): temporal resolution, temporal integration, and the impact of intrinsic noise.

Science.gov (United States)

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

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

Science.gov (United States)

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

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.

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

Science.gov (United States)

Dehé, Alfons

2017-06-01

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

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

An improved method based on wavelet coefficient correlation to filter noise in Doppler ultrasound blood flow signals

Science.gov (United States)

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.

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

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

African Journals Online (AJOL)

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

The effects of LIGO detector noise on a 15-dimensional Markov-chain Monte Carlo analysis of gravitational-wave signals

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.

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....

Fractional Gaussian noise-enhanced information capacity of a nonlinear neuron model with binary signal input

Science.gov (United States)

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.

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.

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 ...

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

Science.gov (United States)

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

2017-10-01

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

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)

Adaptive noise cancellation

International Nuclear Information System (INIS)

Akram, N.

1999-01-01

In this report we describe the concept of adaptive noise canceling, an alternative method of estimating signals corrupted by additive noise of interference. The method uses 'primary' input containing the corrupted signal and a 'reference' input containing noise correlated in some unknown way with the primary noise, the reference input is adaptively filtered and subtracted from the primary input to obtain the signal estimate. Adaptive filtering before subtraction allows the treatment of inputs that are deterministic or stochastic, stationary or time variable. When the reference input is free of signal and certain other conditions are met then noise in the primary input can be essentially eliminated without signal distortion. It is further shown that the adaptive filter also acts as notch filter. Simulated results illustrate the usefulness of the adaptive noise canceling technique. (author)

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

Science.gov (United States)

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

2017-10-01

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

Seismic noise attenuation using an online subspace tracking algorithm

Science.gov (United States)

Zhou, Yatong; Li, Shuhua; Zhang, Dong; Chen, Yangkang

2018-02-01

We propose a new low-rank based noise attenuation method using an efficient algorithm for tracking subspaces from highly corrupted seismic observations. The subspace tracking algorithm requires only basic linear algebraic manipulations. The algorithm is derived by analysing incremental gradient descent on the Grassmannian manifold of subspaces. When the multidimensional seismic data are mapped to a low-rank space, the subspace tracking algorithm can be directly applied to the input low-rank matrix to estimate the useful signals. Since the subspace tracking algorithm is an online algorithm, it is more robust to random noise than traditional truncated singular value decomposition (TSVD) based subspace tracking algorithm. Compared with the state-of-the-art algorithms, the proposed denoising method can obtain better performance. More specifically, the proposed method outperforms the TSVD-based singular spectrum analysis method in causing less residual noise and also in saving half of the computational cost. Several synthetic and field data examples with different levels of complexities demonstrate the effectiveness and robustness of the presented algorithm in rejecting different types of noise including random noise, spiky noise, blending noise, and coherent noise.

Efficient algorithm for baseline wander and powerline noise removal from ECG signals based on discrete Fourier series.

Science.gov (United States)

Bahaz, Mohamed; Benzid, Redha

2018-03-01

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.

Low-pass parabolic FFT filter for airborne and satellite lidar signal processing.

Science.gov (United States)

Jiao, Zhongke; Liu, Bo; Liu, Enhai; Yue, Yongjian

2015-10-14

In order to reduce random errors of the lidar signal inversion, a low-pass parabolic fast Fourier transform filter (PFFTF) was introduced for noise elimination. A compact airborne Raman lidar system was studied, which applied PFFTF to process lidar signals. Mathematics and simulations of PFFTF along with low pass filters, sliding mean filter (SMF), median filter (MF), empirical mode decomposition (EMD) and wavelet transform (WT) were studied, and the practical engineering value of PFFTF for lidar signal processing has been verified. The method has been tested on real lidar signal from Wyoming Cloud Lidar (WCL). Results show that PFFTF has advantages over the other methods. It keeps the high frequency components well and reduces much of the random noise simultaneously for lidar signal processing.

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

Science.gov (United States)

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

2018-05-01

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

High level white noise generator

International Nuclear Information System (INIS)

Borkowski, C.J.; Blalock, T.V.

1979-01-01

A wide band, stable, random noise source with a high and well-defined output power spectral density is provided which may be used for accurate calibration of Johnson Noise Power Thermometers (JNPT) and other applications requiring a stable, wide band, well-defined noise power spectral density. The noise source is based on the fact that the open-circuit thermal noise voltage of a feedback resistor, connecting the output to the input of a special inverting amplifier, is available at the amplifier output from an equivalent low output impedance caused by the feedback mechanism. The noise power spectral density level at the noise source output is equivalent to the density of the open-circuit thermal noise or a 100 ohm resistor at a temperature of approximately 64,000 Kelvins. The noise source has an output power spectral density that is flat to within 0.1% (0.0043 db) in the frequency range of from 1 KHz to 100 KHz which brackets typical passbands of the signal-processing channels of JNPT's. Two embodiments, one of higher accuracy that is suitable for use as a standards instrument and another that is particularly adapted for ambient temperature operation, are illustrated in this application

High level white noise generator

Science.gov (United States)

Borkowski, Casimer J.; Blalock, Theron V.

1979-01-01

A wide band, stable, random noise source with a high and well-defined output power spectral density is provided which may be used for accurate calibration of Johnson Noise Power Thermometers (JNPT) and other applications requiring a stable, wide band, well-defined noise power spectral density. The noise source is based on the fact that the open-circuit thermal noise voltage of a feedback resistor, connecting the output to the input of a special inverting amplifier, is available at the amplifier output from an equivalent low output impedance caused by the feedback mechanism. The noise power spectral density level at the noise source output is equivalent to the density of the open-circuit thermal noise or a 100 ohm resistor at a temperature of approximately 64,000 Kelvins. The noise source has an output power spectral density that is flat to within 0.1% (0.0043 db) in the frequency range of from 1 KHz to 100 KHz which brackets typical passbands of the signal-processing channels of JNPT's. Two embodiments, one of higher accuracy that is suitable for use as a standards instrument and another that is particularly adapted for ambient temperature operation, are illustrated in this application.

Affectively salient meaning in random noise: a task sensitive to psychosis liability.

Science.gov (United States)

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.

Improving the signal-to-noise ratio in ultrasound-modulated optical tomography by a lock-in amplifier

Science.gov (United States)

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.

Prediction of interior noise due to random acoustic or turbulent boundary layer excitation using statistical energy analysis

Science.gov (United States)

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.

Random vibrations theory and practice

CERN Document Server

Wirsching, Paul H; Ortiz, Keith

1995-01-01

Random Vibrations: Theory and Practice covers the theory and analysis of mechanical and structural systems undergoing random oscillations due to any number of phenomena— from engine noise, turbulent flow, and acoustic noise to wind, ocean waves, earthquakes, and rough pavement. For systems operating in such environments, a random vibration analysis is essential to the safety and reliability of the system. By far the most comprehensive text available on random vibrations, Random Vibrations: Theory and Practice is designed for readers who are new to the subject as well as those who are familiar with the fundamentals and wish to study a particular topic or use the text as an authoritative reference. It is divided into three major sections: fundamental background, random vibration development and applications to design, and random signal analysis. Introductory chapters cover topics in probability, statistics, and random processes that prepare the reader for the development of the theory of random vibrations a...

Noise generator for tinnitus treatment based on look-up tables

Science.gov (United States)

Uriz, Alejandro J.; Agüero, Pablo; Tulli, Juan C.; Castiñeira Moreira, Jorge; González, Esteban; Hidalgo, Roberto; Casadei, Manuel

2016-04-01

Treatment of tinnitus by means of masking sounds allows to obtain a significant improve of the quality of life of the individual that suffer that condition. In view of that, it is possible to develop noise synthesizers based on random number generators in digital signal processors (DSP), which are used in almost any digital hearing aid devices. DSP architecture have limitations to implement a pseudo random number generator, due to it, the noise statistics can be not as good as expectations. In this paper, a technique to generate additive white gaussian noise (AWGN) or other types of filtered noise using coefficients stored in program memory of the DSP is proposed. Also, an implementation of the technique is carried out on a dsPIC from Microchip®. Objective experiments and experimental measurements are performed to analyze the proposed technique.

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

Science.gov (United States)

Wu, Yu-Hsiang; Stangl, Elizabeth

2013-01-01

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

Noise frame duration, masking potency and whiteness of temporal noise.

Science.gov (United States)

Kukkonen, Heljä; Rovamo, Jyrki; Donner, Kristian; Tammikallio, Marja; Raninen, Antti

2002-09-01

Because of the limited contrast range, increasing the duration of the noise frame is often the only option for increasing the masking potency of external, white temporal noise. This, however, reduces the high-frequency cutoff beyond which noise is no longer white. This study was conducted to determine the longest noise frame duration that produces the strongest masking effect and still mimics white noise on the detection of sinusoidal flicker. Contrast energy thresholds (E(th)) were measured for flicker at 1.25 to 20 Hz in strong, purely temporal (spatially uniform), additive, external noise. The masking power of white external noise, characterized by its spectral density at zero frequency N0, increases with the duration of the noise frame. For short noise frame durations, E(th) increased in direct proportion to N0, keeping the nominal signal-to-noise ratio [SNR = (E(th)/N0)(0.5)] constant at threshold. The masking effect thus increased with the duration of the noise frame and the noise mimicked white noise. When noise frame duration and N0 increased further, the nominal SNR at threshold started to decrease, indicating that noise no longer mimicked white noise. The minimum number of noise frames per flicker cycle needed to mimic white noise decreased with increasing flicker frequency from 8.3 at 1.25 Hz to 1.6 at 20 Hz. The critical high-frequency cutoff of detection-limiting temporal noise in terms of noise frames per signal cycle depends on the temporal frequency of the signal. This is opposite to the situation in the spatial domain and must be taken into consideration when temporal signals are masked with temporal noise.

Periodic rotation noise induced by the crosstalk between two beat-frequency signals in multi-oscillator ring laser gyros

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)

Communication system with adaptive noise suppression

Science.gov (United States)

Kozel, David (Inventor); Devault, James A. (Inventor); Birr, Richard B. (Inventor)

2007-01-01

A signal-to-noise ratio dependent adaptive spectral subtraction process eliminates noise from noise-corrupted speech signals. The process first pre-emphasizes the frequency components of the input sound signal which contain the consonant information in human speech. Next, a signal-to-noise ratio is determined and a spectral subtraction proportion adjusted appropriately. After spectral subtraction, low amplitude signals can be squelched. A single microphone is used to obtain both the noise-corrupted speech and the average noise estimate. This is done by determining if the frame of data being sampled is a voiced or unvoiced frame. During unvoiced frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Spectral subtraction may be performed on a composite noise-corrupted signal, or upon individual sub-bands of the noise-corrupted signal. Pre-averaging of the input signal's magnitude spectrum over multiple time frames may be performed to reduce musical noise.

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

International Nuclear Information System (INIS)

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

2015-01-01

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

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)

Background Noise Reduction Using Adaptive Noise Cancellation Determined by the Cross-Correlation

Science.gov (United States)

Spalt, Taylor B.; Brooks, Thomas F.; Fuller, Christopher R.

2012-01-01

Background noise due to flow in wind tunnels contaminates desired data by decreasing the Signal-to-Noise Ratio. The use of Adaptive Noise Cancellation to remove background noise at measurement microphones is compromised when the reference sensor measures both background and desired noise. The technique proposed modifies the classical processing configuration based on the cross-correlation between the reference and primary microphone. Background noise attenuation is achieved using a cross-correlation sample width that encompasses only the background noise and a matched delay for the adaptive processing. A present limitation of the method is that a minimum time delay between the background noise and desired signal must exist in order for the correlated parts of the desired signal to be separated from the background noise in the crosscorrelation. A simulation yields primary signal recovery which can be predicted from the coherence of the background noise between the channels. Results are compared with two existing methods.

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.

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

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

Representation of acoustic signals in the eighth nerve of the Tokay gecko. II. Masking of pure tones with noise.

Science.gov (United States)

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.

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.

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

Science.gov (United States)

Alfisyahrin; Isranuri, I.

2018-02-01

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

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

KAUST Repository

Lipor, John

2013-05-12

Multiple-input multiple-output (MIMO) radar employs orthogonal or partially correlated transmit signals to achieve performance benefits over its phased-array counterpart. It has been shown that MIMO radar can achieve greater spatial resolution, improved signal-to-noise ratio (SNR) and target localization, and greater clutter resolution using space-time adaptive processing (STAP). This thesis explores various methods to improve the signal-to-interference-plus-noise ratio (SINR) via transmit and receive beamforming. In MIMO radar settings, it is often desirable to transmit power only to a given location or set of locations defined by a beampattern. Current methods involve a two- step process of designing the transmit covariance matrix R via iterative solutions and then using R to generate waveforms that fulfill practical constraints such as having a constant-envelope or drawing from a finite alphabet. In this document, a closed- form method to design R is proposed that utilizes the discrete Fourier transform (DFT) coefficients and Toeplitz matrices. The resulting covariance matrix fulfills the practical constraints such as positive semidefiniteness and the uniform elemental power constraint and provides performance similar to that of iterative methods, which require a much greater computation time. Next, a transmit architecture is presented 
that exploits the orthogonality of frequencies at discrete DFT values to transmit a sum of orthogonal signals from each antenna. The resulting waveforms provide a lower mean-square error than current methods at a much lower computational cost, and a simulated detection scenario demonstrates the performance advantages achieved. It is also desirable to receive signal power only from a given set of directions defined by a beampattern. In a later chapter of this document, the problem of receive beampattern matching is formulated and three solutions to this problem are demonstrated. We show that partitioning the received data vector

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

KAUST Repository

Aldawood, Ali

2012-04-01

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

Noise in Optical Amplifiers

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....

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.

Seismic signal and noise on Europa and how to use it

Science.gov (United States)

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

2017-12-01

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

Synchronisation and desynchronisation of self-modulation oscillations in a ring chip laser under the action of a periodic signal and noise

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)

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...

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

Science.gov (United States)

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

2018-04-01

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

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.)

A continuous wavelet transform approach for harmonic parameters estimation in the presence of impulsive noise

Science.gov (United States)

Dai, Yu; Xue, Yuan; Zhang, Jianxun

2016-01-01

Impulsive noise caused by some random events has the main character of short rise-time and wide frequency spectrum range, so it has the potential to degrade the performance and reliability of the harmonic estimation. This paper focuses on the harmonic estimation procedure based on continuous wavelet transform (CWT) when the analyzed signal is corrupted by the impulsive noise. The digital CWT of both the time-varying sinusoidal signal and the impulsive noise are analyzed, and there are two cross ridges in the time-frequency plane of CWT, which are generated by the signal and the noise separately. In consideration of the amplitude of the noise and the number of the spike event, two inequalities are derived to provide limitations on the wavelet parameters. Based on the amplitude distribution of the noise, the optimal wavelet parameters determined by solving these inequalities are used to suppress the contamination of the noise, as well as increase the amplitude of the ridge corresponding to the signal, so the parameters of each harmonic component can be estimated accurately. The proposed procedure is applied to a numerical simulation and a bone vibration signal test giving satisfactory results of stationary and time-varying harmonic parameter estimation.

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.

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

Science.gov (United States)

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

2013-04-01

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

Noise magnetic Barkahausen: modeling and scale

International Nuclear Information System (INIS)

Rodríguez-Pérez, Jorge L.; Pérez Benítez, José A.

2008-01-01

Noise magnetic Barkahausen of produces due to network defaults, and is reflected in abrupt changes that take place in the magnetization of the material in Studio. This fact presupposes a complexity, according to the various factors that influence its occurrence and internal changes in the system. A study of noise are used in three fundamental quantities: length the signal, the area under the curve and the energy of the signal; from these other quantities that are used often are defined: the square root mean (average-quadratic voltage) signal and the amplitude of the signal (maximum peak voltage). This form of investigate the phenomenon assumes a statistical analysis of the behaviour of the signal as a result of a set of changes that occur in the material, showing the complexity of the system and the importance of the laws of scale. This paper investigates the relationship between noise magnetic Barkahausen, laws of scale and complexity using structural steel ATSM 36 samples that have been subjected to mechanical deformations by traction and compression. For it's performed a statistical analysis to determine the complexity from the Test-appointment and reported the values of fundamental quantities and laws of scale for different deformation, resulting in the unit which shows the connection between the values of the voltage quadratic medium, the depth of the sample, the characteristics of the laws of scale and complexity: a pseudo random system.

Process sensors characterization based on noise analysis technique and artificial intelligence

International Nuclear Information System (INIS)

Mesquita, Roberto N. de; Perillo, Sergio R.P.; Santos, Roberto C. dos

2005-01-01

The time response of pressure and temperature sensors from the Reactor Protection System (RPS) is a requirement that must be satisfied in nuclear power plants, furthermore is an indicative of its degradation and its remaining life. The nuclear power industry and others have been eager to implement smart sensor technologies and digital instrumentation concepts to reduce manpower and effort currently spent on testing and calibration. Process parameters fluctuations during normal operation of a reactor are caused by random variations in neutron flux, heat transfer and other sources. The output sensor noise can be considered as the response of the system to an input representing the statistical nature of the underlying process which can be modeled using a time series model. Since the noise signal measurements are influenced by many factors, such as location of sensors, extraneous noise interference, and randomness in temperature and pressure fluctuation - the quantitative estimate of the time response using autoregressive noise modeling is subject to error. This technique has been used as means of sensor monitoring. In this work a set of pressure sensors installed in one experimental loop adapted from a flow calibration setup is used to test and analyze signals in a new approach using artificial intelligence techniques. A set of measurements of dynamic signals in different experimental conditions is used to distinguish and identify underlying process sources. A methodology that uses Blind Separation of Sources with a neural networks scheme is being developed to improve time response estimate reliability in noise analysis. (author)

Process sensors characterization based on noise analysis technique and artificial intelligence

Energy Technology Data Exchange (ETDEWEB)

Mesquita, Roberto N. de; Perillo, Sergio R.P.; Santos, Roberto C. dos [Instituto de Pesquisas Energeticas e Nucleares (IPEN), Sao Paulo, SP (Brazil)]. E-mail: rnavarro@ipen.br; sperillo@ipen.br; rcsantos@ipen.br

2005-07-01

The time response of pressure and temperature sensors from the Reactor Protection System (RPS) is a requirement that must be satisfied in nuclear power plants, furthermore is an indicative of its degradation and its remaining life. The nuclear power industry and others have been eager to implement smart sensor technologies and digital instrumentation concepts to reduce manpower and effort currently spent on testing and calibration. Process parameters fluctuations during normal operation of a reactor are caused by random variations in neutron flux, heat transfer and other sources. The output sensor noise can be considered as the response of the system to an input representing the statistical nature of the underlying process which can be modeled using a time series model. Since the noise signal measurements are influenced by many factors, such as location of sensors, extraneous noise interference, and randomness in temperature and pressure fluctuation - the quantitative estimate of the time response using autoregressive noise modeling is subject to error. This technique has been used as means of sensor monitoring. In this work a set of pressure sensors installed in one experimental loop adapted from a flow calibration setup is used to test and analyze signals in a new approach using artificial intelligence techniques. A set of measurements of dynamic signals in different experimental conditions is used to distinguish and identify underlying process sources. A methodology that uses Blind Separation of Sources with a neural networks scheme is being developed to improve time response estimate reliability in noise analysis. (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

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)

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)

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.

Stochastic amplification and signaling in enzymatic futile cycles through noise-induced bistability with oscillations

Science.gov (United States)

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

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

BER analysis for MPAM signal constellations in the presence of fading and ADC quantization noise

NARCIS (Netherlands)

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

Non-Stoichiometric SixN Metal-Oxide-Semiconductor Field-Effect Transistor for Compact Random Number Generator with 0.3 Mbit/s Generation Rate

Science.gov (United States)

Matsumoto, Mari; Ohba, Ryuji; Yasuda, Shin-ichi; Uchida, Ken; Tanamoto, Tetsufumi; Fujita, Shinobu

2008-08-01

The demand for random numbers for security applications is increasing. A conventional random number generator using thermal noise can generate unpredictable high-quality random numbers, but the circuit is extremely large because of large amplifier circuit for a small thermal signal. On the other hand, a pseudo-random number generator is small but the quality of randomness is bad. For a small circuit and a high quality of randomness, we purpose a non-stoichiometric SixN metal-oxide-semiconductor field-effect transistor (MOSFET) noise source device. This device generates a very large noise signal without an amplifier circuit. As a result, it is shown that, utilizing a SiN MOSFET, we can attain a compact random number generator with a high generation rate near 1 Mbit/s, which is suitable for almost all security applications.

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

A noise reconfigurable current-reuse resistive feedback amplifier with signal-dependent power consumption for fetal ECG monitoring

NARCIS (Netherlands)

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

Spin noise amplification and giant noise in optical microcavity

Energy Technology Data Exchange (ETDEWEB)

Ryzhov, I. I.; Poltavtsev, S. V.; Kozlov, G. G.; Zapasskii, V. S. [Spin-Optics Laboratory, St. Petersburg State University, 198504 St. Petersburg (Russian Federation); Kavokin, A. V. [Department of Physics and Astronomy, University of Southampton, Southampton SO17 1BJ (United Kingdom); Spin-Optics Laboratory, St. Petersburg State University, 198504 St. Petersburg (Russian Federation); Lagoudakis, P. V. [Department of Physics and Astronomy, University of Southampton, Southampton SO17 1BJ (United Kingdom)

2015-06-14

When studying the spin-noise-induced fluctuations of Kerr rotation in a quantum-well microcavity, we have found a dramatic increase of the noise signal (by more than two orders of magnitude) in the vicinity of anti-crossing of the polariton branches. The effect is explained by nonlinear optical instability of the microcavity giving rise to the light-power-controlled amplification of the polarization noise signal. In the framework of the developed model of built-in amplifier, we also interpret the nontrivial spectral and intensity-related properties of the observed noise signal below the region of anti-crossing of polariton branches. The discovered effect of optically controllable amplification of broadband polarization signals in microcavities in the regime of optical instability may be of interest for detecting weak oscillations of optical anisotropy in fundamental research and for other applications in optical information processing.

Phenomenon of entropic stochastic resonance with asymmetric dichotomous noise and white noise

International Nuclear Information System (INIS)

Guo, Feng; Li, Shao-Fu; Cheng, Xiao-Feng

2012-01-01

The entropic stochastic resonance (ESR) in a confined system subject to asymmetric dichotomous noise, white noise, and a periodic square-wave signal is investigated. Under the adiabatic approximation condition, by use of the properties of the dichotomous noise, we obtain the expression of the output signal-to-noise ratio (SNR) based on two-state theory. The SNR is shown to be a nonmonotonic function of the strength and asymmetry of the dichotomous noise, the intensity of the white noise, and the amplitude of the square-wave signal. The SNR varies non-monotonically with increases in the parameters of the confined structure. The influence of the correlation rate of the dichotomous noise and the frequency of the external constant force on the SNR is also discussed.

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.

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

KAUST Repository

Laleg-Kirati, Taous-Meriem

2016-09-05

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

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

KAUST Repository

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

2016-01-01

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

External noise distinguishes attention mechanisms.

Science.gov (United States)

Lu, Z L; Dosher, B A

1998-05-01

We developed and tested a powerful method for identifying and characterizing the effect of attention on performance in visual tasks as due to signal enhancement, distractor exclusion, or internal noise suppression. Based on a noisy Perceptual Template Model (PTM) of a human observer, the method adds increasing amounts of external noise (white gaussian random noise) to the visual stimulus and observes the effect on performance of a perceptual task for attended and unattended stimuli. The three mechanisms of attention yield three "signature" patterns of performance. The general framework for characterizing the mechanisms of attention is used here to investigate the attentional mechanisms in a concurrent location-cued orientation discrimination task. Test stimuli--Gabor patches tilted slightly to the right or left--always appeared on both the left and the right of fixation, and varied independently. Observers were cued on each trial to attend to the left, the right, or evenly to both stimuli, and decide the direction of tilt of both test stimuli. For eight levels of added external noise and three attention conditions (attended, unattended, and equal), subjects' contrast threshold levels were determined. At low levels of external noise, attention affected threshold contrast: threshold contrasts for non-attended stimuli were systematically higher than for equal attention stimuli, which were, in turn, higher than for attended stimuli. Specifically, when the rms contrast of the external noise is below 10%, there is a consistent 17% elevation of contrast threshold from attended to unattended condition across all three subjects. For higher levels of external noise, attention conditions did not affect threshold contrast values at all. These strong results are characteristic of a signal enhancement, or equivalently, an internal additive noise reduction mechanism of attention.

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.

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

Science.gov (United States)

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

2013-04-01

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

Enhancement of information transmission with stochastic resonance in hippocampal CA1 neuron models: effects of noise input location.

Science.gov (United States)

Kawaguchi, Minato; Mino, Hiroyuki; Durand, Dominique M

2007-01-01

Stochastic resonance (SR) has been shown to enhance the signal to noise ratio or detection of signals in neurons. It is not yet clear how this effect of SR on the signal to noise ratio affects signal processing in neural networks. In this paper, we investigate the effects of the location of background noise input on information transmission in a hippocampal CA1 neuron model. In the computer simulation, random sub-threshold spike trains (signal) generated by a filtered homogeneous Poisson process were presented repeatedly to the middle point of the main apical branch, while the homogeneous Poisson shot noise (background noise) was applied to a location of the dendrite in the hippocampal CA1 model consisting of the soma with a sodium, a calcium, and five potassium channels. The location of the background noise input was varied along the dendrites to investigate the effects of background noise input location on information transmission. The computer simulation results show that the information rate reached a maximum value for an optimal amplitude of the background noise amplitude. It is also shown that this optimal amplitude of the background noise is independent of the distance between the soma and the noise input location. The results also show that the location of the background noise input does not significantly affect the maximum values of the information rates generated by stochastic resonance.

Simulation for noise cancellation using LMS adaptive filter

Science.gov (United States)

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

2017-06-01

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

Determination of noise sources and space-dependent reactor transfer functions from measured output signals only

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.

Determination of noise sources and space-dependent reactor transfer functions from measured output signals only

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)

Complex noise suppression using a sparse representation and 3D filtering of images

Science.gov (United States)

Kravchenko, V. F.; Ponomaryov, V. I.; Pustovoit, V. I.; Palacios-Enriquez, A.

2017-08-01

A novel method for the filtering of images corrupted by complex noise composed of randomly distributed impulses and additive Gaussian noise has been substantiated for the first time. The method consists of three main stages: the detection and filtering of pixels corrupted by impulsive noise, the subsequent image processing to suppress the additive noise based on 3D filtering and a sparse representation of signals in a basis of wavelets, and the concluding image processing procedure to clean the final image of the errors emerged at the previous stages. A physical interpretation of the filtering method under complex noise conditions is given. A filtering block diagram has been developed in accordance with the novel approach. Simulations of the novel image filtering method have shown an advantage of the proposed filtering scheme in terms of generally recognized criteria, such as the structural similarity index measure and the peak signal-to-noise ratio, and when visually comparing the filtered images.

A 7 ke-SD-FWC 1.2 e-RMS Temporal Random Noise 128×256 Time-Resolved CMOS Image Sensor With Two In-Pixel SDs for Biomedical Applications.

Science.gov (United States)

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.

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)

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

Science.gov (United States)

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

1977-01-01

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

Noise in strong laser-atom interactions: Phase telegraph noise

International Nuclear Information System (INIS)

Eberly, J.H.; Wodkiewicz, K.; Shore, B.W.

1984-01-01

We discuss strong laser-atom interactions that are subjected to jump-type (random telegraph) random-phase noise. Physically, the jumps may arise from laser fluctuations, from collisions of various kinds, or from other external forces. Our discussion is carried out in two stages. First, direct and partially heuristic calculations determine the laser spectrum and also give a third-order differential equation for the average inversion of a two-level atom on resonance. At this stage a number of general features of the interaction are able to be studied easily. The optical analog of motional narrowing, for example, is clearly predicted. Second, we show that the theory of generalized Poisson processes allows laser-atom interactions in the presence of random telegraph noise of all kinds (not only phase noise) to be treated systematically, by means of a master equation first used in the context of quantum optics by Burshtein. We use the Burshtein equation to obtain an exact expression for the two-level atom's steady-state resonance fluorescence spectrum, when the exciting laser exhibits phase telegraph noise. Some comparisons are made with results obtained from other noise models. Detailed treatments of the effects ofmly jumps, or as a model of finite laser bandwidth effects, in which the laser frequency exhibits random jumps. We show that these two types of frequency noise can be distinguished in light-scattering spectra. We also discuss examples which demonstrate both temporal and spectral motional narrowing, nonexponential correlations, and non-Lorentzian spectra. Its exact solubility in finite terms makes the frequency-telegraph noise model an attractive alternative to the white-noise Ornstein-Uhlenbeck frequency noise model which has been previously applied to laser-atom interactions

Noise analysis of grating-based x-ray differential phase-contrast imaging with angular signal radiography

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)

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

Science.gov (United States)

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

2016-07-01

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

Optimal signal constellation design for ultra-high-speed optical transport in the presence of nonlinear phase noise.

Science.gov (United States)

Liu, Tao; Djordjevic, Ivan B

2014-12-29

In this paper, we first describe an optimal signal constellation design algorithm suitable for the coherent optical channels dominated by the linear phase noise. Then, we modify this algorithm to be suitable for the nonlinear phase noise dominated channels. In optimization procedure, the proposed algorithm uses the cumulative log-likelihood function instead of the Euclidian distance. Further, an LDPC coded modulation scheme is proposed to be used in combination with signal constellations obtained by proposed algorithm. Monte Carlo simulations indicate that the LDPC-coded modulation schemes employing the new constellation sets, obtained by our new signal constellation design algorithm, outperform corresponding QAM constellations significantly in terms of transmission distance and have better nonlinearity tolerance.

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

International Nuclear Information System (INIS)

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

2010-01-01

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

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.

Integration of motion energy from overlapping random background noise increases perceived speed of coherently moving stimuli.

Science.gov (United States)

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.

First evaluation of low frequency noise measurements of in core detector signals in the measuring assembly Rheinsberg

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

Random Deep Belief Networks for Recognizing Emotions from Speech Signals.

Science.gov (United States)

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

2017-01-01

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

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.

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

Directory of Open Access Journals (Sweden)

Sabine A. Janssen

2011-05-01

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

Random attractors for stochastic lattice reversible Gray-Scott systems with additive noise

Directory of Open Access Journals (Sweden)

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.

Active3 noise reduction

International Nuclear Information System (INIS)

Holzfuss, J.

1996-01-01

Noise reduction is a problem being encountered in a variety of applications, such as environmental noise cancellation, signal recovery and separation. Passive noise reduction is done with the help of absorbers. Active noise reduction includes the transmission of phase inverted signals for the cancellation. This paper is about a threefold active approach to noise reduction. It includes the separation of a combined source, which consists of both a noise and a signal part. With the help of interaction with the source by scanning it and recording its response, modeling as a nonlinear dynamical system is achieved. The analysis includes phase space analysis and global radial basis functions as tools for the prediction used in a subsequent cancellation procedure. Examples are given which include noise reduction of speech. copyright 1996 American Institute of Physics

Auditory detection of an increment in the rate of a random process

International Nuclear Information System (INIS)

Brown, W.S.; Emmerich, D.S.

1994-01-01

Recent experiments have presented listeners with complex tonal stimuli consisting of components with values (i.e., intensities or frequencies) randomly sampled from probability distributions [e.g., R. A. Lutfi, J. Acoust. Soc. Am. 86, 934--944 (1989)]. In the present experiment, brief tones were presented at intervals corresponding to the intensity of a random process. Specifically, the intervals between tones were randomly selected from exponential probability functions. Listeners were asked to decide whether tones presented during a defined observation interval represented a ''noise'' process alone or the ''noise'' with a ''signal'' process added to it. The number of tones occurring in any observation interval is a Poisson variable; receiver operating characteristics (ROCs) arising from Poisson processes have been considered by Egan [Signal Detection Theory and ROC Analysis (Academic, New York, 1975)]. Several sets of noise and signal intensities and observation interval durations were selected which were expected to yield equivalent performance. Rating ROCs were generated based on subjects' responses in a single-interval, yes--no task. The performance levels achieved by listeners and the effects of intensity and duration are compared to those predicted for an ideal observer

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)

Novel active signal compression in low-noise analog readout at future X-ray FEL facilities

Science.gov (United States)

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.

Classifier for gravitational-wave inspiral signals in nonideal single-detector data

Science.gov (United States)

Kapadia, S. J.; Dent, T.; Dal Canton, T.

2017-11-01

We describe a multivariate classifier for candidate events in a templated search for gravitational-wave (GW) inspiral signals from neutron-star-black-hole (NS-BH) binaries, in data from ground-based detectors where sensitivity is limited by non-Gaussian noise transients. The standard signal-to-noise ratio (SNR) and chi-squared test for inspiral searches use only properties of a single matched filter at the time of an event; instead, we propose a classifier using features derived from a bank of inspiral templates around the time of each event, and also from a search using approximate sine-Gaussian templates. The classifier thus extracts additional information from strain data to discriminate inspiral signals from noise transients. We evaluate a random forest classifier on a set of single-detector events obtained from realistic simulated advanced LIGO data, using simulated NS-BH signals added to the data. The new classifier detects a factor of 1.5-2 more signals at low false positive rates as compared to the standard "reweighted SNR" statistic, and does not require the chi-squared test to be computed. Conversely, if only the SNR and chi-squared values of single-detector events are available, random forest classification performs nearly identically to the reweighted SNR.

Concept of a data base for signal patterns

International Nuclear Information System (INIS)

Olma, B.

1985-01-01

The many requirements made on the storage, administration and handling of signal patterns of stationary random signal patterns and multi-channel transient signal patterns are discussed. For the field of loose part detection, the concept of a data base is presented for structure-borne noise burst patterns. Chapter 2 describes the measuring principle of structure-borne noise monitoring. Chapter 3 gives a summary of the requirements made on the automation of measured data recording; chapter 4 compiles requirements made on the data base. Chapter 5 describes the concept developed for a burst pattern data base; chapter 6 shows the organization of the data base, and chapter 7 reflects the present state of application. (orig./HP) [de

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

Noise properties of Hilbert transform evaluation

International Nuclear Information System (INIS)

Pavliček, Pavel; Svak, Vojtěch

2015-01-01

The Hilbert transform is a standard method for the calculation of the envelope and phase of a modulated signal in optical measurement methods. Usually, the intensity of light is converted into an electric signal at a detector. Therefore the actual spatially or temporally sampled signal is always affected by noise. Because the noise values of individual samples are independent, the noise can be considered as white. If the envelope and phase are calculated from the noised signal, they will also be affected by the noise. We calculate the variance and spectral density of both the envelope noise and the phase noise. We determine which parameters influence the variance and spectral density of both the envelope noise and the phase noise. Finally, we determine the influence of the noise on the measurement uncertainty in white-light interferometry and fringe-pattern analysis. (paper)

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

OpenAIRE

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

2009-01-01

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

Electromagnetic Signals and Earthquakes 2.0: Increasing Signals and Reducing Noise

Science.gov (United States)

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

2013-12-01

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

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

Science.gov (United States)

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

2008-10-01

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

Gating in time domain as a tool for improving the signal-to-noise ratio of beam transfer function measurements

CERN Document Server

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.

Doing the Impossible: A Note on Induction and the Experience of Randomness.

Science.gov (United States)

Lopes, Lola L.

1982-01-01

The process of induction is formulated as a problem in detecting nonrandomness, or pattern, against a background of randomness, or noise. Experimental and philosophical approaches to human conceptions of randomness are contrasted. The relation between induction and the experience of randomness is discussed in terms of signal-detection theory.…

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

Science.gov (United States)

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

1977-01-01

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

Adjusting phenotypes by noise control.

Directory of Open Access Journals (Sweden)

Kyung H Kim

2012-01-01

Full Text Available Genetically identical cells can show phenotypic variability. This is often caused by stochastic events that originate from randomness in biochemical processes involving in gene expression and other extrinsic cellular processes. From an engineering perspective, there have been efforts focused on theory and experiments to control noise levels by perturbing and replacing gene network components. However, systematic methods for noise control are lacking mainly due to the intractable mathematical structure of noise propagation through reaction networks. Here, we provide a numerical analysis method by quantifying the parametric sensitivity of noise characteristics at the level of the linear noise approximation. Our analysis is readily applicable to various types of noise control and to different types of system; for example, we can orthogonally control the mean and noise levels and can control system dynamics such as noisy oscillations. As an illustration we applied our method to HIV and yeast gene expression systems and metabolic networks. The oscillatory signal control was applied to p53 oscillations from DNA damage. Furthermore, we showed that the efficiency of orthogonal control can be enhanced by applying extrinsic noise and feedback. Our noise control analysis can be applied to any stochastic model belonging to continuous time Markovian systems such as biological and chemical reaction systems, and even computer and social networks. We anticipate the proposed analysis to be a useful tool for designing and controlling synthetic gene networks.

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

Science.gov (United States)

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

2011-01-01

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

The Analysis and Suppression of the spike noise in vibrator record

Science.gov (United States)

Jia, H.; Jiang, T.; Xu, X.; Ge, L.; Lin, J.; Yang, Z.

2013-12-01

During the seismic exploration with vibrator, seismic recording systems have often been affected by random spike noise in the background, which leads to strong data distortions as a result of the cross-correlation processing of the vibrator method. Partial or total loss of the desired seismic information is possible if no automatic spike reduction is available in the field prior to correlation of the field record. Generally speaking, original record of vibrator is uncorrelated data, in which the signal is non-wavelet form. In order to obtain the seismic record similar to explosive source, the signal of uncorrelated data needs to use the correlation algorithm to compress into wavelet form. The correlation process results in that the interference of spike in correlated data is not only being suppressed, but also being expanded. So the spike noise suppression of vibrator is indispensable. According to numerical simulation results, the effect of spike in the vibrator record is mainly affected by the amplitude and proportional points in the uncorrelated record. When the spike noise ratio in uncorrelated record reaches 1.5% and the average amplitude exceeds 200, it will make the SNR(signal-to-noise ratio) of the correlated record lower than 0dB, so that it is difficult to separate the signal. While the amplitude and ratio is determined by the intensity of background noise. Therefore, when the noise level is strong, in order to improve SNR of the seismic data, the uncorrelated record of vibrator need to take necessary steps to suppress spike noise. For the sake of reducing the influence of the spike noise, we need to make the detection and suppression of spike noise process for the uncorrelated record. Because vibrator works by inputting sweep signal into the underground long time, ideally, the peak and valley values of each trace have little change. On the basis of the peak and valley values, we can get a reference amplitude value. Then the spike can be detected and

Complex diffusion process for noise reduction

DEFF Research Database (Denmark)

Nadernejad, Ehsan; Barari, A.

2014-01-01

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

The Cause of an Eddy Current Signal Noise from a Steam Generator Tube and its Effect on the Detectability of a Crack

International Nuclear Information System (INIS)

Lee, Deok Hyun; Choi, Myung Sik; Hur, Do Haeng; Kim, Kyung Mo; Han, Jung Ho

2008-01-01

An eddy current inspection has been applied for a pre-service and in-service examination of a steam generator in nuclear power plants. The experience from the inspection of steam generators showed that many plants had an excessive number of tubes with eddy current noise signals over several hundreds, which originated from manufacturing anomalies. The plants in U.S suffered significant downstream inspection costs, history reviews, and diagnostic testing because some signals resembled flaws and others masked a flaw. These lessens learned resulted in issuing the guidelines for steam generator tubing specifications and repair, in order to reduce the number of anomalous signals in the tubes and also to provide the requirement of a signal to noise ratio by applying a field type examination with bobbin coil eddy current probes at a manufacturing process. Besides the noise signals of a bobbin coil eddy current probe from manufacturing anomalies, the excessive background noise of the rotating coil eddy current probe signal is frequently observed from a tube and it negatively affects the detection and sizing estimate of a defect. Since the inspection intervals are being extended up to 60 months for the more recent steam generator of corrosion resistant alloy 690TT tubing, the detection of an earlier crack and an accurate sizing are becoming more important in the activity of a non-destructive examination. In this study, the cause of an eddy current signal noise of a rotating coil probe from a steam generator tube was examined and its influence on the detectability of a crack was analyzed

Secure Image Encryption Based On a Chua Chaotic Noise Generator

Directory of Open Access Journals (Sweden)

A. S. Andreatos

2013-10-01

Full Text Available This paper presents a secure image cryptography telecom system based on a Chua's circuit chaotic noise generator. A chaotic system based on synchronised Master–Slave Chua's circuits has been used as a chaotic true random number generator (CTRNG. Chaotic systems present unpredictable and complex behaviour. This characteristic, together with the dependence on the initial conditions as well as the tolerance of the circuit components, make CTRNGs ideal for cryptography. In the proposed system, the transmitter mixes an input image with chaotic noise produced by a CTRNG. Using thresholding techniques, the chaotic signal is converted to a true random bit sequence. The receiver must be able to reproduce exactly the same chaotic noise in order to subtract it from the received signal. This becomes possible with synchronisation between the two Chua's circuits: through the use of specific techniques, the trajectory of the Slave chaotic system can be bound to that of the Master circuit producing (almost identical behaviour. Additional blocks have been used in order to make the system highly parameterisable and robust against common attacks. The whole system is simulated in Matlab. Simulation results demonstrate satisfactory performance, as well as, robustness against cryptanalysis. The system works with both greyscale and colour jpg images.

Random resampling masks: a non-Bayesian one-shot strategy for noise reduction in digital holography.

Science.gov (United States)

Bianco, V; Paturzo, M; Memmolo, P; Finizio, A; Ferraro, P; Javidi, B

2013-03-01

Holographic imaging may become severely degraded by a mixture of speckle and incoherent additive noise. Bayesian approaches reduce the incoherent noise, but prior information is needed on the noise statistics. With no prior knowledge, one-shot reduction of noise is a highly desirable goal, as the recording process is simplified and made faster. Indeed, neither multiple acquisitions nor a complex setup are needed. So far, this result has been achieved at the cost of a deterministic resolution loss. Here we propose a fast non-Bayesian denoising method that avoids this trade-off by means of a numerical synthesis of a moving diffuser. In this way, only one single hologram is required as multiple uncorrelated reconstructions are provided by random complementary resampling masks. Experiments show a significant incoherent noise reduction, close to the theoretical improvement bound, resulting in image-contrast improvement. At the same time, we preserve the resolution of the unprocessed image.

FPGA implementation of ICA algorithm for blind signal separation and adaptive noise canceling.

Science.gov (United States)

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.

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

Science.gov (United States)

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

2018-04-01

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

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

Science.gov (United States)

Xu, Hui-Qun; Gui, Zhi-Xian

2014-03-01

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

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....

Active noise control in a duct to cancel broadband noise

Science.gov (United States)

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

2017-09-01

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

Stimulation of the Locus Ceruleus Modulates Signal-to-Noise Ratio in the Olfactory Bulb.

Science.gov (United States)

Manella, Laura C; Petersen, Nicholas; Linster, Christiane

2017-11-29

Norepinephrine (NE) has been shown to influence sensory, and specifically olfactory processing at the behavioral and physiological levels, potentially by regulating signal-to-noise ratio (S/N). The present study is the first to look at NE modulation of olfactory bulb (OB) in regards to S/N in vivo We show, in male rats, that locus ceruleus stimulation and pharmacological infusions of NE into the OB modulate both spontaneous and odor-evoked neural responses. NE in the OB generated a non-monotonic dose-response relationship, suppressing mitral cell activity at high and low, but not intermediate, NE levels. We propose that NE enhances odor responses not through direct potentiation of the afferent signal per se, but rather by reducing the intrinsic noise of the system. This has important implications for the ways in which an animal interacts with its olfactory environment, particularly as the animal shifts from a relaxed to an alert behavioral state. SIGNIFICANCE STATEMENT Sensory perception can be modulated by behavioral states such as hunger, fear, stress, or a change in environmental context. Behavioral state often affects neural processing via the release of circulating neurochemicals such as hormones or neuromodulators. We here show that the neuromodulator norepinephrine modulates olfactory bulb spontaneous activity and odor responses so as to generate an increased signal-to-noise ratio at the output of the olfactory bulb. Our results help interpret and improve existing ideas for neural network mechanisms underlying behaviorally observed improvements in near-threshold odor detection and discrimination. Copyright © 2017 the authors 0270-6474/17/3711605-11$15.00/0.

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

Science.gov (United States)

Miles, Jeffrey H.

2009-01-01

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

Study of pseudo noise CW diode laser for ranging applications

Science.gov (United States)

Lee, Hyo S.; Ramaswami, Ravi

1992-01-01

A new Pseudo Random Noise (PN) modulated CW diode laser radar system is being developed for real time ranging of targets at both close and large distances (greater than 10 KM) to satisy a wide range of applications: from robotics to future space applications. Results from computer modeling and statistical analysis, along with some preliminary data obtained from a prototype system, are presented. The received signal is averaged for a short time to recover the target response function. It is found that even with uncooperative targets, based on the design parameters used (200-mW laser and 20-cm receiver), accurate ranging is possible up to about 15 KM, beyond which signal to noise ratio (SNR) becomes too small for real time analog detection.

Filter apparatus for actively reducing noise

NARCIS (Netherlands)

Berkhoff, Arthur P.; Nijsse, G.

2010-01-01

A filter apparatus for reducing noise from a primary noise source, comprising a secondary source signal connector for generating secondary noise to reduce said primary noise and a sensor connector for connecting to a sensor for measuring said primary and secondary noise as an error signal. A first

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

NARCIS (Netherlands)

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

2016-01-01

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

A Bayesian test for periodic signals in red noise

Science.gov (United States)

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.

Adaptive noise reduction circuit for a sound reproduction system

Science.gov (United States)

Engebretson, A. Maynard (Inventor); O'Connell, Michael P. (Inventor)

1995-01-01

A noise reduction circuit for a hearing aid having an adaptive filter for producing a signal which estimates the noise components present in an input signal. The circuit includes a second filter for receiving the noise-estimating signal and modifying it as a function of a user's preference or as a function of an expected noise environment. The circuit also includes a gain control for adjusting the magnitude of the modified noise-estimating signal, thereby allowing for the adjustment of the magnitude of the circuit response. The circuit also includes a signal combiner for combining the input signal with the adjusted noise-estimating signal to produce a noise reduced output signal.

Electronic noise of superconducting tunnel junction detectors

International Nuclear Information System (INIS)

Jochum, J.; Kraus, H.; Gutsche, M.; Kemmather, B.; Feilitzsch, F. v.; Moessbauer, R.L.

1994-01-01

The optimal signal to noise ratio for detectors based on superconducting tunnel junctions is calculated and compared for the cases of a detector consisting of one single tunnel junction, as well as of series and of parallel connections of such tunnel junctions. The influence of 1 / f noise and its dependence on the dynamical resistance of tunnel junctions is discussed quantitatively. A single tunnel junction yields the minimum equivalent noise charge. Such a tunnel junction exhibits the best signal to noise ratio if the signal charge is independent of detector size. In case, signal charge increases with detector size, a parallel or a series connection of tunnel junctions would provide the optimum signal to noise ratio. The equivalent noise charge and the respective signal to noise ratio are deduced as functions of tunnel junction parameters such as tunneling time, quasiparticle lifetime, etc. (orig.)

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

Science.gov (United States)

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

2016-02-01

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

A de-noising algorithm based on wavelet threshold-exponential adaptive window width-fitting for ground electrical source airborne transient electromagnetic signal

Science.gov (United States)

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.

Noise Reduction for Nonlinear Nonstationary Time Series Data using Averaging Intrinsic Mode Function

Directory of Open Access Journals (Sweden)

Christofer Toumazou

2013-07-01

Full Text Available A novel noise filtering algorithm based on averaging Intrinsic Mode Function (aIMF, which is a derivation of Empirical Mode Decomposition (EMD, is proposed to remove white-Gaussian noise of foreign currency exchange rates that are nonlinear nonstationary times series signals. Noise patterns with different amplitudes and frequencies were randomly mixed into the five exchange rates. A number of filters, namely; Extended Kalman Filter (EKF, Wavelet Transform (WT, Particle Filter (PF and the averaging Intrinsic Mode Function (aIMF algorithm were used to compare filtering and smoothing performance. The aIMF algorithm demonstrated high noise reduction among the performance of these filters.