Chaotic oscillations and noise transformations in a simple dissipative system with delayed feedback

NASA Astrophysics Data System (ADS)

Zverev, V. V.; Rubinstein, B. Ya.

1991-04-01

We analyze the statistical behavior of signals in nonlinear circuits with delayed feedback in the presence of external Markovian noise. For the special class of circuits with intense phase mixing we develop an approach for the computation of the probability distributions and multitime correlation functions based on the random phase approximation. Both Gaussian and Kubo-Andersen models of external noise statistics are analyzed and the existence of the stationary (asymptotic) random process in the long-time limit is shown. We demonstrate that a nonlinear system with chaotic behavior becomes a noise amplifier with specific statistical transformation properties.

A Comprehensive Comparison of Multiparty Secure Additions with Differential Privacy

PubMed Central

Goryczka, Slawomir; Xiong, Li

2016-01-01

This paper considers the problem of secure data aggregation (mainly summation) in a distributed setting, while ensuring differential privacy of the result. We study secure multiparty addition protocols using well known security schemes: Shamir’s secret sharing, perturbation-based, and various encryptions. We supplement our study with our new enhanced encryption scheme EFT, which is efficient and fault tolerant. Differential privacy of the final result is achieved by either distributed Laplace or Geometric mechanism (respectively DLPA or DGPA), while approximated differential privacy is achieved by diluted mechanisms. Distributed random noise is generated collectively by all participants, which draw random variables from one of several distributions: Gamma, Gauss, Geometric, or their diluted versions. We introduce a new distributed privacy mechanism with noise drawn from the Laplace distribution, which achieves smaller redundant noise with efficiency. We compare complexity and security characteristics of the protocols with different differential privacy mechanisms and security schemes. More importantly, we implemented all protocols and present an experimental comparison on their performance and scalability in a real distributed environment. Based on the evaluations, we identify our security scheme and Laplace DLPA as the most efficient for secure distributed data aggregation with privacy. PMID:28919841

A Comprehensive Comparison of Multiparty Secure Additions with Differential Privacy.

PubMed

Goryczka, Slawomir; Xiong, Li

2017-01-01

This paper considers the problem of secure data aggregation (mainly summation) in a distributed setting, while ensuring differential privacy of the result. We study secure multiparty addition protocols using well known security schemes: Shamir's secret sharing, perturbation-based, and various encryptions. We supplement our study with our new enhanced encryption scheme EFT, which is efficient and fault tolerant. Differential privacy of the final result is achieved by either distributed Laplace or Geometric mechanism (respectively DLPA or DGPA), while approximated differential privacy is achieved by diluted mechanisms. Distributed random noise is generated collectively by all participants, which draw random variables from one of several distributions: Gamma, Gauss, Geometric, or their diluted versions. We introduce a new distributed privacy mechanism with noise drawn from the Laplace distribution, which achieves smaller redundant noise with efficiency. We compare complexity and security characteristics of the protocols with different differential privacy mechanisms and security schemes. More importantly, we implemented all protocols and present an experimental comparison on their performance and scalability in a real distributed environment. Based on the evaluations, we identify our security scheme and Laplace DLPA as the most efficient for secure distributed data aggregation with privacy.

Adaptive threshold shearlet transform for surface microseismic data denoising

NASA Astrophysics Data System (ADS)

Tang, Na; Zhao, Xian; Li, Yue; Zhu, Dan

2018-06-01

Random noise suppression plays an important role in microseismic data processing. The microseismic data is often corrupted by strong random noise, which would directly influence identification and location of microseismic events. Shearlet transform is a new multiscale transform, which can effectively process the low magnitude of microseismic data. In shearlet domain, due to different distributions of valid signals and random noise, shearlet coefficients can be shrunk by threshold. Therefore, threshold is vital in suppressing random noise. The conventional threshold denoising algorithms usually use the same threshold to process all coefficients, which causes noise suppression inefficiency or valid signals loss. In order to solve above problems, we propose the adaptive threshold shearlet transform (ATST) for surface microseismic data denoising. In the new algorithm, we calculate the fundamental threshold for each direction subband firstly. In each direction subband, the adjustment factor is obtained according to each subband coefficient and its neighboring coefficients, in order to adaptively regulate the fundamental threshold for different shearlet coefficients. Finally we apply the adaptive threshold to deal with different shearlet coefficients. The experimental denoising results of synthetic records and field data illustrate that the proposed method exhibits better performance in suppressing random noise and preserving valid signal than the conventional shearlet denoising method.

Approximations to camera sensor noise

NASA Astrophysics Data System (ADS)

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.

Evaluation of the accuracy of the Rotating Parallel Ray Omnidirectional Integration for instantaneous pressure reconstruction from the measured pressure gradient

NASA Astrophysics Data System (ADS)

Moreto, Jose; Liu, Xiaofeng

2017-11-01

The accuracy of the Rotating Parallel Ray omnidirectional integration for pressure reconstruction from the measured pressure gradient (Liu et al., AIAA paper 2016-1049) is evaluated against both the Circular Virtual Boundary omnidirectional integration (Liu and Katz, 2006 and 2013) and the conventional Poisson equation approach. Dirichlet condition at one boundary point and Neumann condition at all other boundary points are applied to the Poisson solver. A direct numerical simulation database of isotropic turbulence flow (JHTDB), with a homogeneously distributed random noise added to the entire field of DNS pressure gradient, is used to assess the performance of the methods. The random noise, generated by the Matlab function Rand, has a magnitude varying randomly within the range of +/-40% of the maximum DNS pressure gradient. To account for the effect of the noise distribution pattern on the reconstructed pressure accuracy, a total of 1000 different noise distributions achieved by using different random number seeds are involved in the evaluation. Final results after averaging the 1000 realizations show that the error of the reconstructed pressure normalized by the DNS pressure variation range is 0.15 +/-0.07 for the Poisson equation approach, 0.028 +/-0.003 for the Circular Virtual Boundary method and 0.027 +/-0.003 for the Rotating Parallel Ray method, indicating the robustness of the Rotating Parallel Ray method in pressure reconstruction. Sponsor: The San Diego State University UGP program.

Effect of random phase mask on input plane in photorefractive authentic memory with two-wave encryption method

NASA Astrophysics Data System (ADS)

Mita, Akifumi; Okamoto, Atsushi; Funakoshi, Hisatoshi

2004-06-01

We have proposed an all-optical authentic memory with the two-wave encryption method. In the recording process, the image data are encrypted to a white noise by the random phase masks added on the input beam with the image data and the reference beam. Only reading beam with the phase-conjugated distribution of the reference beam can decrypt the encrypted data. If the encrypted data are read out with an incorrect phase distribution, the output data are transformed into a white noise. Moreover, during read out, reconstructions of the encrypted data interfere destructively resulting in zero intensity. Therefore our memory has a merit that we can detect unlawful accesses easily by measuring the output beam intensity. In our encryption method, the random phase mask on the input plane plays important roles in transforming the input image into a white noise and prohibiting to decrypt a white noise to the input image by the blind deconvolution method. Without this mask, when unauthorized users observe the output beam by using CCD in the readout with the plane wave, the completely same intensity distribution as that of Fourier transform of the input image is obtained. Therefore the encrypted image will be decrypted easily by using the blind deconvolution method. However in using this mask, even if unauthorized users observe the output beam using the same method, the encrypted image cannot be decrypted because the observed intensity distribution is dispersed at random by this mask. Thus it can be said the robustness is increased by this mask. In this report, we compare two correlation coefficients, which represents the degree of a white noise of the output image, between the output image and the input image in using this mask or not. We show that the robustness of this encryption method is increased as the correlation coefficient is improved from 0.3 to 0.1 by using this mask.

Shapiro effect as a possible cause of the low-frequency pulsar timing noise in globular clusters

NASA Astrophysics Data System (ADS)

Larchenkova, T. I.; Kopeikin, S. M.

2006-01-01

A prolonged timing of millisecond pulsars has revealed low-frequency uncorrelated (infrared) noise, presumably of astrophysical origin, in the pulse arrival time (PAT) residuals for some of them. Currently available pulsar timing methods allow the statistical parameters of this noise to be reliably measured by decomposing the PAT residual function into orthogonal Fourier harmonics. In most cases, pulsars in globular clusters show a low-frequency modulation of their rotational phase and spin rate. The relativistic time delay of the pulsar signal in the curved spacetime of randomly distributed and moving globular cluster stars (the Shapiro effect) is suggested as a possible cause of this modulation. Extremely important (from an astrophysical point of view) information about the structure of the globular cluster core, which is inaccessible to study by other observational methods, could be obtained by analyzing the spectral parameters of the low-frequency noise caused by the Shapiro effect and attributable to the random passages of stars near the line of sight to the pulsar. Given the smallness of the aberration corrections that arise from the nonstationarity of the gravitational field of the randomly distributed ensemble of stars under consideration, a formula is derived for the Shapiro effect for a pulsar in a globular cluster. The derived formula is used to calculate the autocorrelation function of the low-frequency pulsar noise, the slope of its power spectrum, and the behavior of the σz statistic that characterizes the spectral properties of this noise in the form of a time function. The Shapiro effect under discussion is shown to manifest itself for large impact parameters as a low-frequency noise of the pulsar spin rate with a spectral index of n = -1.8 that depends weakly on the specific model distribution of stars in the globular cluster. For small impact parameters, the spectral index of the noise is n = -1.5.

Spectral filtering of gradient for l2-norm frequency-domain elastic waveform inversion

NASA Astrophysics Data System (ADS)

Oh, Ju-Won; Min, Dong-Joo

2013-05-01

To enhance the robustness of the l2-norm elastic full-waveform inversion (FWI), we propose a denoise function that is incorporated into single-frequency gradients. Because field data are noisy and modelled data are noise-free, the denoise function is designed based on the ratio of modelled data to field data summed over shots and receivers. We first take the sums of the modelled data and field data over shots, then take the sums of the absolute values of the resultant modelled data and field data over the receivers. Due to the monochromatic property of wavefields at each frequency, signals in both modelled and field data tend to be cancelled out or maintained, whereas certain types of noise, particularly random noise, can be amplified in field data. As a result, the spectral distribution of the denoise function is inversely proportional to the ratio of noise to signal at each frequency, which helps prevent the noise-dominant gradients from contributing to model parameter updates. Numerical examples show that the spectral distribution of the denoise function resembles a frequency filter that is determined by the spectrum of the signal-to-noise (S/N) ratio during the inversion process, with little human intervention. The denoise function is applied to the elastic FWI of synthetic data, with three types of random noise generated by the modified version of the Marmousi-2 model: white, low-frequency and high-frequency random noises. Based on the spectrum of S/N ratios at each frequency, the denoise function mainly suppresses noise-dominant single-frequency gradients, which improves the inversion results at the cost of spatial resolution.

Cooperation evolution in random multiplicative environments

NASA Astrophysics Data System (ADS)

Yaari, G.; Solomon, S.

2010-02-01

Most real life systems have a random component: the multitude of endogenous and exogenous factors influencing them result in stochastic fluctuations of the parameters determining their dynamics. These empirical systems are in many cases subject to noise of multiplicative nature. The special properties of multiplicative noise as opposed to additive noise have been noticed for a long while. Even though apparently and formally the difference between free additive vs. multiplicative random walks consists in just a move from normal to log-normal distributions, in practice the implications are much more far reaching. While in an additive context the emergence and survival of cooperation requires special conditions (especially some level of reward, punishment, reciprocity), we find that in the multiplicative random context the emergence of cooperation is much more natural and effective. We study the various implications of this observation and its applications in various contexts.

Reduction of Poisson noise in measured time-resolved data for time-domain diffuse optical tomography.

PubMed

Okawa, S; Endo, Y; Hoshi, Y; Yamada, Y

2012-01-01

A method to reduce noise for time-domain diffuse optical tomography (DOT) is proposed. Poisson noise which contaminates time-resolved photon counting data is reduced by use of maximum a posteriori estimation. The noise-free data are modeled as a Markov random process, and the measured time-resolved data are assumed as Poisson distributed random variables. The posterior probability of the occurrence of the noise-free data is formulated. By maximizing the probability, the noise-free data are estimated, and the Poisson noise is reduced as a result. The performances of the Poisson noise reduction are demonstrated in some experiments of the image reconstruction of time-domain DOT. In simulations, the proposed method reduces the relative error between the noise-free and noisy data to about one thirtieth, and the reconstructed DOT image was smoothed by the proposed noise reduction. The variance of the reconstructed absorption coefficients decreased by 22% in a phantom experiment. The quality of DOT, which can be applied to breast cancer screening etc., is improved by the proposed noise reduction.

Stochastic transport in the presence of spatial disorder: Fluctuation-induced corrections to homogenization

NASA Astrophysics Data System (ADS)

Russell, Matthew J.; Jensen, Oliver E.; Galla, Tobias

2016-10-01

Motivated by uncertainty quantification in natural transport systems, we investigate an individual-based transport process involving particles undergoing a random walk along a line of point sinks whose strengths are themselves independent random variables. We assume particles are removed from the system via first-order kinetics. We analyze the system using a hierarchy of approaches when the sinks are sparsely distributed, including a stochastic homogenization approximation that yields explicit predictions for the extrinsic disorder in the stationary state due to sink strength fluctuations. The extrinsic noise induces long-range spatial correlations in the particle concentration, unlike fluctuations due to the intrinsic noise alone. Additionally, the mean concentration profile, averaged over both intrinsic and extrinsic noise, is elevated compared with the corresponding profile from a uniform sink distribution, showing that the classical homogenization approximation can be a biased estimator of the true mean.

Power-law Exponent in Multiplicative Langevin Equation with Temporally Correlated Noise

NASA Astrophysics Data System (ADS)

Morita, Satoru

2018-05-01

Power-law distributions are ubiquitous in nature. Random multiplicative processes are a basic model for the generation of power-law distributions. For discrete-time systems, the power-law exponent is known to decrease as the autocorrelation time of the multiplier increases. However, for continuous-time systems, it is not yet clear how the temporal correlation affects the power-law behavior. Herein, we analytically investigated a multiplicative Langevin equation with colored noise. We show that the power-law exponent depends on the details of the multiplicative noise, in contrast to the case of discrete-time systems.

Channel doping concentration and cell program state dependence on random telegraph noise spatial and statistical distribution in 30 nm NAND flash memory

NASA Astrophysics Data System (ADS)

Tomita, Toshihiro; Miyaji, Kousuke

2015-04-01

The dependence of spatial and statistical distribution of random telegraph noise (RTN) in a 30 nm NAND flash memory on channel doping concentration NA and cell program state Vth is comprehensively investigated using three-dimensional Monte Carlo device simulation considering random dopant fluctuation (RDF). It is found that single trap RTN amplitude ΔVth is larger at the center of the channel region in the NAND flash memory, which is closer to the jellium (uniform) doping results since NA is relatively low to suppress junction leakage current. In addition, ΔVth peak at the center of the channel decreases in the higher Vth state due to the current concentration at the shallow trench isolation (STI) edges induced by the high vertical electrical field through the fringing capacitance between the channel and control gate. In such cases, ΔVth distribution slope λ cannot be determined by only considering RDF and single trap.

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

PubMed

Mainprize, James G; Yaffe, Martin J

2010-10-01

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

Distributed acoustic sensing: how to make the best out of the Rayleigh-backscattered energy?

NASA Astrophysics Data System (ADS)

Eyal, A.; Gabai, H.; Shpatz, I.

2017-04-01

Coherent fading noise (also known as speckle noise) affects the SNR and sensitivity of Distributed Acoustic Sensing (DAS) systems and makes them random processes of position and time. As in speckle noise, the statistical distribution of DAS SNR is particularly wide and its standard deviation (STD) roughly equals its mean (σSNR/ ≍ 0.89). Trading resolution for SNR may improve the mean SNR but not necessarily narrow its distribution. Here a new approach to achieve both SNR improvement (by sacrificing resolution) and narrowing of the distribution is introduced. The method is based on acquiring high resolution complex backscatter profiles of the sensing fiber, using them to compute complex power profiles of the fiber which retain phase variation information and filtering of the power profiles. The approach is tested via a computer simulation and demonstrates distribution narrowing up to σSNR/ < 0.2.

Distributed Monte Carlo Information Fusion and Distributed Particle Filtering

DTIC Science & Technology

2014-08-24

Distributed Monte Carlo Information Fusion and Distributed Particle Filtering Isaac L. Manuel and Adrian N. Bishop Australian National University and...2 20 + vit , (21) where vit is Gaussian white noise with a random variance. We initialised the filters with the state xi0 = 0.1 for all i ∈ V . This

Energy-Based Wavelet De-Noising of Hydrologic Time Series

PubMed Central

Sang, Yan-Fang; Liu, Changming; Wang, Zhonggen; Wen, Jun; Shang, Lunyu

2014-01-01

De-noising is a substantial issue in hydrologic time series analysis, but it is a difficult task due to the defect of methods. In this paper an energy-based wavelet de-noising method was proposed. It is to remove noise by comparing energy distribution of series with the background energy distribution, which is established from Monte-Carlo test. Differing from wavelet threshold de-noising (WTD) method with the basis of wavelet coefficient thresholding, the proposed method is based on energy distribution of series. It can distinguish noise from deterministic components in series, and uncertainty of de-noising result can be quantitatively estimated using proper confidence interval, but WTD method cannot do this. Analysis of both synthetic and observed series verified the comparable power of the proposed method and WTD, but de-noising process by the former is more easily operable. The results also indicate the influences of three key factors (wavelet choice, decomposition level choice and noise content) on wavelet de-noising. Wavelet should be carefully chosen when using the proposed method. The suitable decomposition level for wavelet de-noising should correspond to series' deterministic sub-signal which has the smallest temporal scale. If too much noise is included in a series, accurate de-noising result cannot be obtained by the proposed method or WTD, but the series would show pure random but not autocorrelation characters, so de-noising is no longer needed. PMID:25360533

Noise Analysis of Simultaneous Quantum Key Distribution and Classical Communication Scheme Using a True Local Oscillator

DOE PAGES

Qi, Bing; Lim, Charles Ci Wen

2018-05-07

Recently, we proposed a simultaneous quantum and classical communication (SQCC) protocol where random numbers for quantum key distribution and bits for classical communication are encoded on the same weak coherent pulse and decoded by the same coherent receiver. Such a scheme could be appealing in practice since a single coherent communication system can be used for multiple purposes. However, previous studies show that the SQCC protocol can tolerate only very small phase noise. This makes it incompatible with the coherent communication scheme using a true local oscillator (LO), which presents a relatively high phase noise due to the fact thatmore » the signal and the LO are generated from two independent lasers. We improve the phase noise tolerance of the SQCC scheme using a true LO by adopting a refined noise model where phase noises originating from different sources are treated differently: on the one hand, phase noise associated with the coherent receiver may be regarded as trusted noise since the detector can be calibrated locally and the photon statistics of the detected signals can be determined from the measurement results; on the other hand, phase noise due to the instability of fiber interferometers may be regarded as untrusted noise since its randomness (from the adversary’s point of view) is hard to justify. Simulation results show the tolerable phase noise in this refined noise model is significantly higher than that in the previous study, where all of the phase noises are assumed to be untrusted. In conclusion, we conduct an experiment to show that the required phase stability can be achieved in a coherent communication system using a true LO.« less

Noise Analysis of Simultaneous Quantum Key Distribution and Classical Communication Scheme Using a True Local Oscillator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qi, Bing; Lim, Charles Ci Wen

Recently, we proposed a simultaneous quantum and classical communication (SQCC) protocol where random numbers for quantum key distribution and bits for classical communication are encoded on the same weak coherent pulse and decoded by the same coherent receiver. Such a scheme could be appealing in practice since a single coherent communication system can be used for multiple purposes. However, previous studies show that the SQCC protocol can tolerate only very small phase noise. This makes it incompatible with the coherent communication scheme using a true local oscillator (LO), which presents a relatively high phase noise due to the fact thatmore » the signal and the LO are generated from two independent lasers. We improve the phase noise tolerance of the SQCC scheme using a true LO by adopting a refined noise model where phase noises originating from different sources are treated differently: on the one hand, phase noise associated with the coherent receiver may be regarded as trusted noise since the detector can be calibrated locally and the photon statistics of the detected signals can be determined from the measurement results; on the other hand, phase noise due to the instability of fiber interferometers may be regarded as untrusted noise since its randomness (from the adversary’s point of view) is hard to justify. Simulation results show the tolerable phase noise in this refined noise model is significantly higher than that in the previous study, where all of the phase noises are assumed to be untrusted. In conclusion, we conduct an experiment to show that the required phase stability can be achieved in a coherent communication system using a true LO.« less

Noise Analysis of Simultaneous Quantum Key Distribution and Classical Communication Scheme Using a True Local Oscillator

NASA Astrophysics Data System (ADS)

Qi, Bing; Lim, Charles Ci Wen

2018-05-01

Recently, we proposed a simultaneous quantum and classical communication (SQCC) protocol where random numbers for quantum key distribution and bits for classical communication are encoded on the same weak coherent pulse and decoded by the same coherent receiver. Such a scheme could be appealing in practice since a single coherent communication system can be used for multiple purposes. However, previous studies show that the SQCC protocol can tolerate only very small phase noise. This makes it incompatible with the coherent communication scheme using a true local oscillator (LO), which presents a relatively high phase noise due to the fact that the signal and the LO are generated from two independent lasers. We improve the phase noise tolerance of the SQCC scheme using a true LO by adopting a refined noise model where phase noises originating from different sources are treated differently: on the one hand, phase noise associated with the coherent receiver may be regarded as trusted noise since the detector can be calibrated locally and the photon statistics of the detected signals can be determined from the measurement results; on the other hand, phase noise due to the instability of fiber interferometers may be regarded as untrusted noise since its randomness (from the adversary's point of view) is hard to justify. Simulation results show the tolerable phase noise in this refined noise model is significantly higher than that in the previous study, where all of the phase noises are assumed to be untrusted. We conduct an experiment to show that the required phase stability can be achieved in a coherent communication system using a true LO.

Effect of signal jitter on the spectrum of rotor impulsive noise

NASA Technical Reports Server (NTRS)

Brooks, Thomas F.

1987-01-01

The effect of randomness or jitter of the acoustic waveform on the spectrum of rotor impulsive noise is studied because of its importance for data interpretation. An acoustic waveform train is modelled representing rotor impulsive noise. The amplitude, shape, and period between occurrences of individual pulses are allowed to be randomized assuming normal probability distributions. Results, in terms of the standard deviations of the variable quantities, are given for the autospectrum as well as special processed spectra designed to separate harmonic and broadband rotor noise components. Consideration is given to the effect of accuracy in triggering or keying to a rotor one per revolution signal. An example is given showing the resultant spectral smearing at the high frequencies due to the pulse signal period variability.

Effect of signal jitter on the spectrum of rotor impulsive noise

NASA Technical Reports Server (NTRS)

Brooks, Thomas F.

1988-01-01

The effect of randomness or jitter of the acoustic waveform on the spectrum of rotor impulsive noise is studied because of its importance for data interpretation. An acoustic waveform train is modeled representing rotor impulsive noise. The amplitude, shape, and period between occurrences of individual pulses are allowed to be randomized assuming normal probability distributions. Results, in terms of the standard deviations of the variable quantities, are given for the autospectrum as well as special processed spectra designed to separate harmonic and broadband rotor noise components. Consideration is given to the effect of accuracy in triggering or keying to a rotor one per revolution signal. An example is given showing the resultant spectral smearing at the high frequencies due to the pulse signal period variability.

Statistical Analysis of the Random Telegraph Noise in a 1.1 μm Pixel, 8.3 MP CMOS Image Sensor Using On-Chip Time Constant Extraction Method.

PubMed

Chao, Calvin Yi-Ping; Tu, Honyih; Wu, Thomas Meng-Hsiu; Chou, Kuo-Yu; Yeh, Shang-Fu; Yin, Chin; Lee, Chih-Lin

2017-11-23

A study of the random telegraph noise (RTN) of a 1.1 μm pitch, 8.3 Mpixel CMOS image sensor (CIS) fabricated in a 45 nm backside-illumination (BSI) technology is presented in this paper. A noise decomposition scheme is used to pinpoint the noise source. The long tail of the random noise (RN) distribution is directly linked to the RTN from the pixel source follower (SF). The full 8.3 Mpixels are classified into four categories according to the observed RTN histogram peaks. A theoretical formula describing the RTN as a function of the time difference between the two phases of the correlated double sampling (CDS) is derived and validated by measured data. An on-chip time constant extraction method is developed and applied to the RTN analysis. The effects of readout circuit bandwidth on the settling ratios of the RTN histograms are investigated and successfully accounted for in a simulation using a RTN behavior model.

Modeling and statistical analysis of non-Gaussian random fields with heavy-tailed distributions.

PubMed

Nezhadhaghighi, Mohsen Ghasemi; Nakhlband, Abbas

2017-04-01

In this paper, we investigate and develop an alternative approach to the numerical analysis and characterization of random fluctuations with the heavy-tailed probability distribution function (PDF), such as turbulent heat flow and solar flare fluctuations. We identify the heavy-tailed random fluctuations based on the scaling properties of the tail exponent of the PDF, power-law growth of qth order correlation function, and the self-similar properties of the contour lines in two-dimensional random fields. Moreover, this work leads to a substitution for the fractional Edwards-Wilkinson (EW) equation that works in the presence of μ-stable Lévy noise. Our proposed model explains the configuration dynamics of the systems with heavy-tailed correlated random fluctuations. We also present an alternative solution to the fractional EW equation in the presence of μ-stable Lévy noise in the steady state, which is implemented numerically, using the μ-stable fractional Lévy motion. Based on the analysis of the self-similar properties of contour loops, we numerically show that the scaling properties of contour loop ensembles can qualitatively and quantitatively distinguish non-Gaussian random fields from Gaussian random fluctuations.

The effects of noise due to random undetected tilts and paleosecular variation on regional paleomagnetic directions

USGS Publications Warehouse

Calderone, G.J.; Butler, R.F.

1991-01-01

Random tilting of a single paleomagnetic vector produces a distribution of vectors which is not rotationally symmetric about the original vector and therefore not Fisherian. Monte Carlo simulations were performed on two types of vector distributions: 1) distributions of vectors formed by perturbing a single original vector with a Fisher distribution of bedding poles (each defining a tilt correction) and 2) standard Fisher distributions. These simulations demonstrate that inclinations of vectors drawn from both distributions are biased toward shallow inclinations. The Fisher mean direction of the distribution of vectors formed by perturbing a single vector with random undetected tilts is biased toward shallow inclinations, but this bias is insignificant for angular dispersions of bedding poles less than 20??. -from Authors

Digital simulation of two-dimensional random fields with arbitrary power spectra and non-Gaussian probability distribution functions.

PubMed

Yura, Harold T; Hanson, Steen G

2012-04-01

Methods for simulation of two-dimensional signals with arbitrary power spectral densities and signal amplitude probability density functions are disclosed. The method relies on initially transforming a white noise sample set of random Gaussian distributed numbers into a corresponding set with the desired spectral distribution, after which this colored Gaussian probability distribution is transformed via an inverse transform into the desired probability distribution. In most cases the method provides satisfactory results and can thus be considered an engineering approach. Several illustrative examples with relevance for optics are given.

Intercellular Variability in Protein Levels from Stochastic Expression and Noisy Cell Cycle Processes

PubMed Central

Soltani, Mohammad; Vargas-Garcia, Cesar A.; Antunes, Duarte; Singh, Abhyudai

2016-01-01

Inside individual cells, expression of genes is inherently stochastic and manifests as cell-to-cell variability or noise in protein copy numbers. Since proteins half-lives can be comparable to the cell-cycle length, randomness in cell-division times generates additional intercellular variability in protein levels. Moreover, as many mRNA/protein species are expressed at low-copy numbers, errors incurred in partitioning of molecules between two daughter cells are significant. We derive analytical formulas for the total noise in protein levels when the cell-cycle duration follows a general class of probability distributions. Using a novel hybrid approach the total noise is decomposed into components arising from i) stochastic expression; ii) partitioning errors at the time of cell division and iii) random cell-division events. These formulas reveal that random cell-division times not only generate additional extrinsic noise, but also critically affect the mean protein copy numbers and intrinsic noise components. Counter intuitively, in some parameter regimes, noise in protein levels can decrease as cell-division times become more stochastic. Computations are extended to consider genome duplication, where transcription rate is increased at a random point in the cell cycle. We systematically investigate how the timing of genome duplication influences different protein noise components. Intriguingly, results show that noise contribution from stochastic expression is minimized at an optimal genome-duplication time. Our theoretical results motivate new experimental methods for decomposing protein noise levels from synchronized and asynchronized single-cell expression data. Characterizing the contributions of individual noise mechanisms will lead to precise estimates of gene expression parameters and techniques for altering stochasticity to change phenotype of individual cells. PMID:27536771

Noise in Attractor Networks in the Brain Produced by Graded Firing Rate Representations

PubMed Central

Webb, Tristan J.; Rolls, Edmund T.; Deco, Gustavo; Feng, Jianfeng

2011-01-01

Representations in the cortex are often distributed with graded firing rates in the neuronal populations. The firing rate probability distribution of each neuron to a set of stimuli is often exponential or gamma. In processes in the brain, such as decision-making, that are influenced by the noise produced by the close to random spike timings of each neuron for a given mean rate, the noise with this graded type of representation may be larger than with the binary firing rate distribution that is usually investigated. In integrate-and-fire simulations of an attractor decision-making network, we show that the noise is indeed greater for a given sparseness of the representation for graded, exponential, than for binary firing rate distributions. The greater noise was measured by faster escaping times from the spontaneous firing rate state when the decision cues are applied, and this corresponds to faster decision or reaction times. The greater noise was also evident as less stability of the spontaneous firing state before the decision cues are applied. The implication is that spiking-related noise will continue to be a factor that influences processes such as decision-making, signal detection, short-term memory, and memory recall even with the quite large networks found in the cerebral cortex. In these networks there are several thousand recurrent collateral synapses onto each neuron. The greater noise with graded firing rate distributions has the advantage that it can increase the speed of operation of cortical circuitry. PMID:21931607

Does prism width from the shell prismatic layer have a random distribution?

NASA Astrophysics Data System (ADS)

Vancolen, Séverine; Verrecchia, Eric

2008-10-01

A study of the distribution of the prism width inside the prismatic layer of Unio tumidus (Philipsson 1788, Diss Hist-Nat, Berling, Lundæ) from Lake Neuchâtel, Switzerland, has been conducted in order to determine whether or not this distribution is random. Measurements of 954 to 1,343 prism widths (depending on shell sample) have been made using a scanning electron microscope in backscattered electron mode. A white noise test has been applied to the distribution of prism sizes (i.e. width). It shows that there is no temporal cycle that could potentially influence their formation and growth. These results suggest that prism widths are randomly distributed, and related neither to external rings nor to environmental constraints.

Magnetic noise as the cause of the spontaneous magnetization reversal of RE–TM–B permanent magnets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dmitriev, A. I., E-mail: aid@icp.ac.ru; Talantsev, A. D., E-mail: artgtx32@mail.ru; Kunitsyna, E. I.

2016-08-15

The relation between the macroscopic spontaneous magnetization reversal (magnetic viscosity) of (NdDySm)(FeCo)B alloys and the spectral characteristics of magnetic noise, which is caused by the random microscopic processes of thermally activated domain wall motion in a potential landscape with uniformly distributed potential barrier heights, is found.

An Effective Post-Filtering Framework for 3-D PET Image Denoising Based on Noise and Sensitivity Characteristics

NASA Astrophysics Data System (ADS)

Kim, Ji Hye; Ahn, Il Jun; Nam, Woo Hyun; Ra, Jong Beom

2015-02-01

Positron emission tomography (PET) images usually suffer from a noticeable amount of statistical noise. In order to reduce this noise, a post-filtering process is usually adopted. However, the performance of this approach is limited because the denoising process is mostly performed on the basis of the Gaussian random noise. It has been reported that in a PET image reconstructed by the expectation-maximization (EM), the noise variance of each voxel depends on its mean value, unlike in the case of Gaussian noise. In addition, we observe that the variance also varies with the spatial sensitivity distribution in a PET system, which reflects both the solid angle determined by a given scanner geometry and the attenuation information of a scanned object. Thus, if a post-filtering process based on the Gaussian random noise is applied to PET images without consideration of the noise characteristics along with the spatial sensitivity distribution, the spatially variant non-Gaussian noise cannot be reduced effectively. In the proposed framework, to effectively reduce the noise in PET images reconstructed by the 3-D ordinary Poisson ordered subset EM (3-D OP-OSEM), we first denormalize an image according to the sensitivity of each voxel so that the voxel mean value can represent its statistical properties reliably. Based on our observation that each noisy denormalized voxel has a linear relationship between the mean and variance, we try to convert this non-Gaussian noise image to a Gaussian noise image. We then apply a block matching 4-D algorithm that is optimized for noise reduction of the Gaussian noise image, and reconvert and renormalize the result to obtain a final denoised image. Using simulated phantom data and clinical patient data, we demonstrate that the proposed framework can effectively suppress the noise over the whole region of a PET image while minimizing degradation of the image resolution.

Frequency domain analysis of errors in cross-correlations of ambient seismic noise

NASA Astrophysics Data System (ADS)

Liu, Xin; Ben-Zion, Yehuda; Zigone, Dimitri

2016-12-01

We analyse random errors (variances) in cross-correlations of ambient seismic noise in the frequency domain, which differ from previous time domain methods. Extending previous theoretical results on ensemble averaged cross-spectrum, we estimate confidence interval of stacked cross-spectrum of finite amount of data at each frequency using non-overlapping windows with fixed length. The extended theory also connects amplitude and phase variances with the variance of each complex spectrum value. Analysis of synthetic stationary ambient noise is used to estimate the confidence interval of stacked cross-spectrum obtained with different length of noise data corresponding to different number of evenly spaced windows of the same duration. This method allows estimating Signal/Noise Ratio (SNR) of noise cross-correlation in the frequency domain, without specifying filter bandwidth or signal/noise windows that are needed for time domain SNR estimations. Based on synthetic ambient noise data, we also compare the probability distributions, causal part amplitude and SNR of stacked cross-spectrum function using one-bit normalization or pre-whitening with those obtained without these pre-processing steps. Natural continuous noise records contain both ambient noise and small earthquakes that are inseparable from the noise with the existing pre-processing steps. Using probability distributions of random cross-spectrum values based on the theoretical results provides an effective way to exclude such small earthquakes, and additional data segments (outliers) contaminated by signals of different statistics (e.g. rain, cultural noise), from continuous noise waveforms. This technique is applied to constrain values and uncertainties of amplitude and phase velocity of stacked noise cross-spectrum at different frequencies, using data from southern California at both regional scale (˜35 km) and dense linear array (˜20 m) across the plate-boundary faults. A block bootstrap resampling method is used to account for temporal correlation of noise cross-spectrum at low frequencies (0.05-0.2 Hz) near the ocean microseismic peaks.

Aircraft adaptive learning control

NASA Technical Reports Server (NTRS)

Lee, P. S. T.; Vanlandingham, H. F.

1979-01-01

The optimal control theory of stochastic linear systems is discussed in terms of the advantages of distributed-control systems, and the control of randomly-sampled systems. An optimal solution to longitudinal control is derived and applied to the F-8 DFBW aircraft. A randomly-sampled linear process model with additive process and noise is developed.

A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution.

PubMed

Hayashi, Hideaki; Furui, Akira; Kurita, Yuichi; Tsuji, Toshio

2017-11-01

Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force. Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force.

Development and Evaluation of a Multistatic Ultrawideband Random Noise Radar

DTIC Science & Technology

2010-03-01

noncoherent MIMO investigates 13 a statistical diversity gain available to systems with widely separated antennas per- forming a distributed detection...design. When widely distributed antenna are operating as a MIMO radar system, research shows a noncoherent signal gain is realized, if there exists

Diffusion MRI noise mapping using random matrix theory

PubMed Central

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

2016-01-01

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Giovannetti, Vittorio; Maccone, Lorenzo; Shapiro, Jeffrey H.

The minimum Renyi and Wehrl output entropies are found for bosonic channels in which the signal photons are either randomly displaced by a Gaussian distribution (classical-noise channel), or coupled to a thermal environment through lossy propagation (thermal-noise channel). It is shown that the Renyi output entropies of integer orders z{>=}2 and the Wehrl output entropy are minimized when the channel input is a coherent state.

Exploring conservative islands using correlated and uncorrelated noise

NASA Astrophysics Data System (ADS)

da Silva, Rafael M.; Manchein, Cesar; Beims, Marcus W.

2018-02-01

In this work, noise is used to analyze the penetration of regular islands in conservative dynamical systems. For this purpose we use the standard map choosing nonlinearity parameters for which a mixed phase space is present. The random variable which simulates noise assumes three distributions, namely equally distributed, normal or Gaussian, and power law (obtained from the same standard map but for other parameters). To investigate the penetration process and explore distinct dynamical behaviors which may occur, we use recurrence time statistics (RTS), Lyapunov exponents and the occupation rate of the phase space. Our main findings are as follows: (i) the standard deviations of the distributions are the most relevant quantity to induce the penetration; (ii) the penetration of islands induce power-law decays in the RTS as a consequence of enhanced trapping; (iii) for the power-law correlated noise an algebraic decay of the RTS is observed, even though sticky motion is absent; and (iv) although strong noise intensities induce an ergodic-like behavior with exponential decays of RTS, the largest Lyapunov exponent is reminiscent of the regular islands.

Non local means denoising in photoacoustic imaging

NASA Astrophysics Data System (ADS)

Siregar, Syahril; Nagaoka, Ryo; Haq, Israr Ul; Saijo, Yoshifumi

2018-07-01

Photoacoustic (PA) imaging has the ability to visualize human organs with high spatial resolution and high contrast. Like digital images, PA images are contaminated with random noise due to some parameters. The band-pass filter does not effectively remove the noise because noise is randomly distributed in the bandwidth frequency. We present noise removal method in PA images by using non local means denoising (NLMD) method. The NLMD can be used if there are similarities or redundancies in the image. PA images contain of blood vessel which repeating on the small patch. The method was tested on PA images of carbon nanotubes in micropipe, in vivo mice brain and in vivo mice ear. We estimated the suggested input parameters of NLMD, so it can be automatically applied after scanning the image in PA imaging system. Our results declared that the NLMD enhanced the image quality of PA images.

Eigenvalues of Random Matrices with Isotropic Gaussian Noise and the Design of Diffusion Tensor Imaging Experiments.

PubMed

Gasbarra, Dario; Pajevic, Sinisa; Basser, Peter J

2017-01-01

Tensor-valued and matrix-valued measurements of different physical properties are increasingly available in material sciences and medical imaging applications. The eigenvalues and eigenvectors of such multivariate data provide novel and unique information, but at the cost of requiring a more complex statistical analysis. In this work we derive the distributions of eigenvalues and eigenvectors in the special but important case of m×m symmetric random matrices, D , observed with isotropic matrix-variate Gaussian noise. The properties of these distributions depend strongly on the symmetries of the mean tensor/matrix, D̄ . When D̄ has repeated eigenvalues, the eigenvalues of D are not asymptotically Gaussian, and repulsion is observed between the eigenvalues corresponding to the same D̄ eigenspaces. We apply these results to diffusion tensor imaging (DTI), with m = 3, addressing an important problem of detecting the symmetries of the diffusion tensor, and seeking an experimental design that could potentially yield an isotropic Gaussian distribution. In the 3-dimensional case, when the mean tensor is spherically symmetric and the noise is Gaussian and isotropic, the asymptotic distribution of the first three eigenvalue central moment statistics is simple and can be used to test for isotropy. In order to apply such tests, we use quadrature rules of order t ≥ 4 with constant weights on the unit sphere to design a DTI-experiment with the property that isotropy of the underlying true tensor implies isotropy of the Fisher information. We also explain the potential implications of the methods using simulated DTI data with a Rician noise model.

Eigenvalues of Random Matrices with Isotropic Gaussian Noise and the Design of Diffusion Tensor Imaging Experiments*

PubMed Central

Gasbarra, Dario; Pajevic, Sinisa; Basser, Peter J.

2017-01-01

Tensor-valued and matrix-valued measurements of different physical properties are increasingly available in material sciences and medical imaging applications. The eigenvalues and eigenvectors of such multivariate data provide novel and unique information, but at the cost of requiring a more complex statistical analysis. In this work we derive the distributions of eigenvalues and eigenvectors in the special but important case of m×m symmetric random matrices, D, observed with isotropic matrix-variate Gaussian noise. The properties of these distributions depend strongly on the symmetries of the mean tensor/matrix, D̄. When D̄ has repeated eigenvalues, the eigenvalues of D are not asymptotically Gaussian, and repulsion is observed between the eigenvalues corresponding to the same D̄ eigenspaces. We apply these results to diffusion tensor imaging (DTI), with m = 3, addressing an important problem of detecting the symmetries of the diffusion tensor, and seeking an experimental design that could potentially yield an isotropic Gaussian distribution. In the 3-dimensional case, when the mean tensor is spherically symmetric and the noise is Gaussian and isotropic, the asymptotic distribution of the first three eigenvalue central moment statistics is simple and can be used to test for isotropy. In order to apply such tests, we use quadrature rules of order t ≥ 4 with constant weights on the unit sphere to design a DTI-experiment with the property that isotropy of the underlying true tensor implies isotropy of the Fisher information. We also explain the potential implications of the methods using simulated DTI data with a Rician noise model. PMID:28989561

Full Waveform Inversion Using Student's t Distribution: a Numerical Study for Elastic Waveform Inversion and Simultaneous-Source Method

NASA Astrophysics Data System (ADS)

Jeong, Woodon; Kang, Minji; Kim, Shinwoong; Min, Dong-Joo; Kim, Won-Ki

2015-06-01

Seismic full waveform inversion (FWI) has primarily been based on a least-squares optimization problem for data residuals. However, the least-squares objective function can suffer from its weakness and sensitivity to noise. There have been numerous studies to enhance the robustness of FWI by using robust objective functions, such as l 1-norm-based objective functions. However, the l 1-norm can suffer from a singularity problem when the residual wavefield is very close to zero. Recently, Student's t distribution has been applied to acoustic FWI to give reasonable results for noisy data. Student's t distribution has an overdispersed density function compared with the normal distribution, and is thus useful for data with outliers. In this study, we investigate the feasibility of Student's t distribution for elastic FWI by comparing its basic properties with those of the l 2-norm and l 1-norm objective functions and by applying the three methods to noisy data. Our experiments show that the l 2-norm is sensitive to noise, whereas the l 1-norm and Student's t distribution objective functions give relatively stable and reasonable results for noisy data. When noise patterns are complicated, i.e., due to a combination of missing traces, unexpected outliers, and random noise, FWI based on Student's t distribution gives better results than l 1- and l 2-norm FWI. We also examine the application of simultaneous-source methods to acoustic FWI based on Student's t distribution. Computing the expectation of the coefficients of gradient and crosstalk noise terms and plotting the signal-to-noise ratio with iteration, we were able to confirm that crosstalk noise is suppressed as the iteration progresses, even when simultaneous-source FWI is combined with Student's t distribution. From our experiments, we conclude that FWI based on Student's t distribution can retrieve subsurface material properties with less distortion from noise than l 1- and l 2-norm FWI, and the simultaneous-source method can be adopted to improve the computational efficiency of FWI based on Student's t distribution.

Classification with asymmetric label noise: Consistency and maximal denoising

DOE PAGES

Blanchard, Gilles; Flaska, Marek; Handy, Gregory; ...

2016-09-20

In many real-world classification problems, the labels of training examples are randomly corrupted. Most previous theoretical work on classification with label noise assumes that the two classes are separable, that the label noise is independent of the true class label, or that the noise proportions for each class are known. In this work, we give conditions that are necessary and sufficient for the true class-conditional distributions to be identifiable. These conditions are weaker than those analyzed previously, and allow for the classes to be nonseparable and the noise levels to be asymmetric and unknown. The conditions essentially state that amore » majority of the observed labels are correct and that the true class-conditional distributions are “mutually irreducible,” a concept we introduce that limits the similarity of the two distributions. For any label noise problem, there is a unique pair of true class-conditional distributions satisfying the proposed conditions, and we argue that this pair corresponds in a certain sense to maximal denoising of the observed distributions. Our results are facilitated by a connection to “mixture proportion estimation,” which is the problem of estimating the maximal proportion of one distribution that is present in another. We establish a novel rate of convergence result for mixture proportion estimation, and apply this to obtain consistency of a discrimination rule based on surrogate loss minimization. Experimental results on benchmark data and a nuclear particle classification problem demonstrate the efficacy of our approach. MSC 2010 subject classifications: Primary 62H30; secondary 68T10. Keywords and phrases: Classification, label noise, mixture proportion estimation, surrogate loss, consistency.« less

Classification with asymmetric label noise: Consistency and maximal denoising

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blanchard, Gilles; Flaska, Marek; Handy, Gregory

In many real-world classification problems, the labels of training examples are randomly corrupted. Most previous theoretical work on classification with label noise assumes that the two classes are separable, that the label noise is independent of the true class label, or that the noise proportions for each class are known. In this work, we give conditions that are necessary and sufficient for the true class-conditional distributions to be identifiable. These conditions are weaker than those analyzed previously, and allow for the classes to be nonseparable and the noise levels to be asymmetric and unknown. The conditions essentially state that amore » majority of the observed labels are correct and that the true class-conditional distributions are “mutually irreducible,” a concept we introduce that limits the similarity of the two distributions. For any label noise problem, there is a unique pair of true class-conditional distributions satisfying the proposed conditions, and we argue that this pair corresponds in a certain sense to maximal denoising of the observed distributions. Our results are facilitated by a connection to “mixture proportion estimation,” which is the problem of estimating the maximal proportion of one distribution that is present in another. We establish a novel rate of convergence result for mixture proportion estimation, and apply this to obtain consistency of a discrimination rule based on surrogate loss minimization. Experimental results on benchmark data and a nuclear particle classification problem demonstrate the efficacy of our approach. MSC 2010 subject classifications: Primary 62H30; secondary 68T10. Keywords and phrases: Classification, label noise, mixture proportion estimation, surrogate loss, consistency.« less

Two competing species in super-diffusive dynamical regimes

NASA Astrophysics Data System (ADS)

La Cognata, A.; Valenti, D.; Spagnolo, B.; Dubkov, A. A.

2010-09-01

The dynamics of two competing species within the framework of the generalized Lotka-Volterra equations, in the presence of multiplicative α-stable Lévy noise sources and a random time dependent interaction parameter, is studied. The species dynamics is characterized by two different dynamical regimes, exclusion of one species and coexistence of both, depending on the values of the interaction parameter, which obeys a Langevin equation with a periodically fluctuating bistable potential and an additive α-stable Lévy noise. The stochastic resonance phenomenon is analyzed for noise sources asymmetrically distributed. Finally, the effects of statistical dependence between multiplicative noise and additive noise on the dynamics of the two species are studied.

Stochastic Models for Laser Propagation in Atmospheric Turbulence.

NASA Astrophysics Data System (ADS)

Leland, Robert Patton

In this dissertation, stochastic models for laser propagation in atmospheric turbulence are considered. A review of the existing literature on laser propagation in the atmosphere and white noise theory is presented, with a view toward relating the white noise integral and Ito integral approaches. The laser beam intensity is considered as the solution to a random Schroedinger equation, or forward scattering equation. This model is formulated in a Hilbert space context as an abstract bilinear system with a multiplicative white noise input, as in the literature. The model is also modeled in the Banach space of Fresnel class functions to allow the plane wave case and the application of path integrals. Approximate solutions to the Schroedinger equation of the Trotter-Kato product form are shown to converge for each white noise sample path. The product forms are shown to be physical random variables, allowing an Ito integral representation. The corresponding Ito integrals are shown to converge in mean square, providing a white noise basis for the Stratonovich correction term associated with this equation. Product form solutions for Ornstein -Uhlenbeck process inputs were shown to converge in mean square as the input bandwidth was expanded. A digital simulation of laser propagation in strong turbulence was used to study properties of the beam. Empirical distributions for the irradiance function were estimated from simulated data, and the log-normal and Rice-Nakagami distributions predicted by the classical perturbation methods were seen to be inadequate. A gamma distribution fit the simulated irradiance distribution well in the vicinity of the boresight. Statistics of the beam were seen to converge rapidly as the bandwidth of an Ornstein-Uhlenbeck process was expanded to its white noise limit. Individual trajectories of the beam were presented to illustrate the distortion and bending of the beam due to turbulence. Feynman path integrals were used to calculate an approximate expression for the mean of the beam intensity without using the Markov, or white noise, assumption, and to relate local variations in the turbulence field to the behavior of the beam by means of two approximations.

Nonlinear optical cryptosystem based on joint Fresnel transform correlator under vector wave illumination

NASA Astrophysics Data System (ADS)

Xueju, Shen; Chao, Lin; Xiao, Zou; Jianjun, Cai

2015-05-01

We present a nonlinear optical cryptosystem with multi-dimensional keys including phase, polarization and diffraction distance. To make full use of the degrees of freedom that optical processing offers, an elaborately designed vector wave with both a space-variant phase and locally linear polarization is generated with a common-path interferometer for illumination. The joint transform correlator in the Fresnel domain, implemented with a double optical wedge, is utilized as the encryption framework which provides an additional key known as the Fresnel diffraction distance. Two nonlinear operations imposed on the recorded joint Fresnel power distribution (JFPD) by a charge coupled device (CCD) are adopted. The first one is the division of power distribution of the reference window random function which is previously proposed by researchers and can improve the quality of the decrypted image. The second one is the recording of a hybrid JFPD using a micro-polarizers array with orthogonal and random transmissive axes attached to the CCD. Then the hybrid JFPD is further scrambled by substituting random noise for partial power distribution. The two nonlinear operations break the linearity of this cryptosystem and provide ultra security. We verify our proposal using a quick response code for noise-free recovery.

Explore Stochastic Instabilities of Periodic Points by Transition Path Theory

NASA Astrophysics Data System (ADS)

Cao, Yu; Lin, Ling; Zhou, Xiang

2016-06-01

We consider the noise-induced transitions from a linearly stable periodic orbit consisting of T periodic points in randomly perturbed discrete logistic map. Traditional large deviation theory and asymptotic analysis at small noise limit cannot distinguish the quantitative difference in noise-induced stochastic instabilities among the T periodic points. To attack this problem, we generalize the transition path theory to the discrete-time continuous-space stochastic process. In our first criterion to quantify the relative instability among T periodic points, we use the distribution of the last passage location related to the transitions from the whole periodic orbit to a prescribed disjoint set. This distribution is related to individual contributions to the transition rate from each periodic points. The second criterion is based on the competency of the transition paths associated with each periodic point. Both criteria utilize the reactive probability current in the transition path theory. Our numerical results for the logistic map reveal the transition mechanism of escaping from the stable periodic orbit and identify which periodic point is more prone to lose stability so as to make successful transitions under random perturbations.

Humpback whale-generated ambient noise levels provide insight into singers' spatial densities.

PubMed

Seger, Kerri D; Thode, Aaron M; Urbán-R, Jorge; Martínez-Loustalot, Pamela; Jiménez-López, M Esther; López-Arzate, Diana

2016-09-01

Baleen whale vocal activity can be the dominant underwater ambient noise source for certain locations and seasons. Previous wind-driven ambient-noise formulations have been adjusted to model ambient noise levels generated by random distributions of singing humpback whales in ocean waveguides and have been combined to a single model. This theoretical model predicts that changes in ambient noise levels with respect to fractional changes in singer population (defined as the noise "sensitivity") are relatively unaffected by the source level distributions and song spectra of individual humpback whales (Megaptera novaeangliae). However, the noise "sensitivity" does depend on frequency and on how the singers' spatial density changes with population size. The theoretical model was tested by comparing visual line transect surveys with bottom-mounted passive acoustic data collected during the 2013 and 2014 humpback whale breeding seasons off Los Cabos, Mexico. A generalized linear model (GLM) estimated the noise "sensitivity" across multiple frequency bands. Comparing the GLM estimates with the theoretical predictions suggests that humpback whales tend to maintain relatively constant spacing between one another while singing, but that individual singers either slightly increase their source levels or song duration, or cluster more tightly as the singing population increases.

Quantum key distribution using basis encoding of Gaussian-modulated coherent states

NASA Astrophysics Data System (ADS)

Huang, Peng; Huang, Jingzheng; Zhang, Zheshen; Zeng, Guihua

2018-04-01

The continuous-variable quantum key distribution (CVQKD) has been demonstrated to be available in practical secure quantum cryptography. However, its performance is restricted strongly by the channel excess noise and the reconciliation efficiency. In this paper, we present a quantum key distribution (QKD) protocol by encoding the secret keys on the random choices of two measurement bases: the conjugate quadratures X and P . The employed encoding method can dramatically weaken the effects of channel excess noise and reconciliation efficiency on the performance of the QKD protocol. Subsequently, the proposed scheme exhibits the capability to tolerate much higher excess noise and enables us to reach a much longer secure transmission distance even at lower reconciliation efficiency. The proposal can work alternatively to strengthen significantly the performance of the known Gaussian-modulated CVQKD protocol and serve as a multiplier for practical secure quantum cryptography with continuous variables.

Self-organisation of random oscillators with Lévy stable distributions

NASA Astrophysics Data System (ADS)

Moradi, Sara; Anderson, Johan

2017-08-01

A novel possibility of self-organized behaviour of stochastically driven oscillators is presented. It is shown that synchronization by Lévy stable processes is significantly more efficient than that by oscillators with Gaussian statistics. The impact of outlier events from the tail of the distribution function was examined by artificially introducing a few additional oscillators with very strong coupling strengths and it is found that remarkably even one such rare and extreme event may govern the long term behaviour of the coupled system. In addition to the multiplicative noise component, we have investigated the impact of an external additive Lévy distributed noise component on the synchronisation properties of the oscillators.

Noise distribution of an incubator with nebulizer at a neonatal intensive care unit in southern Taiwan.

PubMed

Chen, H F; Chang, Y J

2001-06-01

The purpose of this study was to investigate the noise distribution and sources of peak noise inside an incubator with a nebulizer at a neonatal intensive care unit of a medical center in Southern Taiwan. Sound levels were monitored continuously with an electronic sound-meter for 24 hours daily over a one-week period. Three working hours (day, evening, and night hours) in the weekday and weekend (total 48 hours) were selected randomly from the one-week period of noise survey to observe peak noise at levels > or = 65 dBA. Results revealed that 24.8% of the total monitoring period had sound levels at < or = 59 dBA, 58.9% at 60-64 dBA, 10.7% at 65-69 dBA, and 5.6% at > or = 70 dBA. Furthermore, a total of 947 peak noises > or = 65 dBA were found within the 48 hours, of which 61.5% were in a range of 65-69 dBA, 24% of 70-74 dBA, 9.8% of 75-79 dBA, and 4.8% > or = 80 dBA. Human-related sources, equaling 79%, were the dominant peak noises. These noises included opening and closing doors, banging the incubator hood, conversation among staff, nursing activity inside the incubator, tearing and opening paper or bags, opening and closing trash can lids, and bumping metal carts or other apparatus. Nonhuman-related sources were 21% including alarms of monitors and running of the incubator motor. Results of this study showed that the noise distribution in the incubator with nebulizer was far above a protective limitation of 58 dBA, suggested by the American Academy of Pediatrics in 1974. However, most peak noises could be reduced by modification of staff behavior. Therefore, determinations of noise distribution and sources of peak noise in this study are useful for further noise reduction programs.

True randomness from an incoherent source

NASA Astrophysics Data System (ADS)

Qi, Bing

2017-11-01

Quantum random number generators (QRNGs) harness the intrinsic randomness in measurement processes: the measurement outputs are truly random, given the input state is a superposition of the eigenstates of the measurement operators. In the case of trusted devices, true randomness could be generated from a mixed state ρ so long as the system entangled with ρ is well protected. We propose a random number generation scheme based on measuring the quadrature fluctuations of a single mode thermal state using an optical homodyne detector. By mixing the output of a broadband amplified spontaneous emission (ASE) source with a single mode local oscillator (LO) at a beam splitter and performing differential photo-detection, we can selectively detect the quadrature fluctuation of a single mode output of the ASE source, thanks to the filtering function of the LO. Experimentally, a quadrature variance about three orders of magnitude larger than the vacuum noise has been observed, suggesting this scheme can tolerate much higher detector noise in comparison with QRNGs based on measuring the vacuum noise. The high quality of this entropy source is evidenced by the small correlation coefficients of the acquired data. A Toeplitz-hashing extractor is applied to generate unbiased random bits from the Gaussian distributed raw data, achieving an efficiency of 5.12 bits per sample. The output of the Toeplitz extractor successfully passes all the NIST statistical tests for random numbers.

Angiogenic Signaling in Living Breast Tumor Models

DTIC Science & Technology

2007-06-01

Poisson distributed random noise is added in an amount relative to the desired signal to noise ratio. We fit the data using a regressive fitting...AD_________________ Award Number: W81XWH-05-1-0396 TITLE: Angiogenic Signaling in Living Breast...CONTRACT NUMBER Angiogenic Signaling in Living Breast Tumor Models 5b. GRANT NUMBER W81XWH-05-1-0396 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d

Detectability of auditory signals presented without defined observation intervals

NASA Technical Reports Server (NTRS)

Watson, C. S.; Nichols, T. L.

1976-01-01

Ability to detect tones in noise was measured without defined observation intervals. Latency density functions were estimated for the first response following a signal and, separately, for the first response following randomly distributed instances of background noise. Detection performance was measured by the maximum separation between the cumulative latency density functions for signal-plus-noise and for noise alone. Values of the index of detectability, estimated by this procedure, were approximately those obtained with a 2-dB weaker signal and defined observation intervals. Simulation of defined- and non-defined-interval tasks with an energy detector showed that this device performs very similarly to the human listener in both cases.

Heat currents in electronic junctions driven by telegraph noise

NASA Astrophysics Data System (ADS)

Entin-Wohlman, O.; Chowdhury, D.; Aharony, A.; Dattagupta, S.

2017-11-01

The energy and charge fluxes carried by electrons in a two-terminal junction subjected to a random telegraph noise, produced by a single electronic defect, are analyzed. The telegraph processes are imitated by the action of a stochastic electric field that acts on the electrons in the junction. Upon averaging over all random events of the telegraph process, it is found that this electric field supplies, on the average, energy to the electronic reservoirs, which is distributed unequally between them: the stronger is the coupling of the reservoir with the junction, the more energy it gains. Thus the noisy environment can lead to a temperature gradient across an unbiased junction.

On the role of the radiation directivity in noise reduction for STOL aircraft.

NASA Technical Reports Server (NTRS)

Gruschka, H. D.

1972-01-01

The radiation characteristics of distributed randomly fluctuating acoustic sources when shielded by finite surfaces are discussed briefly. A number of model tests using loudspeakers as artificial noise sources with a given broadband power density spectrum are used to demonstrate the effectiveness of reducing the radiated noise intensity in certain directions due to shielding. In the lateral direction of the source array noise reductions of 12 dB are observed with relatively small shields. The same shields reduce the backward radiation by approximately 20 dB. With the results obtained in these acoustic model tests the potentials of jet noise reduction of jet flap propulsion systems applicable in future STOL aircraft are discussed. The jet flap configuration as a complex aerodynamic noise source is described briefly.

On Acoustic Source Specification for Rotor-Stator Interaction Noise Prediction

NASA Technical Reports Server (NTRS)

Nark, Douglas M.; Envia, Edmane; Burley, Caesy L.

2010-01-01

This paper describes the use of measured source data to assess the effects of acoustic source specification on rotor-stator interaction noise predictions. Specifically, the acoustic propagation and radiation portions of a recently developed coupled computational approach are used to predict tonal rotor-stator interaction noise from a benchmark configuration. In addition to the use of full measured data, randomization of source mode relative phases is also considered for specification of the acoustic source within the computational approach. Comparisons with sideline noise measurements are performed to investigate the effects of various source descriptions on both inlet and exhaust predictions. The inclusion of additional modal source content is shown to have a much greater influence on the inlet results. Reasonable agreement between predicted and measured levels is achieved for the inlet, as well as the exhaust when shear layer effects are taken into account. For the number of trials considered, phase randomized predictions follow statistical distributions similar to those found in previous statistical source investigations. The shape of the predicted directivity pattern relative to measurements also improved with phase randomization, having predicted levels generally within one standard deviation of the measured levels.

Eigenvalue distributions for a class of covariance matrices with application to Bienenstock-Cooper-Munro neurons under noisy conditions.

PubMed

Bazzani, Armando; Castellani, Gastone C; Cooper, Leon N

2010-05-01

We analyze the effects of noise correlations in the input to, or among, Bienenstock-Cooper-Munro neurons using the Wigner semicircular law to construct random, positive-definite symmetric correlation matrices and compute their eigenvalue distributions. In the finite dimensional case, we compare our analytic results with numerical simulations and show the effects of correlations on the lifetimes of synaptic strengths in various visual environments. These correlations can be due either to correlations in the noise from the input lateral geniculate nucleus neurons, or correlations in the variability of lateral connections in a network of neurons. In particular, we find that for fixed dimensionality, a large noise variance can give rise to long lifetimes of synaptic strengths. This may be of physiological significance.

The auditory P50 component to onset and offset of sound

PubMed Central

Pratt, Hillel; Starr, Arnold; Michalewski, Henry J.; Bleich, Naomi; Mittelman, Nomi

2008-01-01

Objective: The auditory Event-Related Potentials (ERP) component P50 to sound onset and offset have been reported to be similar, but their magnetic homologue has been reported absent to sound offset. We compared the spatio-temporal distribution of cortical activity during P50 to sound onset and offset, without confounds of spectral change. Methods: ERPs were recorded in response to onsets and offsets of silent intervals of 0.5 s (gaps) appearing randomly in otherwise continuous white noise and compared to ERPs to randomly distributed click pairs with half second separation presented in silence. Subjects were awake and distracted from the stimuli by reading a complicated text. Measures of P50 included peak latency and amplitude, as well as source current density estimates to the clicks and sound onsets and offsets. Results P50 occurred in response to noise onsets and to clicks, while to noise offset it was absent. Latency of P50 was similar to noise onset (56 msec) and to clicks (53 msec). Sources of P50 to noise onsets and clicks included bilateral superior parietal areas. In contrast, noise offsets activated left inferior temporal and occipital areas at the time of P50. Source current density was significantly higher to noise onset than offset in the vicinity of the temporo-parietal junction. Conclusions: P50 to sound offset is absent compared to the distinct P50 to sound onset and to clicks, at different intracranial sources. P50 to stimulus onset and to clicks appears to reflect preattentive arousal by a new sound in the scene. Sound offset does not involve a new sound and hence the absent P50. Significance: Stimulus onset activates distinct early cortical processes that are absent to offset. PMID:18055255

Multi-Aperture-Based Probabilistic Noise Reduction of Random Telegraph Signal Noise and Photon Shot Noise in Semi-Photon-Counting Complementary-Metal-Oxide-Semiconductor Image Sensor

PubMed Central

Ishida, Haruki; Kagawa, Keiichiro; Komuro, Takashi; Zhang, Bo; Seo, Min-Woong; Takasawa, Taishi; Yasutomi, Keita; Kawahito, Shoji

2018-01-01

A probabilistic method to remove the random telegraph signal (RTS) noise and to increase the signal level is proposed, and was verified by simulation based on measured real sensor noise. Although semi-photon-counting-level (SPCL) ultra-low noise complementary-metal-oxide-semiconductor (CMOS) image sensors (CISs) with high conversion gain pixels have emerged, they still suffer from huge RTS noise, which is inherent to the CISs. The proposed method utilizes a multi-aperture (MA) camera that is composed of multiple sets of an SPCL CIS and a moderately fast and compact imaging lens to emulate a very fast single lens. Due to the redundancy of the MA camera, the RTS noise is removed by the maximum likelihood estimation where noise characteristics are modeled by the probability density distribution. In the proposed method, the photon shot noise is also relatively reduced because of the averaging effect, where the pixel values of all the multiple apertures are considered. An extremely low-light condition that the maximum number of electrons per aperture was the only 2e− was simulated. PSNRs of a test image for simple averaging, selective averaging (our previous method), and the proposed method were 11.92 dB, 11.61 dB, and 13.14 dB, respectively. The selective averaging, which can remove RTS noise, was worse than the simple averaging because it ignores the pixels with RTS noise and photon shot noise was less improved. The simulation results showed that the proposed method provided the best noise reduction performance. PMID:29587424

Polarized ensembles of random pure states

NASA Astrophysics Data System (ADS)

Deelan Cunden, Fabio; Facchi, Paolo; Florio, Giuseppe

2013-08-01

A new family of polarized ensembles of random pure states is presented. These ensembles are obtained by linear superposition of two random pure states with suitable distributions, and are quite manageable. We will use the obtained results for two purposes: on the one hand we will be able to derive an efficient strategy for sampling states from isopurity manifolds. On the other, we will characterize the deviation of a pure quantum state from separability under the influence of noise.

Single-mode SOA-based 1kHz-linewidth dual-wavelength random fiber laser.

PubMed

Xu, Yanping; Zhang, Liang; Chen, Liang; Bao, Xiaoyi

2017-07-10

Narrow-linewidth multi-wavelength fiber lasers are of significant interests for fiber-optic sensors, spectroscopy, optical communications, and microwave generation. A novel narrow-linewidth dual-wavelength random fiber laser with single-mode operation, based on the semiconductor optical amplifier (SOA) gain, is achieved in this work for the first time, to the best of our knowledge. A simplified theoretical model is established to characterize such kind of random fiber laser. The inhomogeneous gain in SOA mitigates the mode competition significantly and alleviates the laser instability, which are frequently encountered in multi-wavelength fiber lasers with Erbium-doped fiber gain. The enhanced random distributed feedback from a 5km non-uniform fiber provides coherent feedback, acting as mode selection element to ensure single-mode operation with narrow linewidth of ~1kHz. The laser noises are also comprehensively investigated and studied, showing the improvements of the proposed random fiber laser with suppressed intensity and frequency noises.

Advanced Water Vapor Lidar Detection System

NASA Technical Reports Server (NTRS)

Elsayed-Ali, Hani

1998-01-01

In the present water vapor lidar system, the detected signal is sent over long cables to a waveform digitizer in a CAMAC crate. This has the disadvantage of transmitting analog signals for a relatively long distance, which is subjected to pickup noise, leading to a decrease in the signal to noise ratio. Generally, errors in the measurement of water vapor with the DIAL method arise from both random and systematic sources. Systematic errors in DIAL measurements are caused by both atmospheric and instrumentation effects. The selection of the on-line alexandrite laser with a narrow linewidth, suitable intensity and high spectral purity, and its operation at the center of the water vapor lines, ensures minimum influence in the DIAL measurement that are caused by the laser spectral distribution and avoid system overloads. Random errors are caused by noise in the detected signal. Variability of the photon statistics in the lidar return signal, noise resulting from detector dark current, and noise in the background signal are the main sources of random error. This type of error can be minimized by maximizing the signal to noise ratio. The increase in the signal to noise ratio can be achieved by several ways. One way is to increase the laser pulse energy, by increasing its amplitude or the pulse repetition rate. Another way, is to use a detector system with higher quantum efficiency and lower noise, on the other hand, the selection of a narrow band optical filter that rejects most of the day background light and retains high optical efficiency is an important issue. Following acquisition of the lidar data, we minimize random errors in the DIAL measurement by averaging the data, but this will result in the reduction of the vertical and horizontal resolutions. Thus, a trade off is necessary to achieve a balance between the spatial resolution and the measurement precision. Therefore, the main goal of this research effort is to increase the signal to noise ratio by a factor of 10 over the current system, using a newly evaluated, very low noise avalanche photo diode detector and constructing a 10 MHz waveform digitizer which will replace the current CAMAC system.

Continuous variable quantum cryptography using coherent states.

PubMed

Grosshans, Frédéric; Grangier, Philippe

2002-02-04

We propose several methods for quantum key distribution (QKD) based on the generation and transmission of random distributions of coherent or squeezed states, and we show that they are secure against individual eavesdropping attacks. These protocols require that the transmission of the optical line between Alice and Bob is larger than 50%, but they do not rely on "sub-shot-noise" features such as squeezing. Their security is a direct consequence of the no-cloning theorem, which limits the signal-to-noise ratio of possible quantum measurements on the transmission line. Our approach can also be used for evaluating various QKD protocols using light with Gaussian statistics.

Joint min-max distribution and Edwards-Anderson's order parameter of the circular 1/f-noise model

NASA Astrophysics Data System (ADS)

Cao, Xiangyu; Le Doussal, Pierre

2016-05-01

We calculate the joint min-max distribution and the Edwards-Anderson's order parameter for the circular model of 1/f-noise. Both quantities, as well as generalisations, are obtained exactly by combining the freezing-duality conjecture and Jack-polynomial techniques. Numerical checks come with significantly improved control of finite-size effects in the glassy phase, and the results convincingly validate the freezing-duality conjecture. Application to diffusive dynamics is discussed. We also provide a formula for the pre-factor ratio of the joint/marginal Carpentier-Le Doussal tail for minimum/maximum which applies to any logarithmic random energy model.

The topology of large-scale structure. I - Topology and the random phase hypothesis. [galactic formation models

NASA Technical Reports Server (NTRS)

Weinberg, David H.; Gott, J. Richard, III; Melott, Adrian L.

1987-01-01

Many models for the formation of galaxies and large-scale structure assume a spectrum of random phase (Gaussian), small-amplitude density fluctuations as initial conditions. In such scenarios, the topology of the galaxy distribution on large scales relates directly to the topology of the initial density fluctuations. Here a quantitative measure of topology - the genus of contours in a smoothed density distribution - is described and applied to numerical simulations of galaxy clustering, to a variety of three-dimensional toy models, and to a volume-limited sample of the CfA redshift survey. For random phase distributions the genus of density contours exhibits a universal dependence on threshold density. The clustering simulations show that a smoothing length of 2-3 times the mass correlation length is sufficient to recover the topology of the initial fluctuations from the evolved galaxy distribution. Cold dark matter and white noise models retain a random phase topology at shorter smoothing lengths, but massive neutrino models develop a cellular topology.

Image quality enhancement in low-light-level ghost imaging using modified compressive sensing method

NASA Astrophysics Data System (ADS)

Shi, Xiaohui; Huang, Xianwei; Nan, Suqin; Li, Hengxing; Bai, Yanfeng; Fu, Xiquan

2018-04-01

Detector noise has a significantly negative impact on ghost imaging at low light levels, especially for existing recovery algorithm. Based on the characteristics of the additive detector noise, a method named modified compressive sensing ghost imaging is proposed to reduce the background imposed by the randomly distributed detector noise at signal path. Experimental results show that, with an appropriate choice of threshold value, modified compressive sensing ghost imaging algorithm can dramatically enhance the contrast-to-noise ratio of the object reconstruction significantly compared with traditional ghost imaging and compressive sensing ghost imaging methods. The relationship between the contrast-to-noise ratio of the reconstruction image and the intensity ratio (namely, the average signal intensity to average noise intensity ratio) for the three reconstruction algorithms are also discussed. This noise suppression imaging technique will have great applications in remote-sensing and security areas.

Noise-induced effects in population dynamics

NASA Astrophysics Data System (ADS)

Spagnolo, Bernardo; Cirone, Markus; La Barbera, Antonino; de Pasquale, Ferdinando

2002-03-01

We investigate the role of noise in the nonlinear relaxation of two ecosystems described by generalized Lotka-Volterra equations in the presence of multiplicative noise. Specifically we study two cases: (i) an ecosystem with two interacting species in the presence of periodic driving; (ii) an ecosystem with a great number of interacting species with random interaction matrix. We analyse the interplay between noise and periodic modulation for case (i) and the role of the noise in the transient dynamics of the ecosystem in the presence of an absorbing barrier in case (ii). We find that the presence of noise is responsible for the generation of temporal oscillations and for the appearance of spatial patterns in the first case. In the other case we obtain the asymptotic behaviour of the time average of the ith population and discuss the effect of the noise on the probability distributions of the population and of the local field.

Ensembles of Spiking Neurons with Noise Support Optimal Probabilistic Inference in a Dynamically Changing Environment

PubMed Central

Legenstein, Robert; Maass, Wolfgang

2014-01-01

It has recently been shown that networks of spiking neurons with noise can emulate simple forms of probabilistic inference through “neural sampling”, i.e., by treating spikes as samples from a probability distribution of network states that is encoded in the network. Deficiencies of the existing model are its reliance on single neurons for sampling from each random variable, and the resulting limitation in representing quickly varying probabilistic information. We show that both deficiencies can be overcome by moving to a biologically more realistic encoding of each salient random variable through the stochastic firing activity of an ensemble of neurons. The resulting model demonstrates that networks of spiking neurons with noise can easily track and carry out basic computational operations on rapidly varying probability distributions, such as the odds of getting rewarded for a specific behavior. We demonstrate the viability of this new approach towards neural coding and computation, which makes use of the inherent parallelism of generic neural circuits, by showing that this model can explain experimentally observed firing activity of cortical neurons for a variety of tasks that require rapid temporal integration of sensory information. PMID:25340749

A compound scattering pdf for the ultrasonic echo envelope and its relationship to K and Nakagami distributions.

PubMed

Shankar, P Mohana

2003-03-01

A compound probability density function (pdf) is presented to describe the envelope of the backscattered echo from tissue. This pdf allows local and global variation in scattering cross sections in tissue. The ultrasonic backscattering cross sections are assumed to be gamma distributed. The gamma distribution also is used to model the randomness in the average cross sections. This gamma-gamma model results in the compound scattering pdf for the envelope. The relationship of this compound pdf to the Rayleigh, K, and Nakagami distributions is explored through an analysis of the signal-to-noise ratio of the envelopes and random number simulations. The three parameter compound pdf appears to be flexible enough to represent envelope statistics giving rise to Rayleigh, K, and Nakagami distributions.

Image discrimination models predict detection in fixed but not random noise

NASA Technical Reports Server (NTRS)

Ahumada, A. J. Jr; Beard, B. L.; Watson, A. B. (Principal Investigator)

1997-01-01

By means of a two-interval forced-choice procedure, contrast detection thresholds for an aircraft positioned on a simulated airport runway scene were measured with fixed and random white-noise masks. The term fixed noise refers to a constant, or unchanging, noise pattern for each stimulus presentation. The random noise was either the same or different in the two intervals. Contrary to simple image discrimination model predictions, the same random noise condition produced greater masking than the fixed noise. This suggests that observers seem unable to hold a new noisy image for comparison. Also, performance appeared limited by internal process variability rather than by external noise variability, since similar masking was obtained for both random noise types.

An iteratively reweighted least-squares approach to adaptive robust adjustment of parameters in linear regression models with autoregressive and t-distributed deviations

NASA Astrophysics Data System (ADS)

Kargoll, Boris; Omidalizarandi, Mohammad; Loth, Ina; Paffenholz, Jens-André; Alkhatib, Hamza

2018-03-01

In this paper, we investigate a linear regression time series model of possibly outlier-afflicted observations and autocorrelated random deviations. This colored noise is represented by a covariance-stationary autoregressive (AR) process, in which the independent error components follow a scaled (Student's) t-distribution. This error model allows for the stochastic modeling of multiple outliers and for an adaptive robust maximum likelihood (ML) estimation of the unknown regression and AR coefficients, the scale parameter, and the degree of freedom of the t-distribution. This approach is meant to be an extension of known estimators, which tend to focus only on the regression model, or on the AR error model, or on normally distributed errors. For the purpose of ML estimation, we derive an expectation conditional maximization either algorithm, which leads to an easy-to-implement version of iteratively reweighted least squares. The estimation performance of the algorithm is evaluated via Monte Carlo simulations for a Fourier as well as a spline model in connection with AR colored noise models of different orders and with three different sampling distributions generating the white noise components. We apply the algorithm to a vibration dataset recorded by a high-accuracy, single-axis accelerometer, focusing on the evaluation of the estimated AR colored noise model.

Prescription-induced jump distributions in multiplicative Poisson processes.

PubMed

Suweis, Samir; Porporato, Amilcare; Rinaldo, Andrea; Maritan, Amos

2011-06-01

Generalized Langevin equations (GLE) with multiplicative white Poisson noise pose the usual prescription dilemma leading to different evolution equations (master equations) for the probability distribution. Contrary to the case of multiplicative Gaussian white noise, the Stratonovich prescription does not correspond to the well-known midpoint (or any other intermediate) prescription. By introducing an inertial term in the GLE, we show that the Itô and Stratonovich prescriptions naturally arise depending on two time scales, one induced by the inertial term and the other determined by the jump event. We also show that, when the multiplicative noise is linear in the random variable, one prescription can be made equivalent to the other by a suitable transformation in the jump probability distribution. We apply these results to a recently proposed stochastic model describing the dynamics of primary soil salinization, in which the salt mass balance within the soil root zone requires the analysis of different prescriptions arising from the resulting stochastic differential equation forced by multiplicative white Poisson noise, the features of which are tailored to the characters of the daily precipitation. A method is finally suggested to infer the most appropriate prescription from the data.

Prescription-induced jump distributions in multiplicative Poisson processes

NASA Astrophysics Data System (ADS)

Suweis, Samir; Porporato, Amilcare; Rinaldo, Andrea; Maritan, Amos

2011-06-01

Generalized Langevin equations (GLE) with multiplicative white Poisson noise pose the usual prescription dilemma leading to different evolution equations (master equations) for the probability distribution. Contrary to the case of multiplicative Gaussian white noise, the Stratonovich prescription does not correspond to the well-known midpoint (or any other intermediate) prescription. By introducing an inertial term in the GLE, we show that the Itô and Stratonovich prescriptions naturally arise depending on two time scales, one induced by the inertial term and the other determined by the jump event. We also show that, when the multiplicative noise is linear in the random variable, one prescription can be made equivalent to the other by a suitable transformation in the jump probability distribution. We apply these results to a recently proposed stochastic model describing the dynamics of primary soil salinization, in which the salt mass balance within the soil root zone requires the analysis of different prescriptions arising from the resulting stochastic differential equation forced by multiplicative white Poisson noise, the features of which are tailored to the characters of the daily precipitation. A method is finally suggested to infer the most appropriate prescription from the data.

White Gaussian Noise - Models for Engineers

NASA Astrophysics Data System (ADS)

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.

Precision and Accuracy in PDV and VISAR

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ambrose, W. P.

2017-08-22

This is a technical report discussing our current level of understanding of a wide and varying distribution of uncertainties in velocity results from Photonic Doppler Velocimetry in its application to gas gun experiments. Using propagation of errors methods with statistical averaging of photon number fluctuation in the detected photocurrent and subsequent addition of electronic recording noise, we learn that the velocity uncertainty in VISAR can be written in closed form. For PDV, the non-linear frequency transform and peak fitting methods employed make propagation of errors estimates notoriously more difficult to write down in closed form expect in the limit ofmore » constant velocity and low time resolution (large analysis-window width). An alternative method of error propagation in PDV is to use Monte Carlo methods with a simulation of the time domain signal based on results from the spectral domain. A key problem for Monte Carlo estimation for an experiment is a correct estimate of that portion of the time-domain noise associated with the peak-fitting region-of-interesting in the spectral domain. Using short-time Fourier transformation spectral analysis and working with the phase dependent real and imaginary parts allows removal of amplitude-noise cross terms that invariably show up when working with correlation-based methods or FFT power spectra. Estimation of the noise associated with a given spectral region of interest is then possible. At this level of progress, we learn that Monte Carlo trials with random recording noise and initial (uncontrolled) phase yields velocity uncertainties that are not as large as those observed. In a search for additional noise sources, a speckleinterference modulation contribution with off axis rays was investigated, and was found to add a velocity variation beyond that from the recording noise (due to random interference between off axis rays), but in our experiments the speckle modulation precision was not as important as the recording noise precision. But from these investigations we do appreciate that the velocity-uncertainty itself has a wide distribution of values that varies with signal-amplitude modulation (is not a single value). To provide a rough rule of thumb for the velocity uncertainty, we computed the average of the relative standard deviation distributions from 60 recorded traces (with distributions of uncertainties roughly between 0.1 % to 1 % in each trace) and found a mean of the distribution of uncertainties for our experiments is not better than 0.4 % at an analysis window width of 5 ns (although for brief intervals it can be as good as 0.1 %). Further imagination and testing may be needed to reveal other possible hydrodynamics-related sources of velocity error in PDV.« less

Small-scale seismic inversion using surface waves extracted from noise cross correlation.

PubMed

Gouédard, Pierre; Roux, Philippe; Campillo, Michel

2008-03-01

Green's functions can be retrieved between receivers from the correlation of ambient seismic noise or with an appropriate set of randomly distributed sources. This principle is demonstrated in small-scale geophysics using noise sources generated by human steps during a 10-min walk in the alignment of a 14-m-long accelerometer line array. The time-domain correlation of the records yields two surface wave modes extracted from the Green's function between each pair of accelerometers. A frequency-wave-number Fourier analysis yields each mode contribution and their dispersion curve. These dispersion curves are then inverted to provide the one-dimensional shear velocity of the near surface.

Mixed-mode oscillations and interspike interval statistics in the stochastic FitzHugh-Nagumo model

NASA Astrophysics Data System (ADS)

Berglund, Nils; Landon, Damien

2012-08-01

We study the stochastic FitzHugh-Nagumo equations, modelling the dynamics of neuronal action potentials in parameter regimes characterized by mixed-mode oscillations. The interspike time interval is related to the random number of small-amplitude oscillations separating consecutive spikes. We prove that this number has an asymptotically geometric distribution, whose parameter is related to the principal eigenvalue of a substochastic Markov chain. We provide rigorous bounds on this eigenvalue in the small-noise regime and derive an approximation of its dependence on the system's parameters for a large range of noise intensities. This yields a precise description of the probability distribution of observed mixed-mode patterns and interspike intervals.

Accurate estimation of camera shot noise in the real-time

NASA Astrophysics Data System (ADS)

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 accuracy of the obtained temporal noise values was estimated.

New version of PLNoise: a package for exact numerical simulation of power-law noises

NASA Astrophysics Data System (ADS)

Milotti, Edoardo

2007-08-01

In a recent paper I have introduced a package for the exact simulation of power-law noises and other colored noises [E. Milotti, Comput. Phys. Comm. 175 (2006) 212]: in particular, the algorithm generates 1/f noises with 0<α⩽2. Here I extend the algorithm to generate 1/f noises with 2<α⩽4 (black noises). The method is exact in the sense that it produces a sampled process with a theoretically guaranteed range-limited power-law spectrum for any arbitrary sequence of sampling intervals, i.e. the sampling times may be unevenly spaced. Program summaryTitle of program: PLNoise Catalogue identifier:ADXV_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXV_v2_0.html Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Programming language used: ANSI C Computer: Any computer with an ANSI C compiler: the package has been tested with gcc version 3.2.3 on Red Hat Linux 3.2.3-52 and gcc version 4.0.0 and 4.0.1 on Apple Mac OS X-10.4 Operating system: All operating systems capable of running an ANSI C compiler RAM: The code of the test program is very compact (about 60 Kbytes), but the program works with list management and allocates memory dynamically; in a typical run with average list length 2ṡ10, the RAM taken by the list is 200 Kbytes External routines: The package needs external routines to generate uniform and exponential deviates. The implementation described here uses the random number generation library ranlib freely available from Netlib [B.W. Brown, J. Lovato, K. Russell: ranlib, available from Netlib, http://www.netlib.org/random/index.html, select the C version ranlib.c], but it has also been successfully tested with the random number routines in Numerical Recipes [W.H. Press, S.A. Teulkolsky, W.T. Vetterling, B.P. Flannery, Numerical Recipes in C: The Art of Scientific Computing, second ed., Cambridge Univ. Press., Cambridge, 1992, pp. 274-290]. Notice that ranlib requires a pair of routines from the linear algebra package LINPACK, and that the distribution of ranlib includes the C source of these routines, in case LINPACK is not installed on the target machine. No. of lines in distributed program, including test data, etc.:2975 No. of bytes in distributed program, including test data, etc.:194 588 Distribution format:tar.gz Catalogue identifier of previous version: ADXV_v1_0 Journal reference of previous version: Comput. Phys. Comm. 175 (2006) 212 Does the new version supersede the previous version?: Yes Nature of problem: Exact generation of different types of colored noise. Solution method: Random superposition of relaxation processes [E. Milotti, Phys. Rev. E 72 (2005) 056701], possibly followed by an integration step to produce noise with spectral index >2. Reasons for the new version: Extension to 1/f noises with spectral index 2<α⩽4: the new version generates both noises with spectral with spectral index 0<α⩽2 and with 2<α⩽4. Summary of revisions: Although the overall structure remains the same, one routine has been added and several changes have been made throughout the code to include the new integration step. Unusual features: The algorithm is theoretically guaranteed to be exact, and unlike all other existing generators it can generate samples with uneven spacing. Additional comments: The program requires an initialization step; for some parameter sets this may become rather heavy. Running time: Running time varies widely with different input parameters, however in a test run like the one in Section 3 in the long write-up, the generation routine took on average about 75 μs for each sample.

Pruning a minimum spanning tree

NASA Astrophysics Data System (ADS)

Sandoval, Leonidas

2012-04-01

This work employs various techniques in order to filter random noise from the information provided by minimum spanning trees obtained from the correlation matrices of international stock market indices prior to and during times of crisis. The first technique establishes a threshold above which connections are considered affected by noise, based on the study of random networks with the same probability density distribution of the original data. The second technique is to judge the strength of a connection by its survival rate, which is the amount of time a connection between two stock market indices endures. The idea is that true connections will survive for longer periods of time, and that random connections will not. That information is then combined with the information obtained from the first technique in order to create a smaller network, in which most of the connections are either strong or enduring in time.

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

PubMed Central

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

2015-01-01

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

Universal noise and Efimov physics

NASA Astrophysics Data System (ADS)

Nicholson, Amy N.

2016-03-01

Probability distributions for correlation functions of particles interacting via random-valued fields are discussed as a novel tool for determining the spectrum of a theory. In particular, this method is used to determine the energies of universal N-body clusters tied to Efimov trimers, for even N, by investigating the distribution of a correlation function of two particles at unitarity. Using numerical evidence that this distribution is log-normal, an analytical prediction for the N-dependence of the N-body binding energies is made.

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

NASA Astrophysics Data System (ADS)

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.

Parametric Power Spectral Density Analysis of Noise from Instrumentation in MALDI TOF Mass Spectrometry

PubMed Central

Shin, Hyunjin; Mutlu, Miray; Koomen, John M.; Markey, Mia K.

2007-01-01

Noise in mass spectrometry can interfere with identification of the biochemical substances in the sample. For example, the electric motors and circuits inside the mass spectrometer or in nearby equipment generate random noise that may distort the true shape of mass spectra. This paper presents a stochastic signal processing approach to analyzing noise from electrical noise sources (i.e., noise from instrumentation) in MALDI TOF mass spectrometry. Noise from instrumentation was hypothesized to be a mixture of thermal noise, 1/f noise, and electric or magnetic interference in the instrument. Parametric power spectral density estimation was conducted to derive the power distribution of noise from instrumentation with respect to frequencies. As expected, the experimental results show that noise from instrumentation contains 1/f noise and prominent periodic components in addition to thermal noise. These periodic components imply that the mass spectrometers used in this study may not be completely shielded from the internal or external electrical noise sources. However, according to a simulation study of human plasma mass spectra, noise from instrumentation does not seem to affect mass spectra significantly. In conclusion, analysis of noise from instrumentation using stochastic signal processing here provides an intuitive perspective on how to quantify noise in mass spectrometry through spectral modeling. PMID:19455245

Investigation of Noises in GPS Time Series: Case Study on Epn Weekly Solutions

NASA Astrophysics Data System (ADS)

Klos, Anna; Bogusz, Janusz; Figurski, Mariusz; Kosek, Wieslaw; Gruszczynski, Maciej

2014-05-01

The noises in GPS time series are stated to be described the best by the combination of white (Gaussian) and power-law processes. They are mainly the effect of mismodelled satellite orbits, Earth orientation parameters, atmospheric effects, antennae phase centre effects, or of monument instability. Due to the fact, that velocities of permanent stations define the kinematic reference frame, they have to fulfil the requirement of being stable at 0.1 mm/yr. The previously performed researches showed, that the wrong assumption of noise model leads to the underestimation of velocities and their uncertainties from 2 up to even 11, especially in the Up direction. This presentation focuses on more than 200 EPN (EUREF Permanent Network) stations from the area of Europe with various monument types (concrete pillars, buildings, metal masts, with or without domes, placed on the ground or on the rock) and coordinates of weekly changes (GPS weeks 0834-1459). The topocentric components (North, East, Up) in ITRF2005 which come from the EPN Re-Processing made by the Military University of Technology Local Analysis Centre (MUT LAC) were processed with Maximum Likelihood Estimation (MLE) using CATS software. We have assumed the existence of few combinations of noise models (these are: white, flicker and random walk noise with integer spectral indices and power-law noise models with fractional spectral indices) and investigated which of them EPN weekly time series are likely to follow. The results show, that noises in GPS time series are described the best by the combination of white and flicker noise model. It is strictly related to the so-called common mode error (CME) that is spatially correlated error being one of the dominant error source in GPS solutions. We have assumed CME as spatially uniform, what was a good approximation for stations located hundreds of kilometres one to another. Its removal with spatial filtering reduces the amplitudes of white and flicker noise by a factor of 2 or 3. The assumption of white plus flicker plus random-walk noise (which is considered to be the effect of badly monumented stations) resulted in the random-walk amplitudes at the level of single millimetres for some of the stations, while for the majority of them no random-walk was detected, due to the fact that flicker noise prevails in GPS time series. The removal of CME caused the decrease in flicker noise amplitudes leading at the same time to greater random-walk amplitudes. The assumed combination of white plus power-law noise showed that the spectral indices for the best fitted noise model are unevenly distributed around -1 what also indicates the flicker noise existence in EPN weekly time series. The poster will present all of the assumed noise model combinations with the comparison of noise amplitudes before and after spatial filtering. Additionally, we will discuss over the latitude and longitude noise dependencies for the area of Europe to indicate any similarities between noise amplitudes and the location of stations. Finally, we will focus on the velocities with their uncertainties that were determined from EPN weekly solutions and show how the wrong assumption of noise model changes both of them.

Randomized Hough transform filter for echo extraction in DLR

NASA Astrophysics Data System (ADS)

Liu, Tong; Chen, Hao; Shen, Ming; Gao, Pengqi; Zhao, You

2016-11-01

The signal-to-noise ratio (SNR) of debris laser ranging (DLR) data is extremely low, and the valid returns in the DLR range residuals are distributed on a curve in a long observation time. Therefore, it is hard to extract the signals from noise in the Observed-minus-Calculated (O-C) residuals with low SNR. In order to autonomously extract the valid returns, we propose a new algorithm based on randomized Hough transform (RHT). We firstly pre-process the data using histogram method to find the zonal area that contains all the possible signals to reduce large amount of noise. Then the data is processed with RHT algorithm to find the curve that the signal points are distributed on. A new parameter update strategy is introduced in the RHT to get the best parameters. We also analyze the values of the parameters in the algorithm. We test our algorithm on the 10 Hz repetition rate DLR data from Yunnan Observatory and 100 Hz repetition rate DLR data from Graz SLR station. For 10 Hz DLR data with relative larger and similar range gate, we can process it in real time and extract all the signals autonomously with a few false readings. For 100 Hz DLR data with longer observation time, we autonomously post-process DLR data of 0.9%, 2.7%, 8% and 33% return rate with high reliability. The extracted points contain almost all signals and a low percentage of noise. Additional noise is added to 10 Hz DLR data to get lower return rate data. The valid returns can also be well extracted for DLR data with 0.18% and 0.1% return rate.

Instantaneous phase estimation to measure weak velocity variations: application to noise correlation on seismic data at the exploration scale

NASA Astrophysics Data System (ADS)

Corciulo, M.; Roux, P.; Campillo, M.; Dubucq, D.

2010-12-01

Passive imaging from noise cross-correlation is a consolidated analysis applied at continental and regional scale whereas its use at local scale for seismic exploration purposes is still uncertain. The development of passive imaging by cross-correlation analysis is based on the extraction of the Green’s function from seismic noise data. In a completely random field in time and space, the cross-correlation permits to retrieve the complete Green’s function whatever the complexity of the medium. At the exploration scale and at frequency above 2 Hz, the noise sources are not ideally distributed around the stations which strongly affect the extraction of the direct arrivals from the noise cross-correlation process. In order to overcome this problem, the coda waves extracted from noise correlation could be useful. Coda waves describe long and scattered paths sampling the medium in different ways such that they become sensitive to weak velocity variations without being dependent on the noise source distribution. Indeed, scatters in the medium behave as a set of secondary noise sources which randomize the spatial distribution of noise sources contributing to the coda waves in the correlation process. We developed a new technique to measure weak velocity changes based on the computation of the local phase variations (instantaneous phase variation or IPV) of the cross-correlated signals. This newly-developed technique takes advantage from the doublet and stretching techniques classically used to monitor weak velocity variation from coda waves. We apply IPV to data acquired in Northern America (Canada) on a 1-km side square seismic network laid out by 397 stations. Data used to study temporal variations are cross-correlated signals computed on 10-minutes ambient noise in the frequency band 2-5 Hz. As the data set was acquired over five days, about 660 files are processed to perform a complete temporal analysis for each stations pair. The IPV permits to estimate the phase shift all over the signal length without any assumption on the medium velocity. The instantaneous phase is computed using the Hilbert transform of the signal. For each stations pair, we measure the phase difference between successive correlation functions calculated for 10 minutes of ambient noise. We then fit the instantaneous phase shift using a first-order polynomial function. The measure of the velocity variation corresponds to the slope of this fit. Compared to other techniques, the advantage of IPV is a very fast procedure which efficiently provides the measure of velocity variation on large data sets. Both experimental results and numerical tests on synthetic signals will be presented to assess the reliability of the IPV technique, with comparison to the doublet and stretching methods.

Group identification in Indonesian stock market

NASA Astrophysics Data System (ADS)

Nurriyadi Suparno, Ervano; Jo, Sung Kyun; Lim, Kyuseong; Purqon, Acep; Kim, Soo Yong

2016-08-01

The characteristic of Indonesian stock market is interesting especially because it represents developing countries. We investigate the dynamics and structures by using Random Matrix Theory (RMT). Here, we analyze the cross-correlation of the fluctuations of the daily closing price of stocks from the Indonesian Stock Exchange (IDX) between January 1, 2007, and October 28, 2014. The eigenvalue distribution of the correlation matrix consists of noise which is filtered out using the random matrix as a control. The bulk of the eigenvalue distribution conforms to the random matrix, allowing the separation of random noise from original data which is the deviating eigenvalues. From the deviating eigenvalues and the corresponding eigenvectors, we identify the intrinsic normal modes of the system and interpret their meaning based on qualitative and quantitative approach. The results show that the largest eigenvector represents the market-wide effect which has a predominantly common influence toward all stocks. The other eigenvectors represent highly correlated groups within the system. Furthermore, identification of the largest components of the eigenvectors shows the sector or background of the correlated groups. Interestingly, the result shows that there are mainly two clusters within IDX, natural and non-natural resource companies. We then decompose the correlation matrix to investigate the contribution of the correlated groups to the total correlation, and we find that IDX is still driven mainly by the market-wide effect.

Random errors in interferometry with the least-squares method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang Qi

2011-01-20

This investigation analyzes random errors in interferometric surface profilers using the least-squares method when random noises are present. Two types of random noise are considered here: intensity noise and position noise. Two formulas have been derived for estimating the standard deviations of the surface height measurements: one is for estimating the standard deviation when only intensity noise is present, and the other is for estimating the standard deviation when only position noise is present. Measurements on simulated noisy interferometric data have been performed, and standard deviations of the simulated measurements have been compared with those theoretically derived. The relationships havemore » also been discussed between random error and the wavelength of the light source and between random error and the amplitude of the interference fringe.« less

Estimating rate uncertainty with maximum likelihood: differences between power-law and flicker–random-walk models

USGS Publications Warehouse

Langbein, John O.

2012-01-01

Recent studies have documented that global positioning system (GPS) time series of position estimates have temporal correlations which have been modeled as a combination of power-law and white noise processes. When estimating quantities such as a constant rate from GPS time series data, the estimated uncertainties on these quantities are more realistic when using a noise model that includes temporal correlations than simply assuming temporally uncorrelated noise. However, the choice of the specific representation of correlated noise can affect the estimate of uncertainty. For many GPS time series, the background noise can be represented by either: (1) a sum of flicker and random-walk noise or, (2) as a power-law noise model that represents an average of the flicker and random-walk noise. For instance, if the underlying noise model is a combination of flicker and random-walk noise, then incorrectly choosing the power-law model could underestimate the rate uncertainty by a factor of two. Distinguishing between the two alternate noise models is difficult since the flicker component can dominate the assessment of the noise properties because it is spread over a significant portion of the measurable frequency band. But, although not necessarily detectable, the random-walk component can be a major constituent of the estimated rate uncertainty. None the less, it is possible to determine the upper bound on the random-walk noise.

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

PubMed

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.

Seismic random noise attenuation method based on empirical mode decomposition of Hausdorff dimension

NASA Astrophysics Data System (ADS)

Yan, Z.; Luan, X.

2017-12-01

Introduction Empirical mode decomposition (EMD) is a noise suppression algorithm by using wave field separation, which is based on the scale differences between effective signal and noise. However, since the complexity of the real seismic wave field results in serious aliasing modes, it is not ideal and effective to denoise with this method alone. Based on the multi-scale decomposition characteristics of the signal EMD algorithm, combining with Hausdorff dimension constraints, we propose a new method for seismic random noise attenuation. First of all, We apply EMD algorithm adaptive decomposition of seismic data and obtain a series of intrinsic mode function (IMF)with different scales. Based on the difference of Hausdorff dimension between effectively signals and random noise, we identify IMF component mixed with random noise. Then we use threshold correlation filtering process to separate the valid signal and random noise effectively. Compared with traditional EMD method, the results show that the new method of seismic random noise attenuation has a better suppression effect. The implementation process The EMD algorithm is used to decompose seismic signals into IMF sets and analyze its spectrum. Since most of the random noise is high frequency noise, the IMF sets can be divided into three categories: the first category is the effective wave composition of the larger scale; the second category is the noise part of the smaller scale; the third category is the IMF component containing random noise. Then, the third kind of IMF component is processed by the Hausdorff dimension algorithm, and the appropriate time window size, initial step and increment amount are selected to calculate the Hausdorff instantaneous dimension of each component. The dimension of the random noise is between 1.0 and 1.05, while the dimension of the effective wave is between 1.05 and 2.0. On the basis of the previous steps, according to the dimension difference between the random noise and effective signal, we extracted the sample points, whose fractal dimension value is less than or equal to 1.05 for the each IMF components, to separate the residual noise. Using the IMF components after dimension filtering processing and the effective wave IMF components after the first selection for reconstruction, we can obtained the results of de-noising.

Noise modeling and analysis of an IMU-based attitude sensor: improvement of performance by filtering and sensor fusion

NASA Astrophysics Data System (ADS)

K., Nirmal; A. G., Sreejith; Mathew, Joice; Sarpotdar, Mayuresh; Suresh, Ambily; Prakash, Ajin; Safonova, Margarita; Murthy, Jayant

2016-07-01

We describe the characterization and removal of noises present in the Inertial Measurement Unit (IMU) MPU- 6050, which was initially used in an attitude sensor, and later used in the development of a pointing system for small balloon-borne astronomical payloads. We found that the performance of the IMU degraded with time because of the accumulation of different errors. Using Allan variance analysis method, we identified the different components of noise present in the IMU, and verified the results by the power spectral density analysis (PSD). We tried to remove the high-frequency noise using smooth filters such as moving average filter and then Savitzky Golay (SG) filter. Even though we managed to filter some high-frequency noise, these filters performance wasn't satisfactory for our application. We found the distribution of the random noise present in IMU using probability density analysis and identified that the noise in our IMU was white Gaussian in nature. Hence, we used a Kalman filter to remove the noise and which gave us good performance real time.

Practical quantum random number generator based on measuring the shot noise of vacuum states

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shen Yong; Zou Hongxin; Tian Liang

2010-06-15

The shot noise of vacuum states is a kind of quantum noise and is totally random. In this paper a nondeterministic random number generation scheme based on measuring the shot noise of vacuum states is presented and experimentally demonstrated. We use a homodyne detector to measure the shot noise of vacuum states. Considering that the frequency bandwidth of our detector is limited, we derive the optimal sampling rate so that sampling points have the least correlation with each other. We also choose a method to extract random numbers from sampling values, and prove that the influence of classical noise canmore » be avoided with this method so that the detector does not have to be shot-noise limited. The random numbers generated with this scheme have passed ent and diehard tests.« less

Statistical Significance of Periodicity and Log-Periodicity with Heavy-Tailed Correlated Noise

NASA Astrophysics Data System (ADS)

Zhou, Wei-Xing; Sornette, Didier

We estimate the probability that random noise, of several plausible standard distributions, creates a false alarm that a periodicity (or log-periodicity) is found in a time series. The solution of this problem is already known for independent Gaussian distributed noise. We investigate more general situations with non-Gaussian correlated noises and present synthetic tests on the detectability and statistical significance of periodic components. A periodic component of a time series is usually detected by some sort of Fourier analysis. Here, we use the Lomb periodogram analysis, which is suitable and outperforms Fourier transforms for unevenly sampled time series. We examine the false-alarm probability of the largest spectral peak of the Lomb periodogram in the presence of power-law distributed noises, of short-range and of long-range fractional-Gaussian noises. Increasing heavy-tailness (respectively correlations describing persistence) tends to decrease (respectively increase) the false-alarm probability of finding a large spurious Lomb peak. Increasing anti-persistence tends to decrease the false-alarm probability. We also study the interplay between heavy-tailness and long-range correlations. In order to fully determine if a Lomb peak signals a genuine rather than a spurious periodicity, one should in principle characterize the Lomb peak height, its width and its relations to other peaks in the complete spectrum. As a step towards this full characterization, we construct the joint-distribution of the frequency position (relative to other peaks) and of the height of the highest peak of the power spectrum. We also provide the distributions of the ratio of the highest Lomb peak to the second highest one. Using the insight obtained by the present statistical study, we re-examine previously reported claims of ``log-periodicity'' and find that the credibility for log-periodicity in 2D-freely decaying turbulence is weakened while it is strengthened for fracture, for the ion-signature prior to the Kobe earthquake and for financial markets.

A critical review of noise production models for turbulent, gas-fueled burners

NASA Technical Reports Server (NTRS)

Mahan, J. R.

1984-01-01

The combustion noise literature for the period between 1952 and early 1984 is critically reviewed. Primary emphasis is placed on past theoretical and semi-empirical attempts to predict or explain observed direct combustion noise characteristics of turbulent, gas-fueled burners; works involving liquid-fueled burners are reviewed only when ideas equally applicable to gas-fueled burners are pesented. The historical development of the most important contemporary direct combustion noise theories is traced, and the theories themselves are compared and criticized. While most theories explain combustion noise production by turbulent flames in terms of randomly distributed acoustic monopoles produced by turbulent mixing of products and reactants, none is able to predict the sound pressure in the acoustic farfield of a practical burner because of the lack of a proven model which relates the combustion noise source strenght at a given frequency to the design and operating parameters of the burner. Recommendations are given for establishing a benchmark-quality data base needed to support the development of such a model.

Noise in ecosystems: a short review.

PubMed

Spagnolo, B; Valenti, D; Fiasconaro, A

2004-06-01

Noise, through its interaction with the nonlinearity of the living systems, can give rise to counter-intuitive phenomena such as stochastic resonance, noise-delayed extinction, temporal oscillations, and spatial patterns. In this paper we briefly review the noise-induced effects in three different ecosystems: (i) two competing species; (ii) three interacting species, one predator and two preys, and (iii) N-interacting species. The transient dynamics of these ecosystems are analyzed through generalized Lotka-Volterra equations in the presence of multiplicative noise, which models the interaction between the species and the environment. The interaction parameter between the species is random in cases (i) and (iii), and a periodical function, which accounts for the environmental temperature, in case (ii). We find noise-induced phenomena such as quasi-deterministic oscillations, stochastic resonance, noise-delayed extinction, and noise-induced pattern formation with nonmonotonic behaviors of patterns areas and of the density correlation as a function of the multiplicative noise intensity. The asymptotic behavior of the time average of the i(th) population when the ecosystem is composed of a great number of interacting species is obtained and the effect of the noise on the asymptotic probability distributions of the populations is discussed.

Understanding genetic regulatory networks

NASA Astrophysics Data System (ADS)

Kauffman, Stuart

2003-04-01

Random Boolean networks (RBM) were introduced about 35 years ago as first crude models of genetic regulatory networks. RBNs are comprised of N on-off genes, connected by a randomly assigned regulatory wiring diagram where each gene has K inputs, and each gene is controlled by a randomly assigned Boolean function. This procedure samples at random from the ensemble of all possible NK Boolean networks. The central ideas are to study the typical, or generic properties of this ensemble, and see 1) whether characteristic differences appear as K and biases in Boolean functions are introducted, and 2) whether a subclass of this ensemble has properties matching real cells. Such networks behave in an ordered or a chaotic regime, with a phase transition, "the edge of chaos" between the two regimes. Networks with continuous variables exhibit the same two regimes. Substantial evidence suggests that real cells are in the ordered regime. A key concept is that of an attractor. This is a reentrant trajectory of states of the network, called a state cycle. The central biological interpretation is that cell types are attractors. A number of properties differentiate the ordered and chaotic regimes. These include the size and number of attractors, the existence in the ordered regime of a percolating "sea" of genes frozen in the on or off state, with a remainder of isolated twinkling islands of genes, a power law distribution of avalanches of gene activity changes following perturbation to a single gene in the ordered regime versus a similar power law distribution plus a spike of enormous avalanches of gene changes in the chaotic regime, and the existence of branching pathway of "differentiation" between attractors induced by perturbations in the ordered regime. Noise is serious issue, since noise disrupts attractors. But numerical evidence suggests that attractors can be made very stable to noise, and meanwhile, metaplasias may be a biological manifestation of noise. As we learn more about the wiring diagram and constraints on rules controlling real genes, we can build refined ensembles reflecting these properties, study the generic properties of the refined ensembles, and hope to gain insight into the dynamics of real cells.

Experimental integration of quantum key distribution and gigabit-capable passive optical network

NASA Astrophysics Data System (ADS)

Sun, Wei; Wang, Liu-Jun; Sun, Xiang-Xiang; Mao, Yingqiu; Yin, Hua-Lei; Wang, Bi-Xiao; Chen, Teng-Yun; Pan, Jian-Wei

2018-01-01

Quantum key distribution (QKD) ensures information-theoretic security for the distribution of random bits between two remote parties. To extend QKD applications to fiber-to-the-home optical communications, such as gigabit-capable passive optical networks (GPONs), an effective method is the use of wavelength-division multiplexing. However, the Raman scattering noise from intensive classical traffic and the huge loss introduced by the beam splitter in a GPON severely limits the performance of QKD. Here, we demonstrate the integration of QKD and a commercial GPON system with fiber lengths up to 14 km, in which the maximum splitting ratio of the beam splitter reaches 1:64. By placing the QKD transmitter on the optical line terminal side, we reduce the Raman noise collected at the QKD receiver. Using a bypass structure, the loss of the beam splitter is circumvented effectively. Our results pave the way to extending the applications of QKD to last-mile communications.

Phase diagram for the Kuramoto model with van Hemmen interactions.

PubMed

Kloumann, Isabel M; Lizarraga, Ian M; Strogatz, Steven H

2014-01-01

We consider a Kuramoto model of coupled oscillators that includes quenched random interactions of the type used by van Hemmen in his model of spin glasses. The phase diagram is obtained analytically for the case of zero noise and a Lorentzian distribution of the oscillators' natural frequencies. Depending on the size of the attractive and random coupling terms, the system displays four states: complete incoherence, partial synchronization, partial antiphase synchronization, and a mix of antiphase and ordinary synchronization.

Probabilistic inference in discrete spaces can be implemented into networks of LIF neurons.

PubMed

Probst, Dimitri; Petrovici, Mihai A; Bytschok, Ilja; Bill, Johannes; Pecevski, Dejan; Schemmel, Johannes; Meier, Karlheinz

2015-01-01

The means by which cortical neural networks are able to efficiently solve inference problems remains an open question in computational neuroscience. Recently, abstract models of Bayesian computation in neural circuits have been proposed, but they lack a mechanistic interpretation at the single-cell level. In this article, we describe a complete theoretical framework for building networks of leaky integrate-and-fire neurons that can sample from arbitrary probability distributions over binary random variables. We test our framework for a model inference task based on a psychophysical phenomenon (the Knill-Kersten optical illusion) and further assess its performance when applied to randomly generated distributions. As the local computations performed by the network strongly depend on the interaction between neurons, we compare several types of couplings mediated by either single synapses or interneuron chains. Due to its robustness to substrate imperfections such as parameter noise and background noise correlations, our model is particularly interesting for implementation on novel, neuro-inspired computing architectures, which can thereby serve as a fast, low-power substrate for solving real-world inference problems.

Probabilistic inference in discrete spaces can be implemented into networks of LIF neurons

PubMed Central

Probst, Dimitri; Petrovici, Mihai A.; Bytschok, Ilja; Bill, Johannes; Pecevski, Dejan; Schemmel, Johannes; Meier, Karlheinz

2015-01-01

The means by which cortical neural networks are able to efficiently solve inference problems remains an open question in computational neuroscience. Recently, abstract models of Bayesian computation in neural circuits have been proposed, but they lack a mechanistic interpretation at the single-cell level. In this article, we describe a complete theoretical framework for building networks of leaky integrate-and-fire neurons that can sample from arbitrary probability distributions over binary random variables. We test our framework for a model inference task based on a psychophysical phenomenon (the Knill-Kersten optical illusion) and further assess its performance when applied to randomly generated distributions. As the local computations performed by the network strongly depend on the interaction between neurons, we compare several types of couplings mediated by either single synapses or interneuron chains. Due to its robustness to substrate imperfections such as parameter noise and background noise correlations, our model is particularly interesting for implementation on novel, neuro-inspired computing architectures, which can thereby serve as a fast, low-power substrate for solving real-world inference problems. PMID:25729361

Method and apparatus for in-situ characterization of energy storage and energy conversion devices

DOEpatents

Christophersen, Jon P [Idaho Falls, ID; Motloch, Chester G [Idaho Falls, ID; Morrison, John L [Butte, MT; Albrecht, Weston [Layton, UT

2010-03-09

Disclosed are methods and apparatuses for determining an impedance of an energy-output device using a random noise stimulus applied to the energy-output device. A random noise signal is generated and converted to a random noise stimulus as a current source correlated to the random noise signal. A bias-reduced response of the energy-output device to the random noise stimulus is generated by comparing a voltage at the energy-output device terminal to an average voltage signal. The random noise stimulus and bias-reduced response may be periodically sampled to generate a time-varying current stimulus and a time-varying voltage response, which may be correlated to generate an autocorrelated stimulus, an autocorrelated response, and a cross-correlated response. Finally, the autocorrelated stimulus, the autocorrelated response, and the cross-correlated response may be combined to determine at least one of impedance amplitude, impedance phase, and complex impedance.

Computation of Steady-State Probability Distributions in Stochastic Models of Cellular Networks

PubMed Central

Hallen, Mark; Li, Bochong; Tanouchi, Yu; Tan, Cheemeng; West, Mike; You, Lingchong

2011-01-01

Cellular processes are “noisy”. In each cell, concentrations of molecules are subject to random fluctuations due to the small numbers of these molecules and to environmental perturbations. While noise varies with time, it is often measured at steady state, for example by flow cytometry. When interrogating aspects of a cellular network by such steady-state measurements of network components, a key need is to develop efficient methods to simulate and compute these distributions. We describe innovations in stochastic modeling coupled with approaches to this computational challenge: first, an approach to modeling intrinsic noise via solution of the chemical master equation, and second, a convolution technique to account for contributions of extrinsic noise. We show how these techniques can be combined in a streamlined procedure for evaluation of different sources of variability in a biochemical network. Evaluation and illustrations are given in analysis of two well-characterized synthetic gene circuits, as well as a signaling network underlying the mammalian cell cycle entry. PMID:22022252

High-speed free-space optical continuous-variable quantum key distribution enabled by three-dimensional multiplexing.

PubMed

Qu, Zhen; Djordjevic, Ivan B

2017-04-03

A high-speed four-state continuous-variable quantum key distribution (CV-QKD) system, enabled by wavelength-division multiplexing, polarization multiplexing, and orbital angular momentum (OAM) multiplexing, is studied in the presence of atmospheric turbulence. The atmospheric turbulence channel is emulated by two spatial light modulators (SLMs) on which two randomly generated azimuthal phase patterns yielding Andrews' spectrum are recorded. The phase noise is mitigated by the phase noise cancellation (PNC) stage, and channel transmittance can be monitored directly by the D.C. level in our PNC stage. After the system calibration, a total SKR of >1.68 Gbit/s can be reached in the ideal system, featured with lossless channel and free of excess noise. In our experiment, based on commercial photodetectors, the minimum transmittances of 0.21 and 0.29 are required for OAM states of 2 (or -2) and 6 (or -6), respectively, to guarantee the secure transmission, while a total SKR of 120 Mbit/s can be obtained in case of mean transmittances.

Recovering Galaxy Properties Using Gaussian Process SED Fitting

NASA Astrophysics Data System (ADS)

Iyer, Kartheik; Awan, Humna

2018-01-01

Information about physical quantities like the stellar mass, star formation rates, and ages for distant galaxies is contained in their spectral energy distributions (SEDs), obtained through photometric surveys like SDSS, CANDELS, LSST etc. However, noise in the photometric observations often is a problem, and using naive machine learning methods to estimate physical quantities can result in overfitting the noise, or converging on solutions that lie outside the physical regime of parameter space.We use Gaussian Process regression trained on a sample of SEDs corresponding to galaxies from a Semi-Analytic model (Somerville+15a) to estimate their stellar masses, and compare its performance to a variety of different methods, including simple linear regression, Random Forests, and k-Nearest Neighbours. We find that the Gaussian Process method is robust to noise and predicts not only stellar masses but also their uncertainties. The method is also robust in the cases where the distribution of the training data is not identical to the target data, which can be extremely useful when generalized to more subtle galaxy properties.

Motion of Euglena gracilis: Active fluctuations and velocity distribution

NASA Astrophysics Data System (ADS)

Romanczuk, P.; Romensky, M.; Scholz, D.; Lobaskin, V.; Schimansky-Geier, L.

2015-07-01

We study the velocity distribution of unicellular swimming algae Euglena gracilis using optical microscopy and active Brownian particle theory. To characterize a peculiar feature of the experimentally observed distribution at small velocities we use the concept of active fluctuations, which was recently proposed for the description of stochastically self-propelled particles [Romanczuk, P. and Schimansky-Geier, L., Phys. Rev. Lett. 106, 230601 (2011)]. In this concept, the fluctuating forces arise due to internal random performance of the propulsive motor. The fluctuating forces are directed in parallel to the heading direction, in which the propulsion acts. In the theory, we introduce the active motion via the depot model [Schweitzer, et al., Phys. Rev. Lett. 80(23), 5044 (1998)]. We demonstrate that the theoretical predictions based on the depot model with active fluctuations are consistent with the experimentally observed velocity distributions. In addition to the model with additive active noise, we obtain theoretical results for a constant propulsion with multiplicative noise.

Single-photon continuous-variable quantum key distribution based on the energy-time uncertainty relation.

PubMed

Qi, Bing

2006-09-15

We propose a new quantum key distribution protocol in which information is encoded on continuous variables of a single photon. In this protocol, Alice randomly encodes her information on either the central frequency of a narrowband single-photon pulse or the time delay of a broadband single-photon pulse, while Bob randomly chooses to do either frequency measurement or time measurement. The security of this protocol rests on the energy-time uncertainty relation, which prevents Eve from simultaneously determining both frequency and time information with arbitrarily high resolution. Since no interferometer is employed in this scheme, it is more robust against various channel noises, such as polarization and phase fluctuations.

A statistical model of false negative and false positive detection of phase singularities.

PubMed

Jacquemet, Vincent

2017-10-01

The complexity of cardiac fibrillation dynamics can be assessed by analyzing the distribution of phase singularities (PSs) observed using mapping systems. Interelectrode distance, however, limits the accuracy of PS detection. To investigate in a theoretical framework the PS false negative and false positive rates in relation to the characteristics of the mapping system and fibrillation dynamics, we propose a statistical model of phase maps with controllable number and locations of PSs. In this model, phase maps are generated from randomly distributed PSs with physiologically-plausible directions of rotation. Noise and distortion of the phase are added. PSs are detected using topological charge contour integrals on regular grids of varying resolutions. Over 100 × 10 6 realizations of the random field process are used to estimate average false negative and false positive rates using a Monte-Carlo approach. The false detection rates are shown to depend on the average distance between neighboring PSs expressed in units of interelectrode distance, following approximately a power law with exponents in the range of 1.14 to 2 for false negatives and around 2.8 for false positives. In the presence of noise or distortion of phase, false detection rates at high resolution tend to a non-zero noise-dependent lower bound. This model provides an easy-to-implement tool for benchmarking PS detection algorithms over a broad range of configurations with multiple PSs.

Statistical properties of a filtered Poisson process with additive random noise: distributions, correlations and moment estimation

NASA Astrophysics Data System (ADS)

Theodorsen, A.; E Garcia, O.; Rypdal, M.

2017-05-01

Filtered Poisson processes are often used as reference models for intermittent fluctuations in physical systems. Such a process is here extended by adding a noise term, either as a purely additive term to the process or as a dynamical term in a stochastic differential equation. The lowest order moments, probability density function, auto-correlation function and power spectral density are derived and used to identify and compare the effects of the two different noise terms. Monte-Carlo studies of synthetic time series are used to investigate the accuracy of model parameter estimation and to identify methods for distinguishing the noise types. It is shown that the probability density function and the three lowest order moments provide accurate estimations of the model parameters, but are unable to separate the noise types. The auto-correlation function and the power spectral density also provide methods for estimating the model parameters, as well as being capable of identifying the noise type. The number of times the signal crosses a prescribed threshold level in the positive direction also promises to be able to differentiate the noise type.

Investigation of mode partition noise in Fabry-Perot laser diode

NASA Astrophysics Data System (ADS)

Guo, Qingyi; Deng, Lanxin; Mu, Jianwei; Li, Xun; Huang, Wei-Ping

2014-09-01

Passive optical network (PON) is considered as the most appealing access network architecture in terms of cost-effectiveness, bandwidth management flexibility, scalability and durability. And to further reduce the cost per subscriber, a Fabry-Perot (FP) laser diode is preferred as the transmitter at the optical network units (ONUs) because of its lower cost compared to distributed feedback (DFB) laser diode. However, the mode partition noise (MPN) associated with the multi-longitudinal-mode FP laser diode becomes the limiting factor in the network. This paper studies the MPN characteristics of the FP laser diode using the time-domain simulation of noise-driven multi-mode laser rate equation. The probability density functions are calculated for each longitudinal mode. The paper focuses on the investigation of the k-factor, which is a simple yet important measure of the noise power, but is usually taken as a fitted or assumed value in the penalty calculations. In this paper, the sources of the k-factor are studied with simulation, including the intrinsic source of the laser Langevin noise, and the extrinsic source of the bit pattern. The photon waveforms are shown under four simulation conditions for regular or random bit pattern, and with or without Langevin noise. The k-factors contributed by those sources are studied with a variety of bias current and modulation current. Simulation results are illustrated in figures, and show that the contribution of Langevin noise to the k-factor is larger than that of the random bit pattern, and is more dominant at lower bias current or higher modulation current.

Does the noise matter? Effects of different kinematogram types on smooth pursuit eye movements and perception

PubMed Central

Schütz, Alexander C.; Braun, Doris I.; Movshon, J. Anthony; Gegenfurtner, Karl R.

2011-01-01

We investigated how the human visual system and the pursuit system react to visual motion noise. We presented three different types of random-dot kinematograms at five different coherence levels. For transparent motion, the signal and noise labels on each dot were preserved throughout each trial, and noise dots moved with the same speed as the signal dots but in fixed random directions. For white noise motion, every 20 ms the signal and noise labels were randomly assigned to each dot and noise dots appeared at random positions. For Brownian motion, signal and noise labels were also randomly assigned, but the noise dots moved at the signal speed in a direction that varied randomly from moment to moment. Neither pursuit latency nor early eye acceleration differed among the different types of kinematograms. Late acceleration, pursuit gain, and perceived speed all depended on kinematogram type, with good agreement between pursuit gain and perceived speed. For transparent motion, pursuit gain and perceived speed were independent of coherence level. For white and Brownian motions, pursuit gain and perceived speed increased with coherence but were higher for white than for Brownian motion. This suggests that under our conditions, the pursuit system integrates across all directions of motion but not across all speeds. PMID:21149307

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

PLNoise: a package for exact numerical simulation of power-law noises

NASA Astrophysics Data System (ADS)

Milotti, Edoardo

2006-08-01

Many simulations of stochastic processes require colored noises: here I describe a small program library that generates samples with a tunable power-law spectral density: the algorithm can be modified to generate more general colored noises, and is exact for all time steps, even when they are unevenly spaced (as may often happen in the case of astronomical data, see e.g. [N.R. Lomb, Astrophys. Space Sci. 39 (1976) 447]. The method is exact in the sense that it reproduces a process that is theoretically guaranteed to produce a range-limited power-law spectrum 1/f with -1<β⩽1. The algorithm has a well-behaved computational complexity, it produces a nearly perfect Gaussian noise, and its computational efficiency depends on the required degree of noise Gaussianity. Program summaryTitle of program: PLNoise Catalogue identifier:ADXV_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXV_v1_0.html Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Licensing provisions: none Programming language used: ANSI C Computer: Any computer with an ANSI C compiler: the package has been tested with gcc version 3.2.3 on Red Hat Linux 3.2.3-52 and gcc version 4.0.0 and 4.0.1 on Apple Mac OS X-10.4 Operating system: All operating systems capable of running an ANSI C compiler No. of lines in distributed program, including test data, etc.:6238 No. of bytes in distributed program, including test data, etc.:52 387 Distribution format:tar.gz RAM: The code of the test program is very compact (about 50 Kbytes), but the program works with list management and allocates memory dynamically; in a typical run (like the one discussed in Section 4 in the long write-up) with average list length 2ṡ10, the RAM taken by the list is 200 Kbytes. External routines: The package needs external routines to generate uniform and exponential deviates. The implementation described here uses the random number generation library ranlib freely available from Netlib [B.W. Brown, J. Lovato, K. Russell, ranlib, available from Netlib, http://www.netlib.org/random/index.html, select the C version ranlib.c], but it has also been successfully tested with the random number routines in Numerical Recipes [W.H. Press, S.A. Teulkolsky, W.T. Vetterling, B.P. Flannery, Numerical Recipes in C: The Art of Scientific Computing, second ed., Cambridge Univ. Press, Cambridge, 1992, pp. 274-290]. Notice that ranlib requires a pair of routines from the linear algebra package LINPACK, and that the distribution of ranlib includes the C source of these routines, in case LINPACK is not installed on the target machine. Nature of problem: Exact generation of different types of Gaussian colored noise. Solution method: Random superposition of relaxation processes [E. Milotti, Phys. Rev. E 72 (2005) 056701]. Unusual features: The algorithm is theoretically guaranteed to be exact, and unlike all other existing generators it can generate samples with uneven spacing. Additional comments: The program requires an initialization step; for some parameter sets this may become rather heavy. Running time: Running time varies widely with different input parameters, however in a test run like the one in Section 4 in this work, the generation routine took on average about 7 ms for each sample.

Electronic Noise and Fluctuations in Solids

NASA Astrophysics Data System (ADS)

Kogan, Sh.

2008-07-01

Preface; Part I. Introduction. Some Basic Concepts of the Theory of Random Processes: 1. Probability density functions. Moments. Stationary processes; 2. Correlation function; 3. Spectral density of noise; 4. Ergodicity and nonergodicity of random processes; 5. Random pulses and shot noise; 6. Markov processes. General theory; 7. Discrete Markov processes. Random telegraph noise; 8. Quasicontinuous (Diffusion-like) Markov processes; 9. Brownian motion; 10. Langevin approach to the kinetics of fluctuations; Part II. Fluctuation-Dissipation Relations in Equilibrium Systems: 11. Derivation of fluctuation-dissipation relations; 12. Equilibrium noise in quasistationary circuits. Nyquist theorem; 13. Fluctuations of electromagnetic fields in continuous media; Part III. Fluctuations in Nonequilibrium Gases: 14. Some basic concepts of hot-electrons' physics; 15. Simple model of current fluctuations in a semiconductor with hot electrons; 16. General kinetic theory of quasiclassical fluctuations in a gas of particles. The Boltzmann-Langevin equation; 17. Current fluctuations and noise temperature; 18. Current fluctuations and diffusion in a gas of hot electrons; 19. One-time correlation in nonequilibrium gases; 20. Intervalley noise in multivalley semiconductors; 21. Noise of hot electrons emitting optical phonons in the streaming regime; 22. Noise in a semiconductor with a postbreakdown stable current filament; Part IV. Generation-recombination noise: 23. G-R noise in uniform unipolar semiconductors; 24. Noise produced by recombination and diffusion; Part V. Noise in quantum ballistic systems: 25. Introduction; 26. Equilibrium noise and shot noise in quantum conductors; 27. Modulation noise in quantum point contacts; 28. Transition from a ballistic conductor to a macroscopic one; 29. Noise in tunnel junctions; Part VI. Resistance noise in metals: 30. Incoherent scattering of electrons by mobile defects; 31. Effect of mobile scattering centers on the electron interference pattern; 32. Fluctuations of the number of diffusing scattering centers; 33. Temperature fluctuations and the corresponding noise; Part VII. Noise in strongly disordered conductors: 34. Basic ideas of the percolation theory; 35. Resistance fluctuations in percolation systems. 36. Experiments; Part VIII. Low-frequency noise with an 1/f-type spectrum and random telegraph noise: 37. Introduction; 38. Some general properties of 1/f noise; 39. Basic models of 1/f noise; 40./f noise in metals; 41. Low-frequency noise in semiconductors; 42. Magnetic noise in spin glasses and some other magnetic systems; 43. Temperature fluctuations as a possible source of 1/f noise; 44. Random telegraph noise; 45. Fluctuations with 1/f spectrum in other systems; 46. General conclusions on 1/f noise; Part IX. Noise in Superconductors and Superconducting Structures: 47. Noise in Josephson junctions; 48. Noise in type II superconductors; References; Subject index.

New distributed fusion filtering algorithm based on covariances over sensor networks with random packet dropouts

NASA Astrophysics Data System (ADS)

Caballero-Águila, R.; Hermoso-Carazo, A.; Linares-Pérez, J.

2017-07-01

This paper studies the distributed fusion estimation problem from multisensor measured outputs perturbed by correlated noises and uncertainties modelled by random parameter matrices. Each sensor transmits its outputs to a local processor over a packet-erasure channel and, consequently, random losses may occur during transmission. Different white sequences of Bernoulli variables are introduced to model the transmission losses. For the estimation, each lost output is replaced by its estimator based on the information received previously, and only the covariances of the processes involved are used, without requiring the signal evolution model. First, a recursive algorithm for the local least-squares filters is derived by using an innovation approach. Then, the cross-correlation matrices between any two local filters is obtained. Finally, the distributed fusion filter weighted by matrices is obtained from the local filters by applying the least-squares criterion. The performance of the estimators and the influence of both sensor uncertainties and transmission losses on the estimation accuracy are analysed in a numerical example.

Studies in astronomical time series analysis: Modeling random processes in the time domain

NASA Technical Reports Server (NTRS)

Scargle, J. D.

1979-01-01

Random process models phased in the time domain are used to analyze astrophysical time series data produced by random processes. A moving average (MA) model represents the data as a sequence of pulses occurring randomly in time, with random amplitudes. An autoregressive (AR) model represents the correlations in the process in terms of a linear function of past values. The best AR model is determined from sampled data and transformed to an MA for interpretation. The randomness of the pulse amplitudes is maximized by a FORTRAN algorithm which is relatively stable numerically. Results of test cases are given to study the effects of adding noise and of different distributions for the pulse amplitudes. A preliminary analysis of the optical light curve of the quasar 3C 273 is given.

Preventive and Abortive Strategies for Stimulation Based Control of Epilepsy: A Computational Model Study.

PubMed

Koppert, Marc; Kalitzin, Stiliyan; Velis, Demetrios; Lopes Da Silva, Fernando; Viergever, Max A

2016-12-01

Epilepsy is a condition in which periods of ongoing normal EEG activity alternate with periods of oscillatory behavior characteristic of epileptic seizures. The dynamics of the transitions between the two states are still unclear. Computational models provide a powerful tool to explore the underlying mechanisms of such transitions, with the purpose of eventually finding therapeutic interventions for this debilitating condition. In this study, the possibility to postpone seizures elicited by a decrease of inhibition is investigated by using external stimulation in a realistic bistable neuronal model consisting of two interconnected neuronal populations representing pyramidal cells and interneurons. In the simulations, seizures are induced by slowly decreasing the conductivity of GABA[Formula: see text] synaptic channels over time. Since the model is bistable, the system will change state from the initial steady state (SS) to the limit cycle (LS) state because of internal noise, when the inhibition falls below a certain threshold. Several state-independent stimulations paradigms are simulated. Their effectiveness is analyzed for various stimulation frequencies and intensities in combination with periodic and random stimulation sequences. The distributions of the time to first seizure in the presence of stimulation are compared with the situation without stimulation. In addition, stimulation protocols targeted to specific subsystems are applied with the objective of counteracting the baseline shift due to decreased inhibition in the system. Furthermore, an analytical model is used to investigate the effects of random noise. The relation between the strength of random noise stimulation, the control parameter of the system and the transitions between steady state and limit cycle are investigated. The study shows that it is possible to postpone epileptic activity by targeted stimulation in a realistic neuronal model featuring bistability and that it is possible to stop seizures by random noise in an analytical model.

Neural Mechanisms Behind Identification of Leptokurtic Noise and Adaptive Behavioral Response

PubMed Central

d'Acremont, Mathieu; Bossaerts, Peter

2016-01-01

Large-scale human interaction through, for example, financial markets causes ceaseless random changes in outcome variability, producing frequent and salient outliers that render the outcome distribution more peaked than the Gaussian distribution, and with longer tails. Here, we study how humans cope with this evolutionary novel leptokurtic noise, focusing on the neurobiological mechanisms that allow the brain, 1) to recognize the outliers as noise and 2) to regulate the control necessary for adaptive response. We used functional magnetic resonance imaging, while participants tracked a target whose movements were affected by leptokurtic noise. After initial overreaction and insufficient subsequent correction, participants improved performance significantly. Yet, persistently long reaction times pointed to continued need for vigilance and control. We ran a contrasting treatment where outliers reflected permanent moves of the target, as in traditional mean-shift paradigms. Importantly, outliers were equally frequent and salient. There, control was superior and reaction time was faster. We present a novel reinforcement learning model that fits observed choices better than the Bayes-optimal model. Only anterior insula discriminated between the 2 types of outliers. In both treatments, outliers initially activated an extensive bottom-up attention and belief network, followed by sustained engagement of the fronto-parietal control network. PMID:26850528

Evolution and anti-evolution in a minimal stock market model

NASA Astrophysics Data System (ADS)

Rothenstein, R.; Pawelzik, K.

2003-08-01

We present a novel microscopic stock market model consisting of a large number of random agents modeling traders in a market. Each agent is characterized by a set of parameters that serve to make iterated predictions of two successive returns. The future price is determined according to the offer and the demand of all agents. The system evolves by redistributing the capital among the agents in each trading cycle. Without noise the dynamics of this system is nearly regular and thereby fails to reproduce the stochastic return fluctuations observed in real markets. However, when in each cycle a small amount of noise is introduced we find the typical features of real financial time series like fat-tails of the return distribution and large temporal correlations in the volatility without significant correlations in the price returns. Introducing the noise by an evolutionary process leads to different scalings of the return distributions that depend on the definition of fitness. Because our realistic model has only very few parameters, and the results appear to be robust with respect to the noise level and the number of agents we expect that our framework may serve as new paradigm for modeling self-generated return fluctuations in markets.

Analysis of Noise Mechanisms in Cell-Size Control.

PubMed

Modi, Saurabh; Vargas-Garcia, Cesar Augusto; Ghusinga, Khem Raj; Singh, Abhyudai

2017-06-06

At the single-cell level, noise arises from multiple sources, such as inherent stochasticity of biomolecular processes, random partitioning of resources at division, and fluctuations in cellular growth rates. How these diverse noise mechanisms combine to drive variations in cell size within an isoclonal population is not well understood. Here, we investigate the contributions of different noise sources in well-known paradigms of cell-size control, such as adder (division occurs after adding a fixed size from birth), sizer (division occurs after reaching a size threshold), and timer (division occurs after a fixed time from birth). Analysis reveals that variation in cell size is most sensitive to errors in partitioning of volume among daughter cells, and not surprisingly, this process is well regulated among microbes. Moreover, depending on the dominant noise mechanism, different size-control strategies (or a combination of them) provide efficient buffering of size variations. We further explore mixer models of size control, where a timer phase precedes/follows an adder, as has been proposed in Caulobacter crescentus. Although mixing a timer and an adder can sometimes attenuate size variations, it invariably leads to higher-order moments growing unboundedly over time. This results in a power-law distribution for the cell size, with an exponent that depends inversely on the noise in the timer phase. Consistent with theory, we find evidence of power-law statistics in the tail of C. crescentus cell-size distribution, although there is a discrepancy between the observed power-law exponent and that predicted from the noise parameters. The discrepancy, however, is removed after data reveal that the size added by individual newborns in the adder phase itself exhibits power-law statistics. Taken together, this study provides key insights into the role of noise mechanisms in size homeostasis, and suggests an inextricable link between timer-based models of size control and heavy-tailed cell-size distributions. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Least squares deconvolution for leak detection with a pseudo random binary sequence excitation

NASA Astrophysics Data System (ADS)

Nguyen, Si Tran Nguyen; Gong, Jinzhe; Lambert, Martin F.; Zecchin, Aaron C.; Simpson, Angus R.

2018-01-01

Leak detection and localisation is critical for water distribution system pipelines. This paper examines the use of the time-domain impulse response function (IRF) for leak detection and localisation in a pressurised water pipeline with a pseudo random binary sequence (PRBS) signal excitation. Compared to the conventional step wave generated using a single fast operation of a valve closure, a PRBS signal offers advantageous correlation properties, in that the signal has very low autocorrelation for lags different from zero and low cross correlation with other signals including noise and other interference. These properties result in a significant improvement in the IRF signal to noise ratio (SNR), leading to more accurate leak localisation. In this paper, the estimation of the system IRF is formulated as an optimisation problem in which the l2 norm of the IRF is minimised to suppress the impact of noise and interference sources. Both numerical and experimental data are used to verify the proposed technique. The resultant estimated IRF provides not only accurate leak location estimation, but also good sensitivity to small leak sizes due to the improved SNR.

Model-based optimization of near-field binary-pixelated beam shapers

DOE PAGES

Dorrer, C.; Hassett, J.

2017-01-23

The optimization of components that rely on spatially dithered distributions of transparent or opaque pixels and an imaging system with far-field filtering for transmission control is demonstrated. The binary-pixel distribution can be iteratively optimized to lower an error function that takes into account the design transmission and the characteristics of the required far-field filter. Simulations using a design transmission chosen in the context of high-energy lasers show that the beam-fluence modulation at an image plane can be reduced by a factor of 2, leading to performance similar to using a non-optimized spatial-dithering algorithm with pixels of size reduced by amore » factor of 2 without the additional fabrication complexity or cost. The optimization process preserves the pixel distribution statistical properties. Analysis shows that the optimized pixel distribution starting from a high-noise distribution defined by a random-draw algorithm should be more resilient to fabrication errors than the optimized pixel distributions starting from a low-noise, error-diffusion algorithm, while leading to similar beamshaping performance. Furthermore, this is confirmed by experimental results obtained with various pixel distributions and induced fabrication errors.« less

Delay-induced stochastic bifurcations in a bistable system under white noise

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, Zhongkui, E-mail: sunzk@nwpu.edu.cn; Fu, Jin; Xu, Wei

2015-08-15

In this paper, the effects of noise and time delay on stochastic bifurcations are investigated theoretically and numerically in a time-delayed Duffing-Van der Pol oscillator subjected to white noise. Due to the time delay, the random response is not Markovian. Thereby, approximate methods have been adopted to obtain the Fokker-Planck-Kolmogorov equation and the stationary probability density function for amplitude of the response. Based on the knowledge that stochastic bifurcation is characterized by the qualitative properties of the steady-state probability distribution, it is found that time delay and feedback intensity as well as noise intensity will induce the appearance of stochasticmore » P-bifurcation. Besides, results demonstrated that the effects of the strength of the delayed displacement feedback on stochastic bifurcation are accompanied by the sensitive dependence on time delay. Furthermore, the results from numerical simulations best confirm the effectiveness of the theoretical analyses.« less

Noise induced oscillations and coherence resonance in a generic model of the nonisothermal chemical oscillator

PubMed Central

Simakov, David S. A.; Pérez-Mercader, Juan

2013-01-01

Oscillating chemical reactions are common in biological systems and they also occur in artificial non-biological systems. Generally, these reactions are subject to random fluctuations in environmental conditions which translate into fluctuations in the values of physical variables, for example, temperature. We formulate a mathematical model for a nonisothermal minimal chemical oscillator containing a single negative feedback loop and study numerically the effects of stochastic fluctuations in temperature in the absence of any deterministic limit cycle or periodic forcing. We show that noise in temperature can induce sustained limit cycle oscillations with a relatively narrow frequency distribution and some characteristic frequency. These properties differ significantly depending on the noise correlation. Here, we have explored white and colored (correlated) noise. A plot of the characteristic frequency of the noise induced oscillations as a function of the correlation exponent shows a maximum, therefore indicating the existence of autonomous stochastic resonance, i.e. coherence resonance. PMID:23929212

Asymmetric noise sensitivity of pulse trains in an excitable microlaser with delayed optical feedback

NASA Astrophysics Data System (ADS)

Terrien, Soizic; Krauskopf, Bernd; Broderick, Neil G. R.; Andréoli, Louis; Selmi, Foued; Braive, Rémy; Beaudoin, Grégoire; Sagnes, Isabelle; Barbay, Sylvain

2017-10-01

A semiconductor micropillar laser with delayed optical feedback is considered. In the excitable regime, we show that a single optical perturbation can trigger a train of pulses that is sustained for a finite duration. The distribution of the pulse train duration exhibits an exponential behavior characteristic of a noise-induced process driven by uncorrelated white noise present in the system. The comparison of experimental observations with theoretical and numerical analysis of a minimal model yields excellent agreement. Importantly, the random switch-off process takes place between two attractors of different nature: an equilibrium and a periodic orbit. Our analysis shows that there is a small time window during which the pulsations are very sensitive to noise, and this explains the observed strong bias toward switch-off. These results raise the possibility of all optical control of the pulse train duration that may have an impact for practical applications in photonics and may also apply to the dynamics of other noise-driven excitable systems with delayed feedback.

Evidence of Non-extensivity in Earth's Ambient Noise

NASA Astrophysics Data System (ADS)

Koutalonis, Ioannis; Vallianatos, Filippos

2017-12-01

The study of ambient seismic noise is one of the important scientific and practical research challenges, due to its use in a number of geophysical applications. In this work, we describe Earth's ambient noise fluctuations in terms of non-extensive statistical physics. We found that Earth's ambient noise increments follow the q-Gaussian distribution. This indicates that Earth's ambient noise's fluctuations are not random and present long-term memory effects that could be described in terms of Tsallis entropy. Our results suggest that q values depend on the time length used and that the non-extensive parameter, q, converges to value q → 1 for short-time windows and a saturation value of q ≈ 1.33 for longer ones. The results are discussed from the point of view of superstatistics introduced by Beck [Contin Mech Thermodyn 16(3):293-304, 2004] and connects the q values with the system's degrees of freedom. Our work indicates that the converged (maximum) value is q = 1.33 and is related to 5 degrees of freedom.

Notes on SAW Tag Interrogation Techniques

NASA Technical Reports Server (NTRS)

Barton, Richard J.

2010-01-01

We consider the problem of interrogating a single SAW RFID tag with a known ID and known range in the presence of multiple interfering tags under the following assumptions: (1) The RF propagation environment is well approximated as a simple delay channel with geometric power-decay constant alpha >/= 2. (2) The interfering tag IDs are unknown but well approximated as independent, identically distributed random samples from a probability distribution of tag ID waveforms with known second-order properties, and the tag of interest is drawn independently from the same distribution. (3) The ranges of the interfering tags are unknown but well approximated as independent, identically distributed realizations of a random variable rho with a known probability distribution f(sub rho) , and the tag ranges are independent of the tag ID waveforms. In particular, we model the tag waveforms as random impulse responses from a wide-sense-stationary, uncorrelated-scattering (WSSUS) fading channel with known bandwidth and scattering function. A brief discussion of the properties of such channels and the notation used to describe them in this document is given in the Appendix. Under these assumptions, we derive the expression for the output signal-to-noise ratio (SNR) for an arbitrary combination of transmitted interrogation signal and linear receiver filter. Based on this expression, we derive the optimal interrogator configuration (i.e., transmitted signal/receiver filter combination) in the two extreme noise/interference regimes, i.e., noise-limited and interference-limited, under the additional assumption that the coherence bandwidth of the tags is much smaller than the total tag bandwidth. Finally, we evaluate the performance of both optimal interrogators over a broad range of operating scenarios using both numerical simulation based on the assumed model and Monte Carlo simulation based on a small sample of measured tag waveforms. The performance evaluation results not only provide guidelines for proper interrogator design, but also provide some insight on the validity of the assumed signal model. It should be noted that the assumption that the impulse response of the tag of interest is known precisely implies that the temperature and range of the tag are also known precisely, which is generally not the case in practice. However, analyzing interrogator performance under this simplifying assumption is much more straightforward and still provides a great deal of insight into the nature of the problem.

Estimates of the information content and dimensionality of natural scenes from proximity distributions

NASA Astrophysics Data System (ADS)

Chandler, Damon M.; Field, David J.

2007-04-01

Natural scenes, like most all natural data sets, show considerable redundancy. Although many forms of redundancy have been investigated (e.g., pixel distributions, power spectra, contour relationships, etc.), estimates of the true entropy of natural scenes have been largely considered intractable. We describe a technique for estimating the entropy and relative dimensionality of image patches based on a function we call the proximity distribution (a nearest-neighbor technique). The advantage of this function over simple statistics such as the power spectrum is that the proximity distribution is dependent on all forms of redundancy. We demonstrate that this function can be used to estimate the entropy (redundancy) of 3×3 patches of known entropy as well as 8×8 patches of Gaussian white noise, natural scenes, and noise with the same power spectrum as natural scenes. The techniques are based on assumptions regarding the intrinsic dimensionality of the data, and although the estimates depend on an extrapolation model for images larger than 3×3, we argue that this approach provides the best current estimates of the entropy and compressibility of natural-scene patches and that it provides insights into the efficiency of any coding strategy that aims to reduce redundancy. We show that the sample of 8×8 patches of natural scenes used in this study has less than half the entropy of 8×8 white noise and less than 60% of the entropy of noise with the same power spectrum. In addition, given a finite number of samples (<220) drawn randomly from the space of 8×8 patches, the subspace of 8×8 natural-scene patches shows a dimensionality that depends on the sampling density and that for low densities is significantly lower dimensional than the space of 8×8 patches of white noise and noise with the same power spectrum.

The incidence of the different sources of noise on the uncertainty in radiochromic film dosimetry using single channel and multichannel methods

NASA Astrophysics Data System (ADS)

González-López, Antonio; Vera-Sánchez, Juan Antonio; Ruiz-Morales, Carmen

2017-11-01

The influence of the various sources of noise on the uncertainty in radiochromic film (RCF) dosimetry using single channel and multichannel methods is investigated in this work. These sources of noise are extracted from pixel value (PV) readings and dose maps. Pieces of an RCF were each irradiated to different uniform doses, ranging from 0 to 1092 cGy. Then, the pieces were read at two resolutions (72 and 150 ppp) with two flatbed scanners: Epson 10000XL and Epson V800, representing two states of technology. Noise was extracted as described in ISO 15739 (2013), separating its distinct constituents: random noise and fixed pattern (FP) noise. Regarding the PV maps, FP noise is the main source of noise for both models of digitizer. Also, the standard deviation of the random noise in the 10000XL model is almost twice that of the V800 model. In the dose maps, the FP noise is smaller in the multichannel method than in the single channel ones. However, random noise is higher in this method, throughout the dose range. In the multichannel method, FP noise is reduced, as a consequence of this method’s ability to eliminate channel independent perturbations. However, the random noise increases, because the dose is calculated as a linear combination of the doses obtained by the single channel methods. The values of the coefficients of this linear combination are obtained in the present study, and the root of the sum of their squares is shown to range between 0.9 and 1.9 over the dose range studied. These results indicate the random noise to play a fundamental role in the uncertainty of RCF dosimetry: low levels of random noise are required in the digitizer to fully exploit the advantages of the multichannel dosimetry method. This is particularly important for measuring high doses at high spatial resolutions.

Efficient bias correction for magnetic resonance image denoising.

PubMed

Mukherjee, Partha Sarathi; Qiu, Peihua

2013-05-30

Magnetic resonance imaging (MRI) is a popular radiology technique that is used for visualizing detailed internal structure of the body. Observed MRI images are generated by the inverse Fourier transformation from received frequency signals of a magnetic resonance scanner system. Previous research has demonstrated that random noise involved in the observed MRI images can be described adequately by the so-called Rician noise model. Under that model, the observed image intensity at a given pixel is a nonlinear function of the true image intensity and of two independent zero-mean random variables with the same normal distribution. Because of such a complicated noise structure in the observed MRI images, denoised images by conventional denoising methods are usually biased, and the bias could reduce image contrast and negatively affect subsequent image analysis. Therefore, it is important to address the bias issue properly. To this end, several bias-correction procedures have been proposed in the literature. In this paper, we study the Rician noise model and the corresponding bias-correction problem systematically and propose a new and more effective bias-correction formula based on the regression analysis and Monte Carlo simulation. Numerical studies show that our proposed method works well in various applications. Copyright © 2012 John Wiley & Sons, Ltd.

Inversion of particle-size distribution from angular light-scattering data with genetic algorithms.

PubMed

Ye, M; Wang, S; Lu, Y; Hu, T; Zhu, Z; Xu, Y

1999-04-20

A stochastic inverse technique based on a genetic algorithm (GA) to invert particle-size distribution from angular light-scattering data is developed. This inverse technique is independent of any given a priori information of particle-size distribution. Numerical tests show that this technique can be successfully applied to inverse problems with high stability in the presence of random noise and low susceptibility to the shape of distributions. It has also been shown that the GA-based inverse technique is more efficient in use of computing time than the inverse Monte Carlo method recently developed by Ligon et al. [Appl. Opt. 35, 4297 (1996)].

Noisy oscillator: Random mass and random damping.

PubMed

Burov, Stanislav; Gitterman, Moshe

2016-11-01

The problem of a linear damped noisy oscillator is treated in the presence of two multiplicative sources of noise which imply a random mass and random damping. The additive noise and the noise in the damping are responsible for an influx of energy to the oscillator and its dissipation to the surrounding environment. A random mass implies that the surrounding molecules not only collide with the oscillator but may also adhere to it, thereby changing its mass. We present general formulas for the first two moments and address the question of mean and energetic stabilities. The phenomenon of stochastic resonance, i.e., the expansion due to the noise of a system response to an external periodic signal, is considered for separate and joint action of two sources of noise and their characteristics.

Random walk in nonhomogeneous environments: A possible approach to human and animal mobility

NASA Astrophysics Data System (ADS)

Srokowski, Tomasz

2017-03-01

The random walk process in a nonhomogeneous medium, characterized by a Lévy stable distribution of jump length, is discussed. The width depends on a position: either before the jump or after that. In the latter case, the density slope is affected by the variable width and the variance may be finite; then all kinds of the anomalous diffusion are predicted. In the former case, only the time characteristics are sensitive to the variable width. The corresponding Langevin equation with different interpretations of the multiplicative noise is discussed. The dependence of the distribution width on position after jump is interpreted in terms of cognitive abilities and related to such problems as migration in a human population and foraging habits of animals.

Quantitative analysis of random ameboid motion

NASA Astrophysics Data System (ADS)

Bödeker, H. U.; Beta, C.; Frank, T. D.; Bodenschatz, E.

2010-04-01

We quantify random migration of the social ameba Dictyostelium discoideum. We demonstrate that the statistics of cell motion can be described by an underlying Langevin-type stochastic differential equation. An analytic expression for the velocity distribution function is derived. The separation into deterministic and stochastic parts of the movement shows that the cells undergo a damped motion with multiplicative noise. Both contributions to the dynamics display a distinct response to external physiological stimuli. The deterministic component depends on the developmental state and ambient levels of signaling substances, while the stochastic part does not.

Distributed Noise Generation for Density Estimation Based Clustering without Trusted Third Party

NASA Astrophysics Data System (ADS)

Su, Chunhua; Bao, Feng; Zhou, Jianying; Takagi, Tsuyoshi; Sakurai, Kouichi

The rapid growth of the Internet provides people with tremendous opportunities for data collection, knowledge discovery and cooperative computation. However, it also brings the problem of sensitive information leakage. Both individuals and enterprises may suffer from the massive data collection and the information retrieval by distrusted parties. In this paper, we propose a privacy-preserving protocol for the distributed kernel density estimation-based clustering. Our scheme applies random data perturbation (RDP) technique and the verifiable secret sharing to solve the security problem of distributed kernel density estimation in [4] which assumed a mediate party to help in the computation.

Speckle lithography for fabricating Gaussian, quasi-random 2D structures and black silicon structures.

PubMed

Bingi, Jayachandra; Murukeshan, Vadakke Matham

2015-12-18

Laser speckle pattern is a granular structure formed due to random coherent wavelet interference and generally considered as noise in optical systems including photolithography. Contrary to this, in this paper, we use the speckle pattern to generate predictable and controlled Gaussian random structures and quasi-random structures photo-lithographically. The random structures made using this proposed speckle lithography technique are quantified based on speckle statistics, radial distribution function (RDF) and fast Fourier transform (FFT). The control over the speckle size, density and speckle clustering facilitates the successful fabrication of black silicon with different surface structures. The controllability and tunability of randomness makes this technique a robust method for fabricating predictable 2D Gaussian random structures and black silicon structures. These structures can enhance the light trapping significantly in solar cells and hence enable improved energy harvesting. Further, this technique can enable efficient fabrication of disordered photonic structures and random media based devices.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smallwood, D.O.

It is recognized that some dynamic and noise environments are characterized by time histories which are not Gaussian. An example is high intensity acoustic noise. Another example is some transportation vibration. A better simulation of these environments can be generated if a zero mean non-Gaussian time history can be reproduced with a specified auto (or power) spectral density (ASD or PSD) and a specified probability density function (pdf). After the required time history is synthesized, the waveform can be used for simulation purposes. For example, modem waveform reproduction techniques can be used to reproduce the waveform on electrodynamic or electrohydraulicmore » shakers. Or the waveforms can be used in digital simulations. A method is presented for the generation of realizations of zero mean non-Gaussian random time histories with a specified ASD, and pdf. First a Gaussian time history with the specified auto (or power) spectral density (ASD) is generated. A monotonic nonlinear function relating the Gaussian waveform to the desired realization is then established based on the Cumulative Distribution Function (CDF) of the desired waveform and the known CDF of a Gaussian waveform. The established function is used to transform the Gaussian waveform to a realization of the desired waveform. Since the transformation preserves the zero-crossings and peaks of the original Gaussian waveform, and does not introduce any substantial discontinuities, the ASD is not substantially changed. Several methods are available to generate a realization of a Gaussian distributed waveform with a known ASD. The method of Smallwood and Paez (1993) is an example. However, the generation of random noise with a specified ASD but with a non-Gaussian distribution is less well known.« less

Consumers don’t play dice, influence of social networks and advertisements

NASA Astrophysics Data System (ADS)

Groot, Robert D.

2006-05-01

Empirical data of supermarket sales show stylised facts that are similar to stock markets, with a broad (truncated) Lévy distribution of weekly sales differences in the baseline sales [R.D. Groot, Physica A 353 (2005) 501]. To investigate the cause of this, the influence of social interactions and advertisements are studied in an agent-based model of consumers in a social network. The influence of network topology was varied by using a small-world network, a random network and a Barabási-Albert network. The degree to which consumers value the opinion of their peers was also varied. On a small-world and random network we find a phase transition between an open market and a locked-in market that is similar to condensation in liquids. At the critical point, fluctuations become large and buying behaviour is strongly correlated. However, on the small world network the noise distribution at the critical point is Gaussian, and critical slowing down occurs which is not observed in supermarket sales. On a scale-free network, the model shows a transition between a gas-like phase and a glassy state, but at the transition point the noise amplitude is much larger than what is seen in supermarket sales. To explore the role of advertisements, a model is studied where imprints are placed on the minds of consumers that ripen when a decision for a product is made. The correct distribution of weekly sales returns follows naturally from this model, as well as the noise amplitude, the correlation time and cross-correlation of sales fluctuations. For particular parameter values, simulated sales correlation shows power-law decay in time. The model predicts that social interaction helps to prevent aversion, and that products are viewed more positively when their consumption rate is higher.

The development and validation of the Closed-set Mandarin Sentence (CMS) test.

PubMed

Tao, Duo-Duo; Fu, Qian-Jie; Galvin, John J; Yu, Ya-Feng

2017-09-01

Matrix-styled sentence tests offer a closed-set paradigm that may be useful when evaluating speech intelligibility. Ideally, sentence test materials should reflect the distribution of phonemes within the target language. We developed and validated the Closed-set Mandarin Sentence (CMS) test to assess Mandarin speech intelligibility in noise. CMS test materials were selected to be familiar words and to represent the natural distribution of vowels, consonants, and lexical tones found in Mandarin Chinese. Ten key words in each of five categories (Name, Verb, Number, Color, and Fruit) were produced by a native Mandarin talker, resulting in a total of 50 words that could be combined to produce 100,000 unique sentences. Normative data were collected in 10 normal-hearing, adult Mandarin-speaking Chinese listeners using a closed-set test paradigm. Two test runs were conducted for each subject, and 20 sentences per run were randomly generated while ensuring that each word was presented only twice in each run. First, the level of the words in each category were adjusted to produce equal intelligibility in noise. Test-retest reliability for word-in-sentence recognition was excellent according to Cronbach's alpha (0.952). After the category level adjustments, speech reception thresholds (SRTs) for sentences in noise, defined as the signal-to-noise ratio (SNR) that produced 50% correct whole sentence recognition, were adaptively measured by adjusting the SNR according to the correctness of response. The mean SRT was -7.9 (SE=0.41) and -8.1 (SE=0.34) dB for runs 1 and 2, respectively. The mean standard deviation across runs was 0.93 dB, and paired t-tests showed no significant difference between runs 1 and 2 (p=0.74) despite random sentences being generated for each run and each subject. The results suggest that the CMS provides large stimulus set with which to repeatedly and reliably measure Mandarin-speaking listeners' speech understanding in noise using a closed-set paradigm.

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

PubMed

Glynn, C C; Konstantinou, K I

2016-11-24

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

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

PubMed Central

Glynn, C. C.; Konstantinou, K. I.

2016-01-01

Ambient seismic noise is characterized by randomness incurred by the random position and strength of the noise sources as well as the heterogeneous properties of the medium through which it propagates. Here we use ambient noise data recorded prior to the 1996 Gjálp eruption in Iceland in order to show that a reduction of noise randomness can be a clear short-term precursor to volcanic activity. The eruption was preceded on 29 September 1996 by a Mw ~5.6 earthquake that occurred in the caldera rim of the Bárdarbunga volcano. A significant reduction of randomness started occurring 8 days before the earthquake and 10 days before the onset of the eruption. This reduction was observed even at stations more than 100 km away from the eruption site. Randomness increased to its previous levels 160 minutes after the Bárdarbunga earthquake, during which time aftershocks migrated from the Bárdarbunga caldera to a site near the Gjálp eruption fissure. We attribute this precursory reduction of randomness to the lack of higher frequencies (>1 Hz) in the noise wavefield caused by high absorption losses as hot magma ascended in the upper crust. PMID:27883050

Role of streams in myxobacteria aggregate formation

NASA Astrophysics Data System (ADS)

Kiskowski, Maria A.; Jiang, Yi; Alber, Mark S.

2004-10-01

Cell contact, movement and directionality are important factors in biological development (morphogenesis), and myxobacteria are a model system for studying cell-cell interaction and cell organization preceding differentiation. When starved, thousands of myxobacteria cells align, stream and form aggregates which later develop into round, non-motile spores. Canonically, cell aggregation has been attributed to attractive chemotaxis, a long range interaction, but there is growing evidence that myxobacteria organization depends on contact-mediated cell-cell communication. We present a discrete stochastic model based on contact-mediated signaling that suggests an explanation for the initialization of early aggregates, aggregation dynamics and final aggregate distribution. Our model qualitatively reproduces the unique structures of myxobacteria aggregates and detailed stages which occur during myxobacteria aggregation: first, aggregates initialize in random positions and cells join aggregates by random walk; second, cells redistribute by moving within transient streams connecting aggregates. Streams play a critical role in final aggregate size distribution by redistributing cells among fewer, larger aggregates. The mechanism by which streams redistribute cells depends on aggregate sizes and is enhanced by noise. Our model predicts that with increased internal noise, more streams would form and streams would last longer. Simulation results suggest a series of new experiments.

Bayesian microsaccade detection

PubMed Central

Mihali, Andra; van Opheusden, Bas; Ma, Wei Ji

2017-01-01

Microsaccades are high-velocity fixational eye movements, with special roles in perception and cognition. The default microsaccade detection method is to determine when the smoothed eye velocity exceeds a threshold. We have developed a new method, Bayesian microsaccade detection (BMD), which performs inference based on a simple statistical model of eye positions. In this model, a hidden state variable changes between drift and microsaccade states at random times. The eye position is a biased random walk with different velocity distributions for each state. BMD generates samples from the posterior probability distribution over the eye state time series given the eye position time series. Applied to simulated data, BMD recovers the “true” microsaccades with fewer errors than alternative algorithms, especially at high noise. Applied to EyeLink eye tracker data, BMD detects almost all the microsaccades detected by the default method, but also apparent microsaccades embedded in high noise—although these can also be interpreted as false positives. Next we apply the algorithms to data collected with a Dual Purkinje Image eye tracker, whose higher precision justifies defining the inferred microsaccades as ground truth. When we add artificial measurement noise, the inferences of all algorithms degrade; however, at noise levels comparable to EyeLink data, BMD recovers the “true” microsaccades with 54% fewer errors than the default algorithm. Though unsuitable for online detection, BMD has other advantages: It returns probabilities rather than binary judgments, and it can be straightforwardly adapted as the generative model is refined. We make our algorithm available as a software package. PMID:28114483

Characterization and simulation of noise in PET images reconstructed with OSEM: Development of a method for the generation of synthetic images.

PubMed

Castro, P; Huerga, C; Chamorro, P; Garayoa, J; Roch, M; Pérez, L

2018-04-17

The goals of the study are to characterize imaging properties in 2D PET images reconstructed with the iterative algorithm ordered-subset expectation maximization (OSEM) and to propose a new method for the generation of synthetic images. The noise is analyzed in terms of its magnitude, spatial correlation, and spectral distribution through standard deviation, autocorrelation function, and noise power spectrum (NPS), respectively. Their variations with position and activity level are also analyzed. This noise analysis is based on phantom images acquired from 18 F uniform distributions. Experimental recovery coefficients of hot spheres in different backgrounds are employed to study the spatial resolution of the system through point spread function (PSF). The NPS and PSF functions provide the baseline for the proposed simulation method: convolution with PSF as kernel and noise addition from NPS. The noise spectral analysis shows that the main contribution is of random nature. It is also proven that attenuation correction does not alter noise texture but it modifies its magnitude. Finally, synthetic images of 2 phantoms, one of them an anatomical brain, are quantitatively compared with experimental images showing a good agreement in terms of pixel values and pixel correlations. Thus, the contrast to noise ratio for the biggest sphere in the NEMA IEC phantom is 10.7 for the synthetic image and 8.8 for the experimental image. The properties of the analyzed OSEM-PET images can be described by NPS and PSF functions. Synthetic images, even anatomical ones, are successfully generated by the proposed method based on the NPS and PSF. Copyright © 2018 Sociedad Española de Medicina Nuclear e Imagen Molecular. Publicado por Elsevier España, S.L.U. All rights reserved.

Measurement and Analysis of the Noise Radiated by Low Mach Number Centrifugal Blowers.

NASA Astrophysics Data System (ADS)

Yeager, David Marvin

An investigation was performed of the broad band, aerodynamically generated noise in low tip-speed Mach number, centrifugal air moving devices. An interdisciplinary experimental approach was taken which involved investigation of the aerodynamic and acoustic fields, and their mutual relationship. The noise generation process was studied using two experimental vehicles: (1) a scale model of a homologous family of centrifugal blowers typical of those used to cool computer and business equipment, and (2) a single blade from a centrifugal blower impeller placed in a known, controllable flow field. The radiation characteristics of the model blower were investigated by measuring the acoustic intensity distribution near the blower inlet and comparing it with the intensity near the inlet to an axial flow fan. Results showed that the centrifugal blower is a distributed, random noise source, unlike an axial fan which exhibited the effects of a coherent, interacting source distribution. Aerodynamic studies of the flow field in the inlet and at the discharge to the rotating impeller were used to assess the mean flow distribution through the impeller blade channels and to identify regions of excessive turbulence near the rotating blade row. Both circumferential and spanwise mean flow nonuniformities were identified along with a region of increased turbulence just downstream of the scroll cutoff. The fluid incidence angle, normally taken as an indicator of blower performance, was estimated from mean flow data as deviating considerably from an ideal impeller design. An investigation of the noise radiated from the single, isolated airfoil was performed using modern correlation and spectral analysis techniques. Radiation from the single blade in flow was characterized using newly developed expressions for the correlation area and the dipole source strength per unit area, and from the relationship between the blade surface pressure and the incident turbulent flow field. Results showed that radiation from the single blade was dominated by the effects of the incident turbulence. Normalized correlations areas of approximately 25% were measured at low frequencies. While the noise generation was more efficient at the trailing edge of the isolated blade, more noise was radiated from the region near the leading edge.

Removal of Stationary Sinusoidal Noise from Random Vibration Signals.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Brian; Cap, Jerome S.

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

Evaluation of a multi-point method for determining acoustic impedance

NASA Technical Reports Server (NTRS)

Jones, Michael G.; Parrott, Tony L.

1988-01-01

An investigation was conducted to explore potential improvements provided by a Multi-Point Method (MPM) over the Standing Wave Method (SWM) and Two-Microphone Method (TMM) for determining acoustic impedance. A wave propagation model was developed to model the standing wave pattern in an impedance tube. The acoustic impedance of a test specimen was calculated from a best fit of this standing wave pattern to pressure measurements obtained along the impedance tube centerline. Three measurement spacing distributions were examined: uniform, random, and selective. Calculated standing wave patterns match the point pressure measurement distributions with good agreement for a reflection factor magnitude range of 0.004 to 0.999. Comparisons of results using 2, 3, 6, and 18 measurement points showed that the most consistent results are obtained when using at least 6 evenly spaced pressure measurements per half-wavelength. Also, data were acquired with broadband noise added to the discrete frequency noise and impedances were calculated using the MPM and TMM algorithms. The results indicate that the MPM will be superior to the TMM in the presence of significant broadband noise levels associated with mean flow.

Free-Space Quantum Communication with a Portable Quantum Memory

NASA Astrophysics Data System (ADS)

Namazi, Mehdi; Vallone, Giuseppe; Jordaan, Bertus; Goham, Connor; Shahrokhshahi, Reihaneh; Villoresi, Paolo; Figueroa, Eden

2017-12-01

The realization of an elementary quantum network that is intrinsically secure and operates over long distances requires the interconnection of several quantum modules performing different tasks. In this work, we report the realization of a communication network functioning in a quantum regime, consisting of four different quantum modules: (i) a random polarization qubit generator, (ii) a free-space quantum-communication channel, (iii) an ultralow-noise portable quantum memory, and (iv) a qubit decoder, in a functional elementary quantum network possessing all capabilities needed for quantum-information distribution protocols. We create weak coherent pulses at the single-photon level encoding polarization states |H ⟩ , |V ⟩, |D ⟩, and |A ⟩ in a randomized sequence. The random qubits are sent over a free-space link and coupled into a dual-rail room-temperature quantum memory and after storage and retrieval are analyzed in a four-detector polarization analysis akin to the requirements of the BB84 protocol. We also show ultralow noise and fully portable operation, paving the way towards memory-assisted all-environment free-space quantum cryptographic networks.

Brain MR image segmentation based on an improved active contour model

PubMed Central

Meng, Xiangrui; Gu, Wenya; Zhang, Jianwei

2017-01-01

It is often a difficult task to accurately segment brain magnetic resonance (MR) images with intensity in-homogeneity and noise. This paper introduces a novel level set method for simultaneous brain MR image segmentation and intensity inhomogeneity correction. To reduce the effect of noise, novel anisotropic spatial information, which can preserve more details of edges and corners, is proposed by incorporating the inner relationships among the neighbor pixels. Then the proposed energy function uses the multivariate Student's t-distribution to fit the distribution of the intensities of each tissue. Furthermore, the proposed model utilizes Hidden Markov random fields to model the spatial correlation between neigh-boring pixels/voxels. The means of the multivariate Student's t-distribution can be adaptively estimated by multiplying a bias field to reduce the effect of intensity inhomogeneity. In the end, we reconstructed the energy function to be convex and calculated it by using the Split Bregman method, which allows our framework for random initialization, thereby allowing fully automated applications. Our method can obtain the final result in less than 1 second for 2D image with size 256 × 256 and less than 300 seconds for 3D image with size 256 × 256 × 171. The proposed method was compared to other state-of-the-art segmentation methods using both synthetic and clinical brain MR images and increased the accuracies of the results more than 3%. PMID:28854235

False Operation of Static Random Access Memory Cells under Alternating Current Power Supply Voltage Variation

NASA Astrophysics Data System (ADS)

Sawada, Takuya; Takata, Hidehiro; Nii, Koji; Nagata, Makoto

2013-04-01

Static random access memory (SRAM) cores exhibit susceptibility against power supply voltage variation. False operation is investigated among SRAM cells under sinusoidal voltage variation on power lines introduced by direct RF power injection. A standard SRAM core of 16 kbyte in a 90 nm 1.5 V technology is diagnosed with built-in self test and on-die noise monitor techniques. The sensitivity of bit error rate is shown to be high against the frequency of injected voltage variation, while it is not greatly influenced by the difference in frequency and phase against SRAM clocking. It is also observed that the distribution of false bits is substantially random in a cell array.

Enzymatic AND logic gates operated under conditions characteristic of biomedical applications.

PubMed

Melnikov, Dmitriy; Strack, Guinevere; Zhou, Jian; Windmiller, Joshua Ray; Halámek, Jan; Bocharova, Vera; Chuang, Min-Chieh; Santhosh, Padmanabhan; Privman, Vladimir; Wang, Joseph; Katz, Evgeny

2010-09-23

Experimental and theoretical analyses of the lactate dehydrogenase and glutathione reductase based enzymatic AND logic gates in which the enzymes and their substrates serve as logic inputs are performed. These two systems are examples of the novel, previously unexplored class of biochemical logic gates that illustrate potential biomedical applications of biochemical logic. They are characterized by input concentrations at logic 0 and 1 states corresponding to normal and pathophysiological conditions. Our analysis shows that the logic gates under investigation have similar noise characteristics. Both significantly amplify random noise present in inputs; however, we establish that for realistic widths of the input noise distributions, it is still possible to differentiate between the logic 0 and 1 states of the output. This indicates that reliable detection of pathophysiological conditions is indeed possible with such enzyme logic systems.

State Estimation Using Dependent Evidence Fusion: Application to Acoustic Resonance-Based Liquid Level Measurement.

PubMed

Xu, Xiaobin; Li, Zhenghui; Li, Guo; Zhou, Zhe

2017-04-21

Estimating the state of a dynamic system via noisy sensor measurement is a common problem in sensor methods and applications. Most state estimation methods assume that measurement noise and state perturbations can be modeled as random variables with known statistical properties. However in some practical applications, engineers can only get the range of noises, instead of the precise statistical distributions. Hence, in the framework of Dempster-Shafer (DS) evidence theory, a novel state estimatation method by fusing dependent evidence generated from state equation, observation equation and the actual observations of the system states considering bounded noises is presented. It can be iteratively implemented to provide state estimation values calculated from fusion results at every time step. Finally, the proposed method is applied to a low-frequency acoustic resonance level gauge to obtain high-accuracy measurement results.

Memory effects on a resonate-and-fire neuron model subjected to Ornstein-Uhlenbeck noise

NASA Astrophysics Data System (ADS)

Paekivi, S.; Mankin, R.; Rekker, A.

2017-10-01

We consider a generalized Langevin equation with an exponentially decaying memory kernel as a model for the firing process of a resonate-and-fire neuron. The effect of temporally correlated random neuronal input is modeled as Ornstein-Uhlenbeck noise. In the noise-induced spiking regime of the neuron, we derive exact analytical formulas for the dependence of some statistical characteristics of the output spike train, such as the probability distribution of the interspike intervals (ISIs) and the survival probability, on the parameters of the input stimulus. Particularly, on the basis of these exact expressions, we have established sufficient conditions for the occurrence of memory-time-induced transitions between unimodal and multimodal structures of the ISI density and a critical damping coefficient which marks a dynamical transition in the behavior of the system.

SER Analysis of MPPM-Coded MIMO-FSO System over Uncorrelated and Correlated Gamma-Gamma Atmospheric Turbulence Channels

NASA Astrophysics Data System (ADS)

Khallaf, Haitham S.; Garrido-Balsells, José M.; Shalaby, Hossam M. H.; Sampei, Seiichi

2015-12-01

The performance of multiple-input multiple-output free space optical (MIMO-FSO) communication systems, that adopt multipulse pulse position modulation (MPPM) techniques, is analyzed. Both exact and approximate symbol-error rates (SERs) are derived for both cases of uncorrelated and correlated channels. The effects of background noise, receiver shot-noise, and atmospheric turbulence are taken into consideration in our analysis. The random fluctuations of the received optical irradiance, produced by the atmospheric turbulence, is modeled by the widely used gamma-gamma statistical distribution. Uncorrelated MIMO channels are modeled by the α-μ distribution. A closed-form expression for the probability density function of the optical received irradiance is derived for the case of correlated MIMO channels. Using our analytical expressions, the degradation of the system performance with the increment of the correlation coefficients between MIMO channels is corroborated.

Multifractal analysis of visibility graph-based Ito-related connectivity time series.

PubMed

Czechowski, Zbigniew; Lovallo, Michele; Telesca, Luciano

2016-02-01

In this study, we investigate multifractal properties of connectivity time series resulting from the visibility graph applied to normally distributed time series generated by the Ito equations with multiplicative power-law noise. We show that multifractality of the connectivity time series (i.e., the series of numbers of links outgoing any node) increases with the exponent of the power-law noise. The multifractality of the connectivity time series could be due to the width of connectivity degree distribution that can be related to the exit time of the associated Ito time series. Furthermore, the connectivity time series are characterized by persistence, although the original Ito time series are random; this is due to the procedure of visibility graph that, connecting the values of the time series, generates persistence but destroys most of the nonlinear correlations. Moreover, the visibility graph is sensitive for detecting wide "depressions" in input time series.

Physical-layer security analysis of a quantum-noise randomized cipher based on the wire-tap channel model.

PubMed

Jiao, Haisong; Pu, Tao; Zheng, Jilin; Xiang, Peng; Fang, Tao

2017-05-15

The physical-layer security of a quantum-noise randomized cipher (QNRC) system is, for the first time, quantitatively evaluated with secrecy capacity employed as the performance metric. Considering quantum noise as a channel advantage for legitimate parties over eavesdroppers, the specific wire-tap models for both channels of the key and data are built with channel outputs yielded by quantum heterodyne measurement; the general expressions of secrecy capacities for both channels are derived, where the matching codes are proved to be uniformly distributed. The maximal achievable secrecy rate of the system is proposed, under which secrecy of both the key and data is guaranteed. The influences of various system parameters on secrecy capacities are assessed in detail. The results indicate that QNRC combined with proper channel codes is a promising framework of secure communication for long distance with high speed, which can be orders of magnitude higher than the perfect secrecy rates of other encryption systems. Even if the eavesdropper intercepts more signal power than the legitimate receiver, secure communication (up to Gb/s) can still be achievable. Moreover, the secrecy of running key is found to be the main constraint to the systemic maximal secrecy rate.

Accuracy of maximum likelihood and least-squares estimates in the lidar slope method with noisy data.

PubMed

Eberhard, Wynn L

2017-04-01

The maximum likelihood estimator (MLE) is derived for retrieving the extinction coefficient and zero-range intercept in the lidar slope method in the presence of random and independent Gaussian noise. Least-squares fitting, weighted by the inverse of the noise variance, is equivalent to the MLE. Monte Carlo simulations demonstrate that two traditional least-squares fitting schemes, which use different weights, are less accurate. Alternative fitting schemes that have some positive attributes are introduced and evaluated. The principal factors governing accuracy of all these schemes are elucidated. Applying these schemes to data with Poisson rather than Gaussian noise alters accuracy little, even when the signal-to-noise ratio is low. Methods to estimate optimum weighting factors in actual data are presented. Even when the weighting estimates are coarse, retrieval accuracy declines only modestly. Mathematical tools are described for predicting retrieval accuracy. Least-squares fitting with inverse variance weighting has optimum accuracy for retrieval of parameters from single-wavelength lidar measurements when noise, errors, and uncertainties are Gaussian distributed, or close to optimum when only approximately Gaussian.

A study of optimal abstract jamming strategies vs. noncoherent MFSK

NASA Technical Reports Server (NTRS)

Mceliece, R. J.; Rodemich, E. R.

1983-01-01

The present investigation is concerned with the performance of uncoded MFSK modulation in the presence of arbitrary additive jamming, taking into account the objective to devise robust antijamming strategies. An abstract model is considered, giving attention to the signal strength as a nonnegative real number X, the employment of X as a random variable, its distribution function G(x), the transmitter's strategy G, the jamming noise as an M-dimensional random vector Z, and the error probability. A summary of previous work on the considered problem is provided, and the results of the current study are presented.

Langevin dynamics for ramified structures

NASA Astrophysics Data System (ADS)

Méndez, Vicenç; Iomin, Alexander; Horsthemke, Werner; Campos, Daniel

2017-06-01

We propose a generalized Langevin formalism to describe transport in combs and similar ramified structures. Our approach consists of a Langevin equation without drift for the motion along the backbone. The motion along the secondary branches may be described either by a Langevin equation or by other types of random processes. The mean square displacement (MSD) along the backbone characterizes the transport through the ramified structure. We derive a general analytical expression for this observable in terms of the probability distribution function of the motion along the secondary branches. We apply our result to various types of motion along the secondary branches of finite or infinite length, such as subdiffusion, superdiffusion, and Langevin dynamics with colored Gaussian noise and with non-Gaussian white noise. Monte Carlo simulations show excellent agreement with the analytical results. The MSD for the case of Gaussian noise is shown to be independent of the noise color. We conclude by generalizing our analytical expression for the MSD to the case where each secondary branch is n dimensional.

Time-dependent solutions for a stochastic model of gene expression with molecule production in the form of a compound Poisson process.

PubMed

Jędrak, Jakub; Ochab-Marcinek, Anna

2016-09-01

We study a stochastic model of gene expression, in which protein production has a form of random bursts whose size distribution is arbitrary, whereas protein decay is a first-order reaction. We find exact analytical expressions for the time evolution of the cumulant-generating function for the most general case when both the burst size probability distribution and the model parameters depend on time in an arbitrary (e.g., oscillatory) manner, and for arbitrary initial conditions. We show that in the case of periodic external activation and constant protein degradation rate, the response of the gene is analogous to the resistor-capacitor low-pass filter, where slow oscillations of the external driving have a greater effect on gene expression than the fast ones. We also demonstrate that the nth cumulant of the protein number distribution depends on the nth moment of the burst size distribution. We use these results to show that different measures of noise (coefficient of variation, Fano factor, fractional change of variance) may vary in time in a different manner. Therefore, any biological hypothesis of evolutionary optimization based on the nonmonotonic dependence of a chosen measure of noise on time must justify why it assumes that biological evolution quantifies noise in that particular way. Finally, we show that not only for exponentially distributed burst sizes but also for a wider class of burst size distributions (e.g., Dirac delta and gamma) the control of gene expression level by burst frequency modulation gives rise to proportional scaling of variance of the protein number distribution to its mean, whereas the control by amplitude modulation implies proportionality of protein number variance to the mean squared.

Stochastic mixed-mode oscillations in a three-species predator-prey model

NASA Astrophysics Data System (ADS)

Sadhu, Susmita; Kuehn, Christian

2018-03-01

The effect of demographic stochasticity, in the form of Gaussian white noise, in a predator-prey model with one fast and two slow variables is studied. We derive the stochastic differential equations (SDEs) from a discrete model. For suitable parameter values, the deterministic drift part of the model admits a folded node singularity and exhibits a singular Hopf bifurcation. We focus on the parameter regime near the Hopf bifurcation, where small amplitude oscillations exist as stable dynamics in the absence of noise. In this regime, the stochastic model admits noise-driven mixed-mode oscillations (MMOs), which capture the intermediate dynamics between two cycles of population outbreaks. We perform numerical simulations to calculate the distribution of the random number of small oscillations between successive spikes for varying noise intensities and distance to the Hopf bifurcation. We also study the effect of noise on a suitable Poincaré map. Finally, we prove that the stochastic model can be transformed into a normal form near the folded node, which can be linked to recent results on the interplay between deterministic and stochastic small amplitude oscillations. The normal form can also be used to study the parameter influence on the noise level near folded singularities.

Convergence Rate Analysis of Distributed Gossip (Linear Parameter) Estimation: Fundamental Limits and Tradeoffs

NASA Astrophysics Data System (ADS)

Kar, Soummya; Moura, José M. F.

2011-08-01

The paper considers gossip distributed estimation of a (static) distributed random field (a.k.a., large scale unknown parameter vector) observed by sparsely interconnected sensors, each of which only observes a small fraction of the field. We consider linear distributed estimators whose structure combines the information \\emph{flow} among sensors (the \\emph{consensus} term resulting from the local gossiping exchange among sensors when they are able to communicate) and the information \\emph{gathering} measured by the sensors (the \\emph{sensing} or \\emph{innovations} term.) This leads to mixed time scale algorithms--one time scale associated with the consensus and the other with the innovations. The paper establishes a distributed observability condition (global observability plus mean connectedness) under which the distributed estimates are consistent and asymptotically normal. We introduce the distributed notion equivalent to the (centralized) Fisher information rate, which is a bound on the mean square error reduction rate of any distributed estimator; we show that under the appropriate modeling and structural network communication conditions (gossip protocol) the distributed gossip estimator attains this distributed Fisher information rate, asymptotically achieving the performance of the optimal centralized estimator. Finally, we study the behavior of the distributed gossip estimator when the measurements fade (noise variance grows) with time; in particular, we consider the maximum rate at which the noise variance can grow and still the distributed estimator being consistent, by showing that, as long as the centralized estimator is consistent, the distributed estimator remains consistent.

Noise Gating Solar Images

NASA Astrophysics Data System (ADS)

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/AIA , SDO/HMI, STEREO/SECCHI, and GOES-R/SUVI) that explore the benefits and limits of the technique.

Spatial clusters of daytime sleepiness and association with nighttime noise levels in a Swiss general population (GeoHypnoLaus).

PubMed

Joost, Stéphane; Haba-Rubio, José; Himsl, Rebecca; Vollenweider, Peter; Preisig, Martin; Waeber, Gérard; Marques-Vidal, Pedro; Heinzer, Raphaël; Guessous, Idris

2018-05-31

Daytime sleepiness is highly prevalent in the general adult population and has been linked to an increased risk of workplace and vehicle accidents, lower professional performance and poorer health. Despite the established relationship between noise and daytime sleepiness, little research has explored the individual-level spatial distribution of noise-related sleep disturbances. We assessed the spatial dependence of daytime sleepiness and tested whether clusters of individuals exhibiting higher daytime sleepiness were characterized by higher nocturnal noise levels than other clusters. Population-based cross-sectional study, in the city of Lausanne, Switzerland. Sleepiness was measured using the Epworth Sleepiness Scale (ESS) for 3697 georeferenced individuals from the CoLaus|PsyCoLaus cohort (period = 2009-2012). We used the sonBASE georeferenced database produced by the Swiss Federal Office for the Environment to characterize nighttime road traffic noise exposure throughout the city. We used the GeoDa software program to calculate the Getis-Ord G i * statistics for unadjusted and adjusted ESS in order to detect spatial clusters of high and low ESS values. Modeled nighttime noise exposure from road and rail traffic was compared across ESS clusters. Daytime sleepiness was not randomly distributed and showed a significant spatial dependence. The median nighttime traffic noise exposure was significantly different across the three ESS Getis cluster classes (p < 0.001). The mean nighttime noise exposure in the high ESS cluster class was 47.6, dB(A) 5.2 dB(A) higher than in low clusters (p < 0.001) and 2.1 dB(A) higher than in the neutral class (p < 0.001). These associations were independent of major potential confounders including body mass index and neighborhood income level. Clusters of higher daytime sleepiness in adults are associated with higher median nighttime noise levels. The identification of these clusters can guide tailored public health interventions. Copyright © 2018 The Authors. Published by Elsevier GmbH.. All rights reserved.

Speckle lithography for fabricating Gaussian, quasi-random 2D structures and black silicon structures

PubMed Central

Bingi, Jayachandra; Murukeshan, Vadakke Matham

2015-01-01

Laser speckle pattern is a granular structure formed due to random coherent wavelet interference and generally considered as noise in optical systems including photolithography. Contrary to this, in this paper, we use the speckle pattern to generate predictable and controlled Gaussian random structures and quasi-random structures photo-lithographically. The random structures made using this proposed speckle lithography technique are quantified based on speckle statistics, radial distribution function (RDF) and fast Fourier transform (FFT). The control over the speckle size, density and speckle clustering facilitates the successful fabrication of black silicon with different surface structures. The controllability and tunability of randomness makes this technique a robust method for fabricating predictable 2D Gaussian random structures and black silicon structures. These structures can enhance the light trapping significantly in solar cells and hence enable improved energy harvesting. Further, this technique can enable efficient fabrication of disordered photonic structures and random media based devices. PMID:26679513

Use of a Linear Paul Trap to Study Random Noise-Induced Beam Degradation in High-Intensity Accelerators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chung, Moses; Gilson, Erik P.; Davidson, Ronald C.

2009-04-10

A random noise-induced beam degradation that can affect intense beam transport over long propagation distances has been experimentally studied by making use of the transverse beam dynamics equivalence between an alternating-gradient (AG) focusing system and a linear Paul trap system. For the present studies, machine imperfections in the quadrupole focusing lattice are considered, which are emulated by adding small random noise on the voltage waveform of the quadrupole electrodes in the Paul trap. It is observed that externally driven noise continuously produces a nonthermal tail of trapped ions, and increases the transverse emittance almost linearly with the duration of themore » noise.« less

An OFDM Receiver with Frequency Domain Diversity Combined Impulsive Noise Canceller for Underwater Network.

PubMed

Saotome, Rie; Hai, Tran Minh; Matsuda, Yasuto; Suzuki, Taisaku; Wada, Tomohisa

2015-01-01

In order to explore marine natural resources using remote robotic sensor or to enable rapid information exchange between ROV (remotely operated vehicles), AUV (autonomous underwater vehicle), divers, and ships, ultrasonic underwater communication systems are used. However, if the communication system is applied to rich living creature marine environment such as shallow sea, it suffers from generated Impulsive Noise so-called Shrimp Noise, which is randomly generated in time domain and seriously degrades communication performance in underwater acoustic network. With the purpose of supporting high performance underwater communication, a robust digital communication method for Impulsive Noise environments is necessary. In this paper, we propose OFDM ultrasonic communication system with diversity receiver. The main feature of the receiver is a newly proposed Frequency Domain Diversity Combined Impulsive Noise Canceller. The OFDM receiver utilizes 20-28 KHz ultrasonic channel and subcarrier spacing of 46.875 Hz (MODE3) and 93.750 Hz (MODE2) OFDM modulations. In addition, the paper shows Impulsive Noise distribution data measured at a fishing port in Okinawa and at a barge in Shizuoka prefectures and then proposed diversity OFDM transceivers architecture and experimental results are described. By the proposed Impulsive Noise Canceller, frame bit error rate has been decreased by 20-30%.

A non-Gaussian option pricing model based on Kaniadakis exponential deformation

NASA Astrophysics Data System (ADS)

Moretto, Enrico; Pasquali, Sara; Trivellato, Barbara

2017-09-01

A way to make financial models effective is by letting them to represent the so called "fat tails", i.e., extreme changes in stock prices that are regarded as almost impossible by the standard Gaussian distribution. In this article, the Kaniadakis deformation of the usual exponential function is used to define a random noise source in the dynamics of price processes capable of capturing such real market phenomena.

Distributed Matrix Completion: Application to Cooperative Positioning in Noisy Environments

DTIC Science & Technology

2013-12-11

positioning, and a gossip version of low-rank approximation were developed. A convex relaxation for positioning in the presence of noise was shown to...of a large data matrix through gossip algorithms. A new algorithm is proposed that amounts to iteratively multiplying a vector by independent random...sparsification of the original matrix and averaging the resulting normalized vectors. This can be viewed as a generalization of gossip algorithms for

Optical noise-free image encryption based on quick response code and high dimension chaotic system in gyrator transform domain

NASA Astrophysics Data System (ADS)

Sui, Liansheng; Xu, Minjie; Tian, Ailing

2017-04-01

A novel optical image encryption scheme is proposed based on quick response code and high dimension chaotic system, where only the intensity distribution of encoded information is recorded as ciphertext. Initially, the quick response code is engendered from the plain image and placed in the input plane of the double random phase encoding architecture. Then, the code is encrypted to the ciphertext with noise-like distribution by using two cascaded gyrator transforms. In the process of encryption, the parameters such as rotation angles and random phase masks are generated as interim variables and functions based on Chen system. A new phase retrieval algorithm is designed to reconstruct the initial quick response code in the process of decryption, in which a priori information such as three position detection patterns is used as the support constraint. The original image can be obtained without any energy loss by scanning the decrypted code with mobile devices. The ciphertext image is the real-valued function which is more convenient for storing and transmitting. Meanwhile, the security of the proposed scheme is enhanced greatly due to high sensitivity of initial values of Chen system. Extensive cryptanalysis and simulation have performed to demonstrate the feasibility and effectiveness of the proposed scheme.

The Fluctuation-Dissipation Theorem of Colloidal Particle's energy on 2D Periodic Substrates: A Monte Carlo Study of thermal noise-like fluctuation and diffusion like Brownian motion

NASA Astrophysics Data System (ADS)

Najafi, Amin

2014-05-01

Using the Monte Carlo simulations, we have calculated mean-square fluctuations in statistical mechanics, such as those for colloids energy configuration are set on square 2D periodic substrates interacting via a long range screened Coulomb potential on any specific and fixed substrate. Random fluctuations with small deviations from the state of thermodynamic equilibrium arise from the granular structure of them and appear as thermal diffusion with Gaussian distribution structure as well. The variations are showing linear form of the Fluctuation-Dissipation Theorem on the energy of particles constitutive a canonical ensemble with continuous diffusion process of colloidal particle systems. The noise-like variation of the energy per particle and the order parameter versus the Brownian displacement of sum of large number of random steps of particles at low temperatures phase are presenting a markovian process on colloidal particles configuration, too.

Impacts of regular and random noise on the behaviour, growth and development of larval Atlantic cod (Gadus morhua)

PubMed Central

Nedelec, Sophie L.; Simpson, Stephen D.; Morley, Erica L.; Nedelec, Brendan; Radford, Andrew N.

2015-01-01

Anthropogenic noise impacts behaviour and physiology in many species, but responses could change with repeat exposures. As repeat exposures can vary in regularity, identifying regimes with less impact is important for regulation. We use a 16-day split-brood experiment to compare effects of regular and random acoustic noise (playbacks of recordings of ships), relative to ambient-noise controls, on behaviour, growth and development of larval Atlantic cod (Gadus morhua). Short-term noise caused startle responses in newly hatched fish, irrespective of rearing noise. Two days of both regular and random noise regimes reduced growth, while regular noise led to faster yolk sac use. After 16 days, growth in all three sound treatments converged, although fish exposed to regular noise had lower body width–length ratios. Larvae with lower body width–length ratios were easier to catch in a predator-avoidance experiment. Our results demonstrate that the timing of acoustic disturbances can impact survival-related measures during development. Much current work focuses on sound levels, but future studies should consider the role of noise regularity and its importance for noise management and mitigation measures. PMID:26468248

Impacts of regular and random noise on the behaviour, growth and development of larval Atlantic cod (Gadus morhua).

PubMed

Nedelec, Sophie L; Simpson, Stephen D; Morley, Erica L; Nedelec, Brendan; Radford, Andrew N

2015-10-22

Anthropogenic noise impacts behaviour and physiology in many species, but responses could change with repeat exposures. As repeat exposures can vary in regularity, identifying regimes with less impact is important for regulation. We use a 16-day split-brood experiment to compare effects of regular and random acoustic noise (playbacks of recordings of ships), relative to ambient-noise controls, on behaviour, growth and development of larval Atlantic cod (Gadus morhua). Short-term noise caused startle responses in newly hatched fish, irrespective of rearing noise. Two days of both regular and random noise regimes reduced growth, while regular noise led to faster yolk sac use. After 16 days, growth in all three sound treatments converged, although fish exposed to regular noise had lower body width-length ratios. Larvae with lower body width-length ratios were easier to catch in a predator-avoidance experiment. Our results demonstrate that the timing of acoustic disturbances can impact survival-related measures during development. Much current work focuses on sound levels, but future studies should consider the role of noise regularity and its importance for noise management and mitigation measures. © 2015 The Authors.

Human exposure to environmental health concern by types of urban environment: The case of Tel Aviv.

PubMed

Schnell, Izhak; Potchter, Oded; Yaakov, Yaron; Epstein, Yoram

2016-01-01

This study classifies urban environments into types characterized by different exposure to environmental risk factors measured by general sense of discomfort and Heart Rate Variability (HRV). We hypothesize that a set of environmental factors (micro-climatic, CO, noise and individual heart rate) that were measured simultaneously in random locations can provide a better understanding of the distribution of human exposure to environmental loads throughout the urban space than results calculated based on measurements from close fixed stations. We measured micro-climatic and thermal load, CO and noise, individual Heart Rate, Subjective Social Load and Sense of Discomfort (SD) were tested by questionnaire survey. The results demonstrate significant differences in exposure to environmental factors among 8 types of urban environments. It appears that noise and social load are the more significant environmental factors to enhance health risks and general sense of discomfort. Copyright © 2015 Elsevier Ltd. All rights reserved.

Cross over of recurrence networks to random graphs and random geometric graphs

NASA Astrophysics Data System (ADS)

Jacob, Rinku; Harikrishnan, K. P.; Misra, R.; Ambika, G.

2017-02-01

Recurrence networks are complex networks constructed from the time series of chaotic dynamical systems where the connection between two nodes is limited by the recurrence threshold. This condition makes the topology of every recurrence network unique with the degree distribution determined by the probability density variations of the representative attractor from which it is constructed. Here we numerically investigate the properties of recurrence networks from standard low-dimensional chaotic attractors using some basic network measures and show how the recurrence networks are different from random and scale-free networks. In particular, we show that all recurrence networks can cross over to random geometric graphs by adding sufficient amount of noise to the time series and into the classical random graphs by increasing the range of interaction to the system size. We also highlight the effectiveness of a combined plot of characteristic path length and clustering coefficient in capturing the small changes in the network characteristics.

Analysis of security of optical encryption with spatially incoherent illumination technique

NASA Astrophysics Data System (ADS)

Cheremkhin, Pavel A.; Evtikhiev, Nikolay N.; Krasnov, Vitaly V.; Rodin, Vladislav G.; Shifrina, Anna V.

2017-03-01

Applications of optical methods for encryption purposes have been attracting interest of researchers for decades. The first and the most popular is double random phase encoding (DRPE) technique. There are many optical encryption techniques based on DRPE. Main advantage of DRPE based techniques is high security due to transformation of spectrum of image to be encrypted into white spectrum via use of first phase random mask which allows for encrypted images with white spectra. Downsides are necessity of using holographic registration scheme in order to register not only light intensity distribution but also its phase distribution, and speckle noise occurring due to coherent illumination. Elimination of these disadvantages is possible via usage of incoherent illumination instead of coherent one. In this case, phase registration no longer matters, which means that there is no need for holographic setup, and speckle noise is gone. This technique does not have drawbacks inherent to coherent methods, however, as only light intensity distribution is considered, mean value of image to be encrypted is always above zero which leads to intensive zero spatial frequency peak in image spectrum. Consequently, in case of spatially incoherent illumination, image spectrum, as well as encryption key spectrum, cannot be white. This might be used to crack encryption system. If encryption key is very sparse, encrypted image might contain parts or even whole unhidden original image. Therefore, in this paper analysis of security of optical encryption with spatially incoherent illumination depending on encryption key size and density is conducted.

Taming stochastic bifurcations in fractional-order systems via noise and delayed feedback

NASA Astrophysics Data System (ADS)

Sun, Zhongkui; Zhang, Jintian; Yang, Xiaoli; Xu, Wei

2017-08-01

The dynamics in fractional-order systems have been widely studied during the past decade due to the potential applications in new materials and anomalous diffusions, but the investigations have been so far restricted to a fractional-order system without time delay(s). In this paper, we report the first study of random responses of fractional-order system coupled with noise and delayed feedback. Stochastic averaging method has been utilized to determine the stationary probability density functions (PDFs) by means of the principle of minimum mean-square error, based on which stochastic bifurcations could be identified through recognizing the shape of the PDFs. It has been found that by changing the fractional order the shape of the PDFs can switch from unimodal distribution to bimodal one, or from bimodal distribution to unimodal one, thus announcing the onset of stochastic bifurcation. Further, we have demonstrated that by merely modulating the time delay, the feedback strengths, or the noise intensity, the shapes of PDFs can transit between a single peak and a double peak. Therefore, it provides an efficient candidate to control, say, induce or suppress, the stochastic bifurcations in fractional-order systems.

Robust local search for spacecraft operations using adaptive noise

NASA Technical Reports Server (NTRS)

Fukunaga, Alex S.; Rabideau, Gregg; Chien, Steve

2004-01-01

Randomization is a standard technique for improving the performance of local search algorithms for constraint satisfaction. However, it is well-known that local search algorithms are constraints satisfaction. However, it is well-known that local search algorithms are to the noise values selected. We investigate the use of an adaptive noise mechanism in an iterative repair-based planner/scheduler for spacecraft operations. Preliminary results indicate that adaptive noise makes the use of randomized repair moves safe and robust; that is, using adaptive noise makes it possible to consistently achieve, performance comparable with the best tuned noise setting without the need for manually tuning the noise parameter.

Air data system optimization using a genetic algorithm

NASA Technical Reports Server (NTRS)

Deshpande, Samir M.; Kumar, Renjith R.; Seywald, Hans; Siemers, Paul M., III

1992-01-01

An optimization method for flush-orifice air data system design has been developed using the Genetic Algorithm approach. The optimization of the orifice array minimizes the effect of normally distributed random noise in the pressure readings on the calculation of air data parameters, namely, angle of attack, sideslip angle and freestream dynamic pressure. The optimization method is applied to the design of Pressure Distribution/Air Data System experiment (PD/ADS) proposed for inclusion in the Aeroassist Flight Experiment (AFE). Results obtained by the Genetic Algorithm method are compared to the results obtained by conventional gradient search method.

Geodesic denoising for optical coherence tomography images

NASA Astrophysics Data System (ADS)

Shahrian Varnousfaderani, Ehsan; Vogl, Wolf-Dieter; Wu, Jing; Gerendas, Bianca S.; Simader, Christian; Langs, Georg; Waldstein, Sebastian M.; Schmidt-Erfurth, Ursula

2016-03-01

Optical coherence tomography (OCT) is an optical signal acquisition method capturing micrometer resolution, cross-sectional three-dimensional images. OCT images are used widely in ophthalmology to diagnose and monitor retinal diseases such as age-related macular degeneration (AMD) and Glaucoma. While OCT allows the visualization of retinal structures such as vessels and retinal layers, image quality and contrast is reduced by speckle noise, obfuscating small, low intensity structures and structural boundaries. Existing denoising methods for OCT images may remove clinically significant image features such as texture and boundaries of anomalies. In this paper, we propose a novel patch based denoising method, Geodesic Denoising. The method reduces noise in OCT images while preserving clinically significant, although small, pathological structures, such as fluid-filled cysts in diseased retinas. Our method selects optimal image patch distribution representations based on geodesic patch similarity to noisy samples. Patch distributions are then randomly sampled to build a set of best matching candidates for every noisy sample, and the denoised value is computed based on a geodesic weighted average of the best candidate samples. Our method is evaluated qualitatively on real pathological OCT scans and quantitatively on a proposed set of ground truth, noise free synthetic OCT scans with artificially added noise and pathologies. Experimental results show that performance of our method is comparable with state of the art denoising methods while outperforming them in preserving the critical clinically relevant structures.

SNR enhancement for downhole microseismic data based on scale classification shearlet transform

NASA Astrophysics Data System (ADS)

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

2018-06-01

Shearlet transform (ST) can be effective in 2D signal processing, due to its parabolic scaling, high directional sensitivity, and optimal sparsity. ST combined with thresholding has been successfully applied to suppress random noise. However, because of the low magnitude and high frequency of a downhole microseismic signal, the coefficient values of valid signals and noise are similar in the shearlet domain. As a result, it is difficult to use for denoising. In this paper, we present a scale classification ST to solve this problem. The ST is used to decompose noisy microseismic data into serval scales. By analyzing the spectrum and energy distribution of the shearlet coefficients of microseismic data, we divide the scales into two types: low-frequency scales which contain less useful signal and high-frequency scales which contain more useful signal. After classification, we use two different methods to deal with the coefficients on different scales. For the low-frequency scales, the noise is attenuated using a thresholding method. As for the high-frequency scales, we propose to use a generalized Gauss distribution model based a non-local means filter, which takes advantage of the temporal and spatial similarity of microseismic data. The experimental results on both synthetic records and field data illustrate that our proposed method preserves the useful components and attenuates the noise well.

Lévy-like behaviour in deterministic models of intelligent agents exploring heterogeneous environments

NASA Astrophysics Data System (ADS)

Boyer, D.; Miramontes, O.; Larralde, H.

2009-10-01

Many studies on animal and human movement patterns report the existence of scaling laws and power-law distributions. Whereas a number of random walk models have been proposed to explain observations, in many situations individuals actually rely on mental maps to explore strongly heterogeneous environments. In this work, we study a model of a deterministic walker, visiting sites randomly distributed on the plane and with varying weight or attractiveness. At each step, the walker minimizes a function that depends on the distance to the next unvisited target (cost) and on the weight of that target (gain). If the target weight distribution is a power law, p(k) ~ k-β, in some range of the exponent β, the foraging medium induces movements that are similar to Lévy flights and are characterized by non-trivial exponents. We explore variations of the choice rule in order to test the robustness of the model and argue that the addition of noise has a limited impact on the dynamics in strongly disordered media.

A Multi-Stage Method for Connecting Participatory Sensing and Noise Simulations

PubMed Central

Hu, Mingyuan; Che, Weitao; Zhang, Qiuju; Luo, Qingli; Lin, Hui

2015-01-01

Most simulation-based noise maps are important for official noise assessment but lack local noise characteristics. The main reasons for this lack of information are that official noise simulations only provide information about expected noise levels, which is limited by the use of large-scale monitoring of noise sources, and are updated infrequently. With the emergence of smart cities and ubiquitous sensing, the possible improvements enabled by sensing technologies provide the possibility to resolve this problem. This study proposed an integrated methodology to propel participatory sensing from its current random and distributed sampling origins to professional noise simulation. The aims of this study were to effectively organize the participatory noise data, to dynamically refine the granularity of the noise features on road segments (e.g., different portions of a road segment), and then to provide a reasonable spatio-temporal data foundation to support noise simulations, which can be of help to researchers in understanding how participatory sensing can play a role in smart cities. This study first discusses the potential limitations of the current participatory sensing and simulation-based official noise maps. Next, we explain how participatory noise data can contribute to a simulation-based noise map by providing (1) spatial matching of the participatory noise data to the virtual partitions at a more microscopic level of road networks; (2) multi-temporal scale noise estimations at the spatial level of virtual partitions; and (3) dynamic aggregation of virtual partitions by comparing the noise values at the relevant temporal scale to form a dynamic segmentation of each road segment to support multiple spatio-temporal noise simulations. In this case study, we demonstrate how this method could play a significant role in a simulation-based noise map. Together, these results demonstrate the potential benefits of participatory noise data as dynamic input sources for noise simulations on multiple spatio-temporal scales. PMID:25621604

A multi-stage method for connecting participatory sensing and noise simulations.

PubMed

Hu, Mingyuan; Che, Weitao; Zhang, Qiuju; Luo, Qingli; Lin, Hui

2015-01-22

Most simulation-based noise maps are important for official noise assessment but lack local noise characteristics. The main reasons for this lack of information are that official noise simulations only provide information about expected noise levels, which is limited by the use of large-scale monitoring of noise sources, and are updated infrequently. With the emergence of smart cities and ubiquitous sensing, the possible improvements enabled by sensing technologies provide the possibility to resolve this problem. This study proposed an integrated methodology to propel participatory sensing from its current random and distributed sampling origins to professional noise simulation. The aims of this study were to effectively organize the participatory noise data, to dynamically refine the granularity of the noise features on road segments (e.g., different portions of a road segment), and then to provide a reasonable spatio-temporal data foundation to support noise simulations, which can be of help to researchers in understanding how participatory sensing can play a role in smart cities. This study first discusses the potential limitations of the current participatory sensing and simulation-based official noise maps. Next, we explain how participatory noise data can contribute to a simulation-based noise map by providing (1) spatial matching of the participatory noise data to the virtual partitions at a more microscopic level of road networks; (2) multi-temporal scale noise estimations at the spatial level of virtual partitions; and (3) dynamic aggregation of virtual partitions by comparing the noise values at the relevant temporal scale to form a dynamic segmentation of each road segment to support multiple spatio-temporal noise simulations. In this case study, we demonstrate how this method could play a significant role in a simulation-based noise map. Together, these results demonstrate the potential benefits of participatory noise data as dynamic input sources for noise simulations on multiple spatio-temporal scales.

Studies in astronomical time series analysis. I - Modeling random processes in the time domain

NASA Technical Reports Server (NTRS)

Scargle, J. D.

1981-01-01

Several random process models in the time domain are defined and discussed. Attention is given to the moving average model, the autoregressive model, and relationships between and combinations of these models. Consideration is then given to methods for investigating pulse structure, procedures of model construction, computational methods, and numerical experiments. A FORTRAN algorithm of time series analysis has been developed which is relatively stable numerically. Results of test cases are given to study the effect of adding noise and of different distributions for the pulse amplitudes. A preliminary analysis of the light curve of the quasar 3C 272 is considered as an example.

The stretch to stray on time: Resonant length of random walks in a transient

NASA Astrophysics Data System (ADS)

Falcke, Martin; Friedhoff, Victor Nicolai

2018-05-01

First-passage times in random walks have a vast number of diverse applications in physics, chemistry, biology, and finance. In general, environmental conditions for a stochastic process are not constant on the time scale of the average first-passage time or control might be applied to reduce noise. We investigate moments of the first-passage time distribution under an exponential transient describing relaxation of environmental conditions. We solve the Laplace-transformed (generalized) master equation analytically using a novel method that is applicable to general state schemes. The first-passage time from one end to the other of a linear chain of states is our application for the solutions. The dependence of its average on the relaxation rate obeys a power law for slow transients. The exponent ν depends on the chain length N like ν = - N / ( N + 1 ) to leading order. Slow transients substantially reduce the noise of first-passage times expressed as the coefficient of variation (CV), even if the average first-passage time is much longer than the transient. The CV has a pronounced minimum for some lengths, which we call resonant lengths. These results also suggest a simple and efficient noise control strategy and are closely related to the timing of repetitive excitations, coherence resonance, and information transmission by noisy excitable systems. A resonant number of steps from the inhibited state to the excitation threshold and slow recovery from negative feedback provide optimal timing noise reduction and information transmission.

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

NASA Astrophysics Data System (ADS)

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.

Nonlinear Relaxation in Population Dynamics

NASA Astrophysics Data System (ADS)

Cirone, Markus A.; de Pasquale, Ferdinando; Spagnolo, Bernardo

We analyze the nonlinear relaxation of a complex ecosystem composed of many interacting species. The ecological system is described by generalized Lotka-Volterra equations with a multiplicative noise. The transient dynamics is studied in the framework of the mean field theory and with random interaction between the species. We focus on the statistical properties of the asymptotic behaviour of the time integral of the ith population and on the distribution of the population and of the local field.

Analytic model for low-frequency noise in nanorod devices.

PubMed

Lee, Jungil; Yu, Byung Yong; Han, Ilki; Choi, Kyoung Jin; Ghibaudo, Gerard

2008-10-01

In this work analytic model for generation of excess low-frequency noise in nanorod devices such as field-effect transistors are developed. In back-gate field-effect transistors where most of the surface area of the nanorod is exposed to the ambient, the surface states could be the major noise source via random walk of electrons for the low-frequency or 1/f noise. In dual gate transistors, the interface states and oxide traps can compete with each other as the main noise source via random walk and tunneling, respectively.

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed Central

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

Realistic noise-tolerant randomness amplification using finite number of devices.

PubMed

Brandão, Fernando G S L; Ramanathan, Ravishankar; Grudka, Andrzej; Horodecki, Karol; Horodecki, Michał; Horodecki, Paweł; Szarek, Tomasz; Wojewódka, Hanna

2016-04-21

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.

Realistic noise-tolerant randomness amplification using finite number of devices

NASA Astrophysics Data System (ADS)

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.

Realistic noise-tolerant randomness amplification using finite number of devices

PubMed Central

Brandão, Fernando G. S. L.; Ramanathan, Ravishankar; Grudka, Andrzej; Horodecki, Karol; Horodecki, Michał; Horodecki, Paweł; Szarek, Tomasz; Wojewódka, Hanna

2016-01-01

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. PMID:27098302

Response statistics of rotating shaft with non-linear elastic restoring forces by path integration

NASA Astrophysics Data System (ADS)

Gaidai, Oleg; Naess, Arvid; Dimentberg, Michael

2017-07-01

Extreme statistics of random vibrations is studied for a Jeffcott rotor under uniaxial white noise excitation. Restoring force is modelled as elastic non-linear; comparison is done with linearized restoring force to see the force non-linearity effect on the response statistics. While for the linear model analytical solutions and stability conditions are available, it is not generally the case for non-linear system except for some special cases. The statistics of non-linear case is studied by applying path integration (PI) method, which is based on the Markov property of the coupled dynamic system. The Jeffcott rotor response statistics can be obtained by solving the Fokker-Planck (FP) equation of the 4D dynamic system. An efficient implementation of PI algorithm is applied, namely fast Fourier transform (FFT) is used to simulate dynamic system additive noise. The latter allows significantly reduce computational time, compared to the classical PI. Excitation is modelled as Gaussian white noise, however any kind distributed white noise can be implemented with the same PI technique. Also multidirectional Markov noise can be modelled with PI in the same way as unidirectional. PI is accelerated by using Monte Carlo (MC) estimated joint probability density function (PDF) as initial input. Symmetry of dynamic system was utilized to afford higher mesh resolution. Both internal (rotating) and external damping are included in mechanical model of the rotor. The main advantage of using PI rather than MC is that PI offers high accuracy in the probability distribution tail. The latter is of critical importance for e.g. extreme value statistics, system reliability, and first passage probability.

Design of fast signal processing readout front-end electronics implemented in CMOS 40 nm technology

NASA Astrophysics Data System (ADS)

Kleczek, Rafal

2016-12-01

The author presents considerations on the design of fast readout front-end electronics implemented in a CMOS 40 nm technology with an emphasis on the system dead time, noise performance and power dissipation. The designed processing channel consists of a charge sensitive amplifier with different feedback types (Krummenacher, resistive and constant current blocks), a threshold setting block, a discriminator and a counter with logic circuitry. The results of schematic and post-layout simulations with randomly generated input pulses in a time domain according to the Poisson distribution are presented and analyzed. Dead time below 20 ns is possible while keeping noise ENC ≈ 90 e- for a detector capacitance CDET = 160 fF.

Modified interferometric imaging condition for reverse-time migration

NASA Astrophysics Data System (ADS)

Guo, Xue-Bao; Liu, Hong; Shi, Ying

2018-01-01

For reverse-time migration, high-resolution imaging mainly depends on the accuracy of the velocity model and the imaging condition. In practice, however, the small-scale components of the velocity model cannot be estimated by tomographical methods; therefore, the wavefields are not accurately reconstructed from the background velocity, and the imaging process will generate artefacts. Some of the noise is due to cross-correlation of unrelated seismic events. Interferometric imaging condition suppresses imaging noise very effectively, especially the unknown random disturbance of the small-scale part. The conventional interferometric imaging condition is extended in this study to obtain a new imaging condition based on the pseudo-Wigner distribution function (WDF). Numerical examples show that the modified interferometric imaging condition improves imaging precision.

Learning stochastic reward distributions in a speeded pointing task.

PubMed

Seydell, Anna; McCann, Brian C; Trommershäuser, Julia; Knill, David C

2008-04-23

Recent studies have shown that humans effectively take into account task variance caused by intrinsic motor noise when planning fast hand movements. However, previous evidence suggests that humans have greater difficulty accounting for arbitrary forms of stochasticity in their environment, both in economic decision making and sensorimotor tasks. We hypothesized that humans can learn to optimize movement strategies when environmental randomness can be experienced and thus implicitly learned over several trials, especially if it mimics the kinds of randomness for which subjects might have generative models. We tested the hypothesis using a task in which subjects had to rapidly point at a target region partly covered by three stochastic penalty regions introduced as "defenders." At movement completion, each defender jumped to a new position drawn randomly from fixed probability distributions. Subjects earned points when they hit the target, unblocked by a defender, and lost points otherwise. Results indicate that after approximately 600 trials, subjects approached optimal behavior. We further tested whether subjects simply learned a set of stimulus-contingent motor plans or the statistics of defenders' movements by training subjects with one penalty distribution and then testing them on a new penalty distribution. Subjects immediately changed their strategy to achieve the same average reward as subjects who had trained with the second penalty distribution. These results indicate that subjects learned the parameters of the defenders' jump distributions and used this knowledge to optimally plan their hand movements under conditions involving stochastic rewards and penalties.

Last Passage Percolation and Traveling Fronts

NASA Astrophysics Data System (ADS)

Comets, Francis; Quastel, Jeremy; Ramírez, Alejandro F.

2013-08-01

We consider a system of N particles with a stochastic dynamics introduced by Brunet and Derrida (Phys. Rev. E 70:016106, 2004). The particles can be interpreted as last passage times in directed percolation on {1,…, N} of mean-field type. The particles remain grouped and move like a traveling front, subject to discretization and driven by a random noise. As N increases, we obtain estimates for the speed of the front and its profile, for different laws of the driving noise. As shown in Brunet and Derrida (Phys. Rev. E 70:016106, 2004), the model with Gumbel distributed jumps has a simple structure. We establish that the scaling limit is a Lévy process in this case. We study other jump distributions. We prove a result showing that the limit for large N is stable under small perturbations of the Gumbel. In the opposite case of bounded jumps, a completely different behavior is found, where finite-size corrections are extremely small.

A new approach for beam hardening correction based on the local spectrum distributions

NASA Astrophysics Data System (ADS)

Rasoulpour, Naser; Kamali-Asl, Alireza; Hemmati, Hamidreza

2015-09-01

Energy dependence of material absorption and polychromatic nature of x-ray beams in the Computed Tomography (CT) causes a phenomenon which called "beam hardening". The purpose of this study is to provide a novel approach for Beam Hardening (BH) correction. This approach is based on the linear attenuation coefficients of Local Spectrum Distributions (LSDs) in the various depths of a phantom. The proposed method includes two steps. Firstly, the hardened spectra in various depths of the phantom (or LSDs) are estimated based on the Expectation Maximization (EM) algorithm for arbitrary thickness interval of known materials in the phantom. The performance of LSD estimation technique is evaluated by applying random Gaussian noise to transmission data. Then, the linear attenuation coefficients with regarding to the mean energy of LSDs are obtained. Secondly, a correction function based on the calculated attenuation coefficients is derived in order to correct polychromatic raw data. Since a correction function has been used for the conversion of the polychromatic data to the monochromatic data, the effect of BH in proposed reconstruction must be reduced in comparison with polychromatic reconstruction. The proposed approach has been assessed in the phantoms which involve less than two materials, but the correction function has been extended for using in the constructed phantoms with more than two materials. The relative mean energy difference in the LSDs estimations based on the noise-free transmission data was less than 1.5%. Also, it shows an acceptable value when a random Gaussian noise is applied to the transmission data. The amount of cupping artifact in the proposed reconstruction method has been effectively reduced and proposed reconstruction profile is uniform more than polychromatic reconstruction profile.

Noise in two-color electronic distance meter measurements revisited

USGS Publications Warehouse

Langbein, J.

2004-01-01

Frequent, high-precision geodetic data have temporally correlated errors. Temporal correlations directly affect both the estimate of rate and its standard error; the rate of deformation is a key product from geodetic measurements made in tectonically active areas. Various models of temporally correlated errors are developed and these provide relations between the power spectral density and the data covariance matrix. These relations are applied to two-color electronic distance meter (EDM) measurements made frequently in California over the past 15-20 years. Previous analysis indicated that these data have significant random walk error. Analysis using the noise models developed here indicates that the random walk model is valid for about 30% of the data. A second 30% of the data can be better modeled with power law noise with a spectral index between 1 and 2, while another 30% of the data can be modeled with a combination of band-pass-filtered plus random walk noise. The remaining 10% of the data can be best modeled as a combination of band-pass-filtered plus power law noise. This band-pass-filtered noise is a product of an annual cycle that leaks into adjacent frequency bands. For time spans of more than 1 year these more complex noise models indicate that the precision in rate estimates is better than that inferred by just the simpler, random walk model of noise.

DIAL with heterodyne detection including speckle noise: Aircraft/shuttle measurements of O3, H2O, and NH3 with pulsed tunable CO2 lasers

NASA Technical Reports Server (NTRS)

Brockman, P.; Hess, R. V.; Staton, L. D.; Bair, C. H.

1980-01-01

Atmospheric trace constituent measurements with higher vertical resolution than attainable with passive radiometers are discussed. Infrared differential absorption lidar (DIAL), which depends on Mie scattering from aerosols, has special advantages for tropospheric and lower stratospheric applications and has great potential importance for measurements from shuttle and aircraft. Differential absorption lidar data reduction involves comparing large amplitude signals which have small differences. The accuracy of the trace constituent concentration inferred from DIAL measurements depends strongly on the errors in determining the amplitude of the signals. Thus, the commonly used SNR expression (signal divided by noise in the absence of signal) is not adequate to describe DIAL measurement accuracy and must be replaced by an expression which includes the random coherent (speckle) noise within the signal. A comprehensive DIAL computer algorithm is modified to include heterodyne detection and speckle noise. Examples for monitoring vertical distributions of O3, H2O, and NH3 using a ground-, aircraft-, or shuttle-based pulsed tunable CO2 laser DIAL system are given.

Narrow line width dual wavelength semiconductor optical amplifier based random fiber laser

NASA Astrophysics Data System (ADS)

Shawki, Heba A.; Kotb, Hussein E.; Khalil, Diaa

2018-02-01

A novel narrow line-width Single longitudinal mode (SLM) dual wavelength random fiber laser of 20 nm separation between wavelengths of 1530 and 1550 nm is presented. The laser is based on Rayleigh backscattering in a standard single mode fiber of 2 Km length as distributed mirrors, and a semiconductor optical amplifier (SOA) as the optical amplification medium. Two optical bandpass filters are used for the two wavelengths selectivity, and two Faraday Rotator mirrors are used to stabilize the two lasing wavelengths against fiber random birefringence. The optical signal to noise ratio (OSNR) was measured to be 38 dB. The line-width of the laser was measured to be 13.3 and 14 KHz at 1530 and 1550 nm respectively, at SOA pump current of 370 mA.

The Combined Effect of Periodic Signals and Noise on the Dilution of Precision of GNSS Station Velocity Uncertainties

NASA Astrophysics Data System (ADS)

Klos, Anna; Olivares, German; Teferle, Felix Norman; Bogusz, Janusz

2016-04-01

Station velocity uncertainties determined from a series of Global Navigation Satellite System (GNSS) position estimates depend on both the deterministic and stochastic models applied to the time series. While the deterministic model generally includes parameters for a linear and several periodic terms the stochastic model is a representation of the noise character of the time series in form of a power-law process. For both of these models the optimal model may vary from one time series to another while the models also depend, to some degree, on each other. In the past various power-law processes have been shown to fit the time series and the sources for the apparent temporally-correlated noise were attributed to, for example, mismodelling of satellites orbits, antenna phase centre variations, troposphere, Earth Orientation Parameters, mass loading effects and monument instabilities. Blewitt and Lavallée (2002) demonstrated how improperly modelled seasonal signals affected the estimates of station velocity uncertainties. However, in their study they assumed that the time series followed a white noise process with no consideration of additional temporally-correlated noise. Bos et al. (2010) empirically showed for a small number of stations that the noise character was much more important for the reliable estimation of station velocity uncertainties than the seasonal signals. In this presentation we pick up from Blewitt and Lavallée (2002) and Bos et al. (2010), and have derived formulas for the computation of the General Dilution of Precision (GDP) under presence of periodic signals and temporally-correlated noise in the time series. We show, based on simulated and real time series from globally distributed IGS (International GNSS Service) stations processed by the Jet Propulsion Laboratory (JPL), that periodic signals dominate the effect on the velocity uncertainties at short time scales while for those beyond four years, the type of noise becomes much more important. In other words, for time series long enough, the assumed periodic signals do not affect the velocity uncertainties as much as the assumed noise model. We calculated the GDP to be the ratio between two errors of velocity: without and with inclusion of seasonal terms of periods equal to one year and its overtones till 3rd. To all these cases power-law processes of white, flicker and random-walk noise were added separately. Few oscillations in GDP can be noticed for integer years, which arise from periodic terms added. Their amplitudes in GDP increase along with the increasing spectral index. Strong peaks of oscillations in GDP are indicated for short time scales, especially for random-walk processes. This means that badly monumented stations are affected the most. Local minima and maxima in GDP are also enlarged as the noise approaches random walk. We noticed that the semi-annual signal increased the local GDP minimum for white noise. This suggests that adding power-law noise to a deterministic model with annual term or adding a semi-annual term to white noise causes an increased velocity uncertainty even at the points, where determined velocity is not biased.

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

PubMed

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.

Acoustic Holography

NASA Astrophysics Data System (ADS)

Kim, Yang-Hann

One of the subtle problems that make noise control difficult for engineers is the invisibility of noise or sound. A visual image of noise often helps to determine an appropriate means for noise control. There have been many attempts to fulfill this rather challenging objective. Theoretical (or numerical) means for visualizing the sound field have been attempted, and as a result, a great deal of progress has been made. However, most of these numerical methods are not quite ready for practical applications to noise control problems. In the meantime, rapid progress with instrumentation has made it possible to use multiple microphones and fast signal-processing systems. Although these systems are not perfect, they are useful. A state-of-the-art system has recently become available, but it still has many problematic issues; for example, how can one implement the visualized noise field. The constructed noise or sound picture always consists of bias and random errors, and consequently, it is often difficult to determine the origin of the noise and the spatial distribution of the noise field. Section 26.2 of this chapter introduces a brief history, which is associated with "sound visualization," acoustic source identification methods and what has been accomplished with a line or surface array. Section 26.2.3 introduces difficulties and recent studies, including de-Dopplerization and de-reverberation methods, both essentialfor visualizing a moving noise source, such as occurs for cars or trains. This section also addresses what produces ambiguity in realizing real sound sources in a room or closed space. Another major issue associated with sound/noise visualization is whether or not we can distinguish between mutual dependencies of noise in space (Sect. 26.2.4); for example, we are asked to answer the question, "Can we see two birds singing or one bird with two beaks?"

Acoustic Holography

NASA Astrophysics Data System (ADS)

Kim, Yang-Hann

One of the subtle problems that make noise control difficult for engineers is the invisibility of noise or sound. A visual image of noise often helps to determine an appropriate means for noise control. There have been many attempts to fulfill this rather challenging objective. Theoretical (or numerical) means for visualizing the sound field have been attempted, and as a result, a great deal of progress has been made. However, most of these numerical methods are not quite ready for practical applications to noise control problems. In the meantime, rapid progress with instrumentation has made it possible to use multiple microphones and fast signal-processing systems. Although these systems are not perfect, they are useful. A state-of-the-art system has recently become available, but it still has many problematic issues; for example, how can one implement the visualized noise field. The constructed noise or sound picture always consists of bias and random errors, and consequently, it is often difficult to determine the origin of the noise and the spatial distribution of the noise field. Section 26.2 of this chapter introduces a brief history, which is associated with sound visualization, acoustic source identification methods and what has been accomplished with a line or surface array. Section 26.2.3 introduces difficulties and recent studies, including de-Dopplerization and de-re verberation methods, both essential for visualizing a moving noise source, such as occurs for cars or trains. This section also addresses what produces ambiguity in realizing real sound sources in a room or closed space. Another major issue associated with sound/noise visualization is whether or not we can distinguish between mutual dependencies of noise in space (Sect. 26.2.4); for example, we are asked to answer the question, Can we see two birds singing or one bird with two beaks?

Random-access algorithms for multiuser computer communication networks. Doctoral thesis, 1 September 1986-31 August 1988

DOE Office of Scientific and Technical Information (OSTI.GOV)

Papantoni-Kazakos, P.; Paterakis, M.

1988-07-01

For many communication applications with time constraints (e.g., transmission of packetized voice messages), a critical performance measure is the percentage of messages transmitted within a given amount of time after their generation at the transmitting station. This report presents a random-access algorithm (RAA) suitable for time-constrained applications. Performance analysis demonstrates that significant message-delay improvement is attained at the expense of minimal traffic loss. Also considered is the case of noisy channels. The noise effect appears at erroneously observed channel feedback. Error sensitivity analysis shows that the proposed random-access algorithm is insensitive to feedback channel errors. Window Random-Access Algorithms (RAAs) aremore » considered next. These algorithms constitute an important subclass of Multiple-Access Algorithms (MAAs); they are distributive, and they attain high throughput and low delays by controlling the number of simultaneously transmitting users.« less

Random attractor of non-autonomous stochastic Boussinesq lattice system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Min, E-mail: zhaomin1223@126.com; Zhou, Shengfan, E-mail: zhoushengfan@yahoo.com

2015-09-15

In this paper, we first consider the existence of tempered random attractor for second-order non-autonomous stochastic lattice dynamical system of nonlinear Boussinesq equations effected by time-dependent coupled coefficients and deterministic forces and multiplicative white noise. Then, we establish the upper semicontinuity of random attractors as the intensity of noise approaches zero.

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

NASA Technical Reports Server (NTRS)

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.

Atomic clocks and the continuous-time random-walk

NASA Astrophysics Data System (ADS)

Formichella, Valerio; Camparo, James; Tavella, Patrizia

2017-11-01

Atomic clocks play a fundamental role in many fields, most notably they generate Universal Coordinated Time and are at the heart of all global navigation satellite systems. Notwithstanding their excellent timekeeping performance, their output frequency does vary: it can display deterministic frequency drift; diverse continuous noise processes result in nonstationary clock noise (e.g., random-walk frequency noise, modelled as a Wiener process), and the clock frequency may display sudden changes (i.e., "jumps"). Typically, the clock's frequency instability is evaluated by the Allan or Hadamard variances, whose functional forms can identify the different operative noise processes. Here, we show that the Allan and Hadamard variances of a particular continuous-time random-walk, the compound Poisson process, have the same functional form as for a Wiener process with drift. The compound Poisson process, introduced as a model for observed frequency jumps, is an alternative to the Wiener process for modelling random walk frequency noise. This alternate model fits well the behavior of the rubidium clocks flying on GPS Block-IIR satellites. Further, starting from jump statistics, the model can be improved by considering a more general form of continuous-time random-walk, and this could bring new insights into the physics of atomic clocks.

Fully probabilistic seismic source inversion - Part 2: Modelling errors and station covariances

NASA Astrophysics Data System (ADS)

Stähler, Simon C.; Sigloch, Karin

2016-11-01

Seismic source inversion, a central task in seismology, is concerned with the estimation of earthquake source parameters and their uncertainties. Estimating uncertainties is particularly challenging because source inversion is a non-linear problem. In a companion paper, Stähler and Sigloch (2014) developed a method of fully Bayesian inference for source parameters, based on measurements of waveform cross-correlation between broadband, teleseismic body-wave observations and their modelled counterparts. This approach yields not only depth and moment tensor estimates but also source time functions. A prerequisite for Bayesian inference is the proper characterisation of the noise afflicting the measurements, a problem we address here. We show that, for realistic broadband body-wave seismograms, the systematic error due to an incomplete physical model affects waveform misfits more strongly than random, ambient background noise. In this situation, the waveform cross-correlation coefficient CC, or rather its decorrelation D = 1 - CC, performs more robustly as a misfit criterion than ℓp norms, more commonly used as sample-by-sample measures of misfit based on distances between individual time samples. From a set of over 900 user-supervised, deterministic earthquake source solutions treated as a quality-controlled reference, we derive the noise distribution on signal decorrelation D = 1 - CC of the broadband seismogram fits between observed and modelled waveforms. The noise on D is found to approximately follow a log-normal distribution, a fortunate fact that readily accommodates the formulation of an empirical likelihood function for D for our multivariate problem. The first and second moments of this multivariate distribution are shown to depend mostly on the signal-to-noise ratio (SNR) of the CC measurements and on the back-azimuthal distances of seismic stations. By identifying and quantifying this likelihood function, we make D and thus waveform cross-correlation measurements usable for fully probabilistic sampling strategies, in source inversion and related applications such as seismic tomography.

Detection of anomalous signals in temporally correlated data (Invited)

NASA Astrophysics Data System (ADS)

Langbein, J. O.

2010-12-01

Detection of transient tectonic signals in data obtained from large geodetic networks requires the ability to detect signals that are both temporally and spatially coherent. In this report I will describe a modification to an existing method that estimates both the coefficients of temporally correlated noise model and an efficient filter based on the noise model. This filter, when applied to the original time-series, effectively whitens (or flattens) the power spectrum. The filtered data provide the means to calculate running averages which are then used to detect deviations from the background trends. For large networks, time-series of signal-to-noise ratio (SNR) can be easily constructed since, by filtering, each of the original time-series has been transformed into one that is closer to having a Gaussian distribution with a variance of 1.0. Anomalous intervals may be identified by counting the number of GPS sites for which the SNR exceeds a specified value. For example, during one time interval, if there were 5 out of 20 time-series with SNR>2, this would be considered anomalous; typically, one would expect at 95% confidence that there would be at least 1 out of 20 time-series with an SNR>2. For time intervals with an anomalously large number of high SNR, the spatial distribution of the SNR is mapped to identify the location of the anomalous signal(s) and their degree of spatial clustering. Estimating the filter that should be used to whiten the data requires modification of the existing methods that employ maximum likelihood estimation to determine the temporal covariance of the data. In these methods, it is assumed that the noise components in the data are a combination of white, flicker and random-walk processes and that they are derived from three different and independent sources. Instead, in this new method, the covariance matrix is constructed assuming that only one source is responsible for the noise and that source can be represented as a white-noise random-number generator convolved with a filter whose spectral properties are frequency (f) independent at its highest frequencies, 1/f at the middle frequencies, and 1/f2 at the lowest frequencies. For data sets with no gaps in their time-series, construction of covariance and inverse covariance matrices is extremely efficient. Application of the above algorithm to real data potentially involves several iterations as small, tectonic signals of interest are often indistinguishable from background noise. Consequently, simply plotting the time-series of each GPS site is used to identify the largest outliers and signals independent of their cause. Any analysis of the background noise levels must factor in these other signals while the gross outliers need to be removed.

High performance frame synchronization for continuous variable quantum key distribution systems.

PubMed

Lin, Dakai; Huang, Peng; Huang, Duan; Wang, Chao; Peng, Jinye; Zeng, Guihua

2015-08-24

Considering a practical continuous variable quantum key distribution(CVQKD) system, synchronization is of significant importance as it is hardly possible to extract secret keys from unsynchronized strings. In this paper, we proposed a high performance frame synchronization method for CVQKD systems which is capable to operate under low signal-to-noise(SNR) ratios and is compatible with random phase shift induced by quantum channel. A practical implementation of this method with low complexity is presented and its performance is analysed. By adjusting the length of synchronization frame, this method can work well with large range of SNR values which paves the way for longer distance CVQKD.

Towards Full-Waveform Ambient Noise Inversion

NASA Astrophysics Data System (ADS)

Sager, Korbinian; Ermert, Laura; Afanasiev, Michael; Boehm, Christian; Fichtner, Andreas

2017-04-01

Noise tomography usually works under the assumption that the inter-station ambient noise correlation is equal to a scaled version of the Green function between the two receivers. This assumption, however, is only met under specific conditions, e.g. wavefield diffusivity and equipartitioning, or the isotropic distribution of both mono- and dipolar uncorrelated noise sources. These assumptions are typically not satisfied in the Earth. This inconsistency inhibits the exploitation of the full waveform information contained in noise correlations in order to constrain Earth structure and noise generation. To overcome this limitation, we attempt to develop a method that consistently accounts for the distribution of noise sources, 3D heterogeneous Earth structure and the full seismic wave propagation physics. This is intended to improve the resolution of tomographic images, to refine noise source distribution, and thereby to contribute to a better understanding of both Earth structure and noise generation. First, we develop an inversion strategy based on a 2D finite-difference code using adjoint techniques. To enable a joint inversion for noise sources and Earth structure, we investigate the following aspects: i) the capability of different misfit functionals to image wave speed anomalies and source distribution and ii) possible source-structure trade-offs, especially to what extent unresolvable structure can be mapped into the inverted noise source distribution and vice versa. In anticipation of real-data applications, we present an extension of the open-source waveform modelling and inversion package Salvus (http://salvus.io). It allows us to compute correlation functions in 3D media with heterogeneous noise sources at the surface and the corresponding sensitivity kernels for the distribution of noise sources and Earth structure. By studying the effect of noise sources on correlation functions in 3D, we validate the aforementioned inversion strategy and prepare the workflow necessary for the first application of full waveform ambient noise inversion to a global dataset, for which a model for the distribution of noise sources is already available.

Temperature dependent characteristics of the random telegraph noise on contact resistive random access memory

NASA Astrophysics Data System (ADS)

Chang, Liang-Shun; Lin, Chrong Jung; King, Ya-Chin

2014-01-01

The temperature dependent characteristics of the random telegraphic noise (RTN) on contact resistive random access memory (CRRAM) are studied in this work. In addition to the bi-level switching, the occurrences of the middle states in the RTN signal are investigated. Based on the unique its temperature dependent characteristics, a new temperature sensing scheme is proposed for applications in ultra-low power sensor modules.

Memory-induced resonancelike suppression of spike generation in a resonate-and-fire neuron model

NASA Astrophysics Data System (ADS)

Mankin, Romi; Paekivi, Sander

2018-01-01

The behavior of a stochastic resonate-and-fire neuron model based on a reduction of a fractional noise-driven generalized Langevin equation (GLE) with a power-law memory kernel is considered. The effect of temporally correlated random activity of synaptic inputs, which arise from other neurons forming local and distant networks, is modeled as an additive fractional Gaussian noise in the GLE. Using a first-passage-time formulation, in certain system parameter domains exact expressions for the output interspike interval (ISI) density and for the survival probability (the probability that a spike is not generated) are derived and their dependence on input parameters, especially on the memory exponent, is analyzed. In the case of external white noise, it is shown that at intermediate values of the memory exponent the survival probability is significantly enhanced in comparison with the cases of strong and weak memory, which causes a resonancelike suppression of the probability of spike generation as a function of the memory exponent. Moreover, an examination of the dependence of multimodality in the ISI distribution on input parameters shows that there exists a critical memory exponent αc≈0.402 , which marks a dynamical transition in the behavior of the system. That phenomenon is illustrated by a phase diagram describing the emergence of three qualitatively different structures of the ISI distribution. Similarities and differences between the behavior of the model at internal and external noises are also discussed.

Generation of Stationary Non-Gaussian Time Histories with a Specified Cross-spectral Density

DOE PAGES

Smallwood, David O.

1997-01-01

The paper reviews several methods for the generation of stationary realizations of sampled time histories with non-Gaussian distributions and introduces a new method which can be used to control the cross-spectral density matrix and the probability density functions (pdfs) of the multiple input problem. Discussed first are two methods for the specialized case of matching the auto (power) spectrum, the skewness, and kurtosis using generalized shot noise and using polynomial functions. It is then shown that the skewness and kurtosis can also be controlled by the phase of a complex frequency domain description of the random process. The general casemore » of matching a target probability density function using a zero memory nonlinear (ZMNL) function is then covered. Next methods for generating vectors of random variables with a specified covariance matrix for a class of spherically invariant random vectors (SIRV) are discussed. Finally the general case of matching the cross-spectral density matrix of a vector of inputs with non-Gaussian marginal distributions is presented.« less

Color speckle in laser displays

NASA Astrophysics Data System (ADS)

Kuroda, Kazuo

2015-07-01

At the beginning of this century, lighting technology has been shifted from discharge lamps, fluorescent lamps and electric bulbs to solid-state lighting. Current solid-state lighting is based on the light emitting diodes (LED) technology, but the laser lighting technology is developing rapidly, such as, laser cinema projectors, laser TVs, laser head-up displays, laser head mounted displays, and laser headlamps for motor vehicles. One of the main issues of laser displays is the reduction of speckle noise1). For the monochromatic laser light, speckle is random interference pattern on the image plane (retina for human observer). For laser displays, RGB (red-green-blue) lasers form speckle patterns independently, which results in random distribution of chromaticity, called color speckle2).

Synchronization and Inter-Layer Interactions of Noise-Driven Neural Networks

PubMed Central

Yuniati, Anis; Mai, Te-Lun; Chen, Chi-Ming

2017-01-01

In this study, we used the Hodgkin-Huxley (HH) model of neurons to investigate the phase diagram of a developing single-layer neural network and that of a network consisting of two weakly coupled neural layers. These networks are noise driven and learn through the spike-timing-dependent plasticity (STDP) or the inverse STDP rules. We described how these networks transited from a non-synchronous background activity state (BAS) to a synchronous firing state (SFS) by varying the network connectivity and the learning efficacy. In particular, we studied the interaction between a SFS layer and a BAS layer, and investigated how synchronous firing dynamics was induced in the BAS layer. We further investigated the effect of the inter-layer interaction on a BAS to SFS repair mechanism by considering three types of neuron positioning (random, grid, and lognormal distributions) and two types of inter-layer connections (random and preferential connections). Among these scenarios, we concluded that the repair mechanism has the largest effect for a network with the lognormal neuron positioning and the preferential inter-layer connections. PMID:28197088

Synchronization and Inter-Layer Interactions of Noise-Driven Neural Networks.

PubMed

Yuniati, Anis; Mai, Te-Lun; Chen, Chi-Ming

2017-01-01

In this study, we used the Hodgkin-Huxley (HH) model of neurons to investigate the phase diagram of a developing single-layer neural network and that of a network consisting of two weakly coupled neural layers. These networks are noise driven and learn through the spike-timing-dependent plasticity (STDP) or the inverse STDP rules. We described how these networks transited from a non-synchronous background activity state (BAS) to a synchronous firing state (SFS) by varying the network connectivity and the learning efficacy. In particular, we studied the interaction between a SFS layer and a BAS layer, and investigated how synchronous firing dynamics was induced in the BAS layer. We further investigated the effect of the inter-layer interaction on a BAS to SFS repair mechanism by considering three types of neuron positioning (random, grid, and lognormal distributions) and two types of inter-layer connections (random and preferential connections). Among these scenarios, we concluded that the repair mechanism has the largest effect for a network with the lognormal neuron positioning and the preferential inter-layer connections.

Correlated errors in geodetic time series: Implications for time-dependent deformation

USGS Publications Warehouse

Langbein, J.; Johnson, H.

1997-01-01

Analysis of frequent trilateration observations from the two-color electronic distance measuring networks in California demonstrate that the noise power spectra are dominated by white noise at higher frequencies and power law behavior at lower frequencies. In contrast, Earth scientists typically have assumed that only white noise is present in a geodetic time series, since a combination of infrequent measurements and low precision usually preclude identifying the time-correlated signature in such data. After removing a linear trend from the two-color data, it becomes evident that there are primarily two recognizable types of time-correlated noise present in the residuals. The first type is a seasonal variation in displacement which is probably a result of measuring to shallow surface monuments installed in clayey soil which responds to seasonally occurring rainfall; this noise is significant only for a small fraction of the sites analyzed. The second type of correlated noise becomes evident only after spectral analysis of line length changes and shows a functional relation at long periods between power and frequency of and where f is frequency and ?? ??? 2. With ?? = 2, this type of correlated noise is termed random-walk noise, and its source is mainly thought to be small random motions of geodetic monuments with respect to the Earth's crust, though other sources are possible. Because the line length changes in the two-color networks are measured at irregular intervals, power spectral techniques cannot reliably estimate the level of I//" noise. Rather, we also use here a maximum likelihood estimation technique which assumes that there are only two sources of noise in the residual time series (white noise and randomwalk noise) and estimates the amount of each. From this analysis we find that the random-walk noise level averages about 1.3 mm/Vyr and that our estimates of the white noise component confirm theoretical limitations of the measurement technique. In addition, the seasonal noise can be as large as 3 mm in amplitude but typically is less than 0.5 mm. Because of the presence of random-walk noise in these time series, modeling and interpretation of the geodetic data must account for this source of error. By way of example we show that estimating the time-varying strain tensor (a form of spatial averaging) from geodetic data having both random-walk and white noise error components results in seemingly significant variations in the rate of strain accumulation; spatial averaging does reduce the size of both noise components but not their relative influence on the resulting strain accumulation model. Copyright 1997 by the American Geophysical Union.

A new stochastic algorithm for inversion of dust aerosol size distribution

NASA Astrophysics Data System (ADS)

Wang, Li; Li, Feng; Yang, Ma-ying

2015-08-01

Dust aerosol size distribution is an important source of information about atmospheric aerosols, and it can be determined from multiwavelength extinction measurements. This paper describes a stochastic inverse technique based on artificial bee colony (ABC) algorithm to invert the dust aerosol size distribution by light extinction method. The direct problems for the size distribution of water drop and dust particle, which are the main elements of atmospheric aerosols, are solved by the Mie theory and the Lambert-Beer Law in multispectral region. And then, the parameters of three widely used functions, i.e. the log normal distribution (L-N), the Junge distribution (J-J), and the normal distribution (N-N), which can provide the most useful representation of aerosol size distributions, are inversed by the ABC algorithm in the dependent model. Numerical results show that the ABC algorithm can be successfully applied to recover the aerosol size distribution with high feasibility and reliability even in the presence of random noise.

Listening to the noise: random fluctuations reveal gene network parameters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Munsky, Brian; Khammash, Mustafa

2009-01-01

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

GPR random noise reduction using BPD and EMD

NASA Astrophysics Data System (ADS)

Ostoori, Roya; Goudarzi, Alireza; Oskooi, Behrooz

2018-04-01

Ground-penetrating radar (GPR) exploration is a new high-frequency technology that explores near-surface objects and structures accurately. The high-frequency antenna of the GPR system makes it a high-resolution method compared to other geophysical methods. The frequency range of recorded GPR is so wide that random noise recording is inevitable due to acquisition. This kind of noise comes from unknown sources and its correlation to the adjacent traces is nearly zero. This characteristic of random noise along with the higher accuracy of GPR system makes denoising very important for interpretable results. The main objective of this paper is to reduce GPR random noise based on pursuing denoising using empirical mode decomposition. Our results showed that empirical mode decomposition in combination with basis pursuit denoising (BPD) provides satisfactory outputs due to the sifting process compared to the time-domain implementation of the BPD method on both synthetic and real examples. Our results demonstrate that because of the high computational costs, the BPD-empirical mode decomposition technique should only be used for heavily noisy signals.

A Markov model for the temporal dynamics of balanced random networks of finite size

PubMed Central

Lagzi, Fereshteh; Rotter, Stefan

2014-01-01

The balanced state of recurrent networks of excitatory and inhibitory spiking neurons is characterized by fluctuations of population activity about an attractive fixed point. Numerical simulations show that these dynamics are essentially nonlinear, and the intrinsic noise (self-generated fluctuations) in networks of finite size is state-dependent. Therefore, stochastic differential equations with additive noise of fixed amplitude cannot provide an adequate description of the stochastic dynamics. The noise model should, rather, result from a self-consistent description of the network dynamics. Here, we consider a two-state Markovian neuron model, where spikes correspond to transitions from the active state to the refractory state. Excitatory and inhibitory input to this neuron affects the transition rates between the two states. The corresponding nonlinear dependencies can be identified directly from numerical simulations of networks of leaky integrate-and-fire neurons, discretized at a time resolution in the sub-millisecond range. Deterministic mean-field equations, and a noise component that depends on the dynamic state of the network, are obtained from this model. The resulting stochastic model reflects the behavior observed in numerical simulations quite well, irrespective of the size of the network. In particular, a strong temporal correlation between the two populations, a hallmark of the balanced state in random recurrent networks, are well represented by our model. Numerical simulations of such networks show that a log-normal distribution of short-term spike counts is a property of balanced random networks with fixed in-degree that has not been considered before, and our model shares this statistical property. Furthermore, the reconstruction of the flow from simulated time series suggests that the mean-field dynamics of finite-size networks are essentially of Wilson-Cowan type. We expect that this novel nonlinear stochastic model of the interaction between neuronal populations also opens new doors to analyze the joint dynamics of multiple interacting networks. PMID:25520644

The statistical mechanics of relativistic orbits around a massive black hole

NASA Astrophysics Data System (ADS)

Bar-Or, Ben; Alexander, Tal

2014-12-01

Stars around a massive black hole (MBH) move on nearly fixed Keplerian orbits, in a centrally-dominated potential. The random fluctuations of the discrete stellar background cause small potential perturbations, which accelerate the evolution of orbital angular momentum by resonant relaxation. This drives many phenomena near MBHs, such as extreme mass-ratio gravitational wave inspirals, the warping of accretion disks, and the formation of exotic stellar populations. We present here a formal statistical mechanics framework to analyze such systems, where the background potential is described as a correlated Gaussian noise. We derive the leading order, phase-averaged 3D stochastic Hamiltonian equations of motion, for evolving the orbital elements of a test star, and obtain the effective Fokker-Planck equation for a general correlated Gaussian noise, for evolving the stellar distribution function. We show that the evolution of angular momentum depends critically on the temporal smoothness of the background potential fluctuations. Smooth noise has a maximal variability frequency {{ν }max }. We show that in the presence of such noise, the evolution of the normalized angular momentum j=\\sqrt{1-{{e}2}} of a relativistic test star, undergoing Schwarzschild (in-plane) general relativistic precession with frequency {{ν }GR}/{{j}2}, is exponentially suppressed for j\\lt {{j}b}, where {{ν }GR}/jb2˜ {{ν }max }, due to the adiabatic invariance of the precession against the slowly varying random background torques. This results in an effective Schwarzschild precession-induced barrier in angular momentum. When jb is large enough, this barrier can have significant dynamical implications for processes near the MBH.

1 / f α noise and generalized diffusion in random Heisenberg spin systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agarwal, Kartiek; Demler, Eugene; Martin, Ivar

2015-11-01

We study the “flux-noise” spectrum of random-bond quantum Heisenberg spin systems using a real-space renormalization group (RSRG) procedure that accounts for both the renormalization of the system Hamiltonian and of a generic probe that measures the noise. For spin chains, we find that the dynamical structure factor Sq (f ), at finite wave vector q, exhibits a power-law behavior both at high and low frequencies f , with exponents that are connected to one another and to an anomalous dynamical exponent through relations that differ at T = 0 and T =∞. The low-frequency power-law behavior of the structure factormore » is inherited by any generic probe with a finite bandwidth and is of the form 1/f α with 0.5 < α < 1. An analytical calculation of the structure factor, assuming a limiting distribution of the RG flow parameters (spin size, length, bond strength) confirms numerical findings.More generally, we demonstrate that this form of the structure factor, at high temperatures, is a manifestation of anomalous diffusionwhich directly follows from a generalized spin-diffusion propagator.We also argue that 1/f -noise is intimately connected to many-body-localization at finite temperatures. In two dimensions, the RG procedure is less reliable; however, it becomes convergent for quasi-one-dimensional geometries where we find that one-dimensional 1/f α behavior is recovered at low frequencies; the latter configurations are likely representative of paramagnetic spin networks that produce 1/f α noise in SQUIDs.« less

A computer program to predict rotor rotational noise of a stationary rotor from blade loading coefficient

NASA Technical Reports Server (NTRS)

Ramakrishnan, R.; Randall, D.; Hosier, R. N.

1976-01-01

The programing language used is FORTRAN IV. A description of all main and subprograms is provided so that any user possessing a FORTRAN compiler and random access capability can adapt the program to his facility. Rotor blade surface-pressure spectra can be used by the program to calculate: (1) blade station loading spectra, (2) chordwise and/or spanwise integrated blade-loading spectra, and (3) far-field rotational noise spectra. Any of five standard inline functions describing the chordwise distribution of the blade loading can be chosen in order to study parametrically the acoustic predictions. The program output consists of both printed and graphic descriptions of the blade-loading coefficient spectra and far-field acoustic spectrum. The results may also be written on binary file for future processing. Examples of the application of the program along with a description of the rotational noise prediction theory on which the program is based are also provided.

Robust Framework to Combine Diverse Classifiers Assigning Distributed Confidence to Individual Classifiers at Class Level

PubMed Central

Arshad, Sannia; Rho, Seungmin

2014-01-01

We have presented a classification framework that combines multiple heterogeneous classifiers in the presence of class label noise. An extension of m-Mediods based modeling is presented that generates model of various classes whilst identifying and filtering noisy training data. This noise free data is further used to learn model for other classifiers such as GMM and SVM. A weight learning method is then introduced to learn weights on each class for different classifiers to construct an ensemble. For this purpose, we applied genetic algorithm to search for an optimal weight vector on which classifier ensemble is expected to give the best accuracy. The proposed approach is evaluated on variety of real life datasets. It is also compared with existing standard ensemble techniques such as Adaboost, Bagging, and Random Subspace Methods. Experimental results show the superiority of proposed ensemble method as compared to its competitors, especially in the presence of class label noise and imbalance classes. PMID:25295302

Robust framework to combine diverse classifiers assigning distributed confidence to individual classifiers at class level.

PubMed

Khalid, Shehzad; Arshad, Sannia; Jabbar, Sohail; Rho, Seungmin

2014-01-01

We have presented a classification framework that combines multiple heterogeneous classifiers in the presence of class label noise. An extension of m-Mediods based modeling is presented that generates model of various classes whilst identifying and filtering noisy training data. This noise free data is further used to learn model for other classifiers such as GMM and SVM. A weight learning method is then introduced to learn weights on each class for different classifiers to construct an ensemble. For this purpose, we applied genetic algorithm to search for an optimal weight vector on which classifier ensemble is expected to give the best accuracy. The proposed approach is evaluated on variety of real life datasets. It is also compared with existing standard ensemble techniques such as Adaboost, Bagging, and Random Subspace Methods. Experimental results show the superiority of proposed ensemble method as compared to its competitors, especially in the presence of class label noise and imbalance classes.

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

NASA Astrophysics Data System (ADS)

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.

Poisson-Gaussian Noise Analysis and Estimation for Low-Dose X-ray Images in the NSCT Domain.

PubMed

Lee, Sangyoon; Lee, Min Seok; Kang, Moon Gi

2018-03-29

The noise distribution of images obtained by X-ray sensors in low-dosage situations can be analyzed using the Poisson and Gaussian mixture model. Multiscale conversion is one of the most popular noise reduction methods used in recent years. Estimation of the noise distribution of each subband in the multiscale domain is the most important factor in performing noise reduction, with non-subsampled contourlet transform (NSCT) representing an effective method for scale and direction decomposition. In this study, we use artificially generated noise to analyze and estimate the Poisson-Gaussian noise of low-dose X-ray images in the NSCT domain. The noise distribution of the subband coefficients is analyzed using the noiseless low-band coefficients and the variance of the noisy subband coefficients. The noise-after-transform also follows a Poisson-Gaussian distribution, and the relationship between the noise parameters of the subband and the full-band image is identified. We then analyze noise of actual images to validate the theoretical analysis. Comparison of the proposed noise estimation method with an existing noise reduction method confirms that the proposed method outperforms traditional methods.

Poisson–Gaussian Noise Analysis and Estimation for Low-Dose X-ray Images in the NSCT Domain

PubMed Central

Lee, Sangyoon; Lee, Min Seok; Kang, Moon Gi

2018-01-01

The noise distribution of images obtained by X-ray sensors in low-dosage situations can be analyzed using the Poisson and Gaussian mixture model. Multiscale conversion is one of the most popular noise reduction methods used in recent years. Estimation of the noise distribution of each subband in the multiscale domain is the most important factor in performing noise reduction, with non-subsampled contourlet transform (NSCT) representing an effective method for scale and direction decomposition. In this study, we use artificially generated noise to analyze and estimate the Poisson–Gaussian noise of low-dose X-ray images in the NSCT domain. The noise distribution of the subband coefficients is analyzed using the noiseless low-band coefficients and the variance of the noisy subband coefficients. The noise-after-transform also follows a Poisson–Gaussian distribution, and the relationship between the noise parameters of the subband and the full-band image is identified. We then analyze noise of actual images to validate the theoretical analysis. Comparison of the proposed noise estimation method with an existing noise reduction method confirms that the proposed method outperforms traditional methods. PMID:29596335

Noise reduction of a composite cylinder subjected to random acoustic excitation

NASA Technical Reports Server (NTRS)

Grosveld, Ferdinand W.; Beyer, T.

1989-01-01

Interior and exterior noise measurements were conducted on a stiffened composite floor-equipped cylinder, with and without an interior trim installed. Noise reduction was obtained for the case of random acoustic excitation in a diffuse field; the frequency range of interest was 100-800-Hz one-third octave bands. The measured data were compared with noise reduction predictions from the Propeller Aircraft Interior Noise (PAIN) program and from a statistical energy analysis. Structural model parameters were not predicted well by the PAIN program for the given input parameters; this resulted in incorrect noise reduction predictions for the lower one-third octave bands where the power flow into the interior of the cylinder was predicted on a mode-per-mode basis.

Effect of noise on defect chaos in a reaction-diffusion model.

PubMed

Wang, Hongli; Ouyang, Qi

2005-06-01

The influence of noise on defect chaos due to breakup of spiral waves through Doppler and Eckhaus instabilities is investigated numerically with a modified Fitzhugh-Nagumo model. By numerical simulations we show that the noise can drastically enhance the creation and annihilation rates of topological defects. The noise-free probability distribution function for defects in this model is found not to fit with the previously reported squared-Poisson distribution. Under the influence of noise, the distributions are flattened, and can fit with the squared-Poisson or the modified-Poisson distribution. The defect lifetime and diffusive property of defects under the influence of noise are also checked in this model.

Multivariate η-μ fading distribution with arbitrary correlation model

NASA Astrophysics Data System (ADS)

Ghareeb, Ibrahim; Atiani, Amani

2018-03-01

An extensive analysis for the multivariate ? distribution with arbitrary correlation is presented, where novel analytical expressions for the multivariate probability density function, cumulative distribution function and moment generating function (MGF) of arbitrarily correlated and not necessarily identically distributed ? power random variables are derived. Also, this paper provides exact-form expression for the MGF of the instantaneous signal-to-noise ratio at the combiner output in a diversity reception system with maximal-ratio combining and post-detection equal-gain combining operating in slow frequency nonselective arbitrarily correlated not necessarily identically distributed ?-fading channels. The average bit error probability of differentially detected quadrature phase shift keying signals with post-detection diversity reception system over arbitrarily correlated and not necessarily identical fading parameters ?-fading channels is determined by using the MGF-based approach. The effect of fading correlation between diversity branches, fading severity parameters and diversity level is studied.

Method for removal of random noise in eddy-current testing system

DOEpatents

Levy, Arthur J.

1995-01-01

Eddy-current response voltages, generated during inspection of metallic structures for anomalies, are often replete with noise. Therefore, analysis of the inspection data and results is difficult or near impossible, resulting in inconsistent or unreliable evaluation of the structure. This invention processes the eddy-current response voltage, removing the effect of random noise, to allow proper identification of anomalies within and associated with the structure.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Okura, Yuki; Futamase, Toshifumi, E-mail: yuki.okura@nao.ac.jp, E-mail: tof@astr.tohoku.ac.jp

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,more » 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 {nu} {approx} 11.7.« less

Image enhancement by spectral-error correction for dual-energy computed tomography.

PubMed

Park, Kyung-Kook; Oh, Chang-Hyun; Akay, Metin

2011-01-01

Dual-energy CT (DECT) was reintroduced recently to use the additional spectral information of X-ray attenuation and aims for accurate density measurement and material differentiation. However, the spectral information lies in the difference between low and high energy images or measurements, so that it is difficult to acquire accurate spectral information due to amplification of high pixel noise in the resulting difference image. In this work, an image enhancement technique for DECT is proposed, based on the fact that the attenuation of a higher density material decreases more rapidly as X-ray energy increases. We define as spectral error the case when a pixel pair of low and high energy images deviates far from the expected attenuation trend. After analyzing the spectral-error sources of DECT images, we propose a DECT image enhancement method, which consists of three steps: water-reference offset correction, spectral-error correction, and anti-correlated noise reduction. It is the main idea of this work that makes spectral errors distributed like random noise over the true attenuation and suppressed by the well-known anti-correlated noise reduction. The proposed method suppressed noise of liver lesions and improved contrast between liver lesions and liver parenchyma in DECT contrast-enhanced abdominal images and their two-material decomposition.

Leader-Follower Formation Control of UUVs with Model Uncertainties, Current Disturbances, and Unstable Communication

PubMed Central

Yan, Zheping; Xu, Da; Chen, Tao; Zhang, Wei; Liu, Yibo

2018-01-01

Unmanned underwater vehicles (UUVs) have rapidly developed as mobile sensor networks recently in the investigation, survey, and exploration of the underwater environment. The goal of this paper is to develop a practical and efficient formation control method to improve work efficiency of multi-UUV sensor networks. Distributed leader-follower formation controllers are designed based on a state feedback and consensus algorithm. Considering that each vehicle is subject to model uncertainties and current disturbances, a second-order integral UUV model with a nonlinear function is established using the state feedback linearized method under current disturbances. For unstable communication among UUVs, communication failure and acoustic link noise interference are considered. Two-layer random switching communication topologies are proposed to solve the problem of communication failure. For acoustic link noise interference, accurate representation of valid communication information and noise stripping when designing controllers is necessary. Effective communication topology weights are designed to represent the validity of communication information interfered by noise. Utilizing state feedback and noise stripping, sufficient conditions for design formation controllers are proposed to ensure UUV formation achieves consensus under model uncertainties, current disturbances, and unstable communication. The stability of formation controllers is proven by the Lyapunov-Razumikhin theorem, and the validity is verified by simulation results. PMID:29473919

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

PubMed

Torres, E B; Denisova, K

2016-11-21

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

Ultrasound introscopic image quantitative characteristics for medical diagnosis

NASA Astrophysics Data System (ADS)

Novoselets, Mikhail K.; Sarkisov, Sergey S.; Gridko, Alexander N.; Tcheban, Anatoliy K.

1993-09-01

The results on computer aided extraction of quantitative characteristics (QC) of ultrasound introscopic images for medical diagnosis are presented. Thyroid gland (TG) images of Chernobil Accident sufferers are considered. It is shown that TG diseases can be associated with some values of selected QCs of random echo distribution in the image. The possibility of these QCs usage for TG diseases recognition in accordance with calculated values is analyzed. The role of speckle noise elimination in the solution of the problem on TG diagnosis is considered too.

Coverage dependent molecular assembly of anthraquinone on Au(111)

NASA Astrophysics Data System (ADS)

DeLoach, Andrew S.; Conrad, Brad R.; Einstein, T. L.; Dougherty, Daniel B.

2017-11-01

A scanning tunneling microscopy study of anthraquinone (AQ) on the Au(111) surface shows that the molecules self-assemble into several structures depending on the local surface coverage. At high coverages, a close-packed saturated monolayer is observed, while at low coverages, mobile surface molecules coexist with stable chiral hexamer clusters. At intermediate coverages, a disordered 2D porous network interlinking close-packed islands is observed in contrast to the giant honeycomb networks observed for the same molecule on Cu(111). This difference verifies the predicted extreme sensitivity [J. Wyrick et al., Nano Lett. 11, 2944 (2011)] of the pore network to small changes in the surface electronic structure. Quantitative analysis of the 2D pore network reveals that the areas of the vacancy islands are distributed log-normally. Log-normal distributions are typically associated with the product of random variables (multiplicative noise), and we propose that the distribution of pore sizes for AQ on Au(111) originates from random linear rate constants for molecules to either desorb from the surface or detach from the region of a nucleated pore.

Coverage dependent molecular assembly of anthraquinone on Au(111).

PubMed

DeLoach, Andrew S; Conrad, Brad R; Einstein, T L; Dougherty, Daniel B

2017-11-14

A scanning tunneling microscopy study of anthraquinone (AQ) on the Au(111) surface shows that the molecules self-assemble into several structures depending on the local surface coverage. At high coverages, a close-packed saturated monolayer is observed, while at low coverages, mobile surface molecules coexist with stable chiral hexamer clusters. At intermediate coverages, a disordered 2D porous network interlinking close-packed islands is observed in contrast to the giant honeycomb networks observed for the same molecule on Cu(111). This difference verifies the predicted extreme sensitivity [J. Wyrick et al., Nano Lett. 11, 2944 (2011)] of the pore network to small changes in the surface electronic structure. Quantitative analysis of the 2D pore network reveals that the areas of the vacancy islands are distributed log-normally. Log-normal distributions are typically associated with the product of random variables (multiplicative noise), and we propose that the distribution of pore sizes for AQ on Au(111) originates from random linear rate constants for molecules to either desorb from the surface or detach from the region of a nucleated pore.

Evaluation of noise limits to improve image processing in soft X-ray projection microscopy.

PubMed

Jamsranjav, Erdenetogtokh; Kuge, Kenichi; Ito, Atsushi; Kinjo, Yasuhito; Shiina, Tatsuo

2017-03-03

Soft X-ray microscopy has been developed for high resolution imaging of hydrated biological specimens due to the availability of water window region. In particular, a projection type microscopy has advantages in wide viewing area, easy zooming function and easy extensibility to computed tomography (CT). The blur of projection image due to the Fresnel diffraction of X-rays, which eventually reduces spatial resolution, could be corrected by an iteration procedure, i.e., repetition of Fresnel and inverse Fresnel transformations. However, it was found that the correction is not enough to be effective for all images, especially for images with low contrast. In order to improve the effectiveness of image correction by computer processing, we in this study evaluated the influence of background noise in the iteration procedure through a simulation study. In the study, images of model specimen with known morphology were used as a substitute for the chromosome images, one of the targets of our microscope. Under the condition that artificial noise was distributed on the images randomly, we introduced two different parameters to evaluate noise effects according to each situation where the iteration procedure was not successful, and proposed an upper limit of the noise within which the effective iteration procedure for the chromosome images was possible. The study indicated that applying the new simulation and noise evaluation method was useful for image processing where background noises cannot be ignored compared with specimen images.

Shaping the spectrum of random-phase radar waveforms

DOEpatents

Doerry, Armin W.; Marquette, Brandeis

2017-05-09

The various technologies presented herein relate to generation of a desired waveform profile in the form of a spectrum of apparently random noise (e.g., white noise or colored noise), but with precise spectral characteristics. Hence, a waveform profile that could be readily determined (e.g., by a spoofing system) is effectively obscured. Obscuration is achieved by dividing the waveform into a series of chips, each with an assigned frequency, wherein the sequence of chips are subsequently randomized. Randomization can be a function of the application of a key to the chip sequence. During processing of the echo pulse, a copy of the randomized transmitted pulse is recovered or regenerated against which the received echo is correlated. Hence, with the echo energy range-compressed in this manner, it is possible to generate a radar image with precise impulse response.

Noise effects on entanglement distribution by separable state

NASA Astrophysics Data System (ADS)

Bordbar, Najmeh Tabe; Memarzadeh, Laleh

2018-02-01

We investigate noise effects on the performance of entanglement distribution by separable state. We consider a realistic situation in which the mediating particle between two distant nodes of the network goes through a noisy channel. For a large class of noise models, we show that the average value of distributed entanglement between two parties is equal to entanglement between particular bipartite partitions of target qubits and exchange qubit in intermediate steps of the protocol. This result is valid for distributing two-qubit/qudit and three-qubit entangled states. In explicit examples of the noise family, we show that there exists a critical value of noise parameter beyond which distribution of distillable entanglement is not possible. Furthermore, we determine how this critical value increases in terms of Hilbert space dimension, when distributing d-dimensional Bell states.

Robust random telegraph conductivity noise in single crystals of the ferromagnetic insulating manganite La0.86Ca0.14MnO3

NASA Astrophysics Data System (ADS)

Przybytek, J.; Fink-Finowicki, J.; Puźniak, R.; Shames, A.; Markovich, V.; Mogilyansky, D.; Jung, G.

2017-03-01

Robust random telegraph conductivity fluctuations have been observed in La0.86Ca0.14MnO3 manganite single crystals. At room temperatures, the spectra of conductivity fluctuations are featureless and follow a 1 /f shape in the entire experimental frequency and bias range. Upon lowering the temperature, clear Lorentzian bias-dependent excess noise appears on the 1 /f background and eventually dominates the spectral behavior. In the time domain, fully developed Lorentzian noise appears as pronounced two-level random telegraph noise with a thermally activated switching rate, which does not depend on bias current and applied magnetic field. The telegraph noise is very robust and persists in the exceptionally wide temperature range of more than 50 K. The amplitude of the telegraph noise decreases exponentially with increasing bias current in exactly the same manner as the sample resistance increases with the current, pointing out the dynamic current redistribution between percolation paths dominated by phase-separated clusters with different conductivity as a possible origin of two-level conductivity fluctuations.

Correlative weighted stacking for seismic data in the wavelet domain

USGS Publications Warehouse

Zhang, S.; Xu, Y.; Xia, J.; ,

2004-01-01

Horizontal stacking plays a crucial role for modern seismic data processing, for it not only compresses random noise and multiple reflections, but also provides a foundational data for subsequent migration and inversion. However, a number of examples showed that random noise in adjacent traces exhibits correlation and coherence. The average stacking and weighted stacking based on the conventional correlative function all result in false events, which are caused by noise. Wavelet transform and high order statistics are very useful methods for modern signal processing. The multiresolution analysis in wavelet theory can decompose signal on difference scales, and high order correlative function can inhibit correlative noise, for which the conventional correlative function is of no use. Based on the theory of wavelet transform and high order statistics, high order correlative weighted stacking (HOCWS) technique is presented in this paper. Its essence is to stack common midpoint gathers after the normal moveout correction by weight that is calculated through high order correlative statistics in the wavelet domain. Synthetic examples demonstrate its advantages in improving the signal to noise (S/N) ration and compressing the correlative random noise.

Bird's-eye view on noise-based logic.

PubMed

Kish, Laszlo B; Granqvist, Claes G; Horvath, Tamas; Klappenecker, Andreas; Wen, He; Bezrukov, Sergey M

2014-01-01

Noise-based logic is a practically deterministic logic scheme inspired by the randomness of neural spikes and uses a system of uncorrelated stochastic processes and their superposition to represent the logic state. We briefly discuss various questions such as ( i ) What does practical determinism mean? ( ii ) Is noise-based logic a Turing machine? ( iii ) Is there hope to beat (the dreams of) quantum computation by a classical physical noise-based processor, and what are the minimum hardware requirements for that? Finally, ( iv ) we address the problem of random number generators and show that the common belief that quantum number generators are superior to classical (thermal) noise-based generators is nothing but a myth.

Bird's-eye view on noise-based logic

NASA Astrophysics Data System (ADS)

Kish, Laszlo B.; Granqvist, Claes G.; Horvath, Tamas; Klappenecker, Andreas; Wen, He; Bezrukov, Sergey M.

2014-09-01

Noise-based logic is a practically deterministic logic scheme inspired by the randomness of neural spikes and uses a system of uncorrelated stochastic processes and their superposition to represent the logic state. We briefly discuss various questions such as (i) What does practical determinism mean? (ii) Is noise-based logic a Turing machine? (iii) Is there hope to beat (the dreams of) quantum computation by a classical physical noise-based processor, and what are the minimum hardware requirements for that? Finally, (iv) we address the problem of random number generators and show that the common belief that quantum number generators are superior to classical (thermal) noise-based generators is nothing but a myth.

Record statistics of a strongly correlated time series: random walks and Lévy flights

NASA Astrophysics Data System (ADS)

Godrèche, Claude; Majumdar, Satya N.; Schehr, Grégory

2017-08-01

We review recent advances on the record statistics of strongly correlated time series, whose entries denote the positions of a random walk or a Lévy flight on a line. After a brief survey of the theory of records for independent and identically distributed random variables, we focus on random walks. During the last few years, it was indeed realized that random walks are a very useful ‘laboratory’ to test the effects of correlations on the record statistics. We start with the simple one-dimensional random walk with symmetric jumps (both continuous and discrete) and discuss in detail the statistics of the number of records, as well as of the ages of the records, i.e. the lapses of time between two successive record breaking events. Then we review the results that were obtained for a wide variety of random walk models, including random walks with a linear drift, continuous time random walks, constrained random walks (like the random walk bridge) and the case of multiple independent random walkers. Finally, we discuss further observables related to records, like the record increments, as well as some questions raised by physical applications of record statistics, like the effects of measurement error and noise.

The deterministic chaos and random noise in turbulent jet

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yao, Tian-Liang; Shanghai Institute of Space Propulsion, Shanghai 201112; Shanghai Engineering Research Center of Space Engine, Shanghai Institute of Space Propulsion, Shanghai 201112

2014-06-01

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 proportionalitymore » 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.« less

Maximum-Entropy Inference with a Programmable Annealer

PubMed Central

Chancellor, Nicholas; Szoke, Szilard; Vinci, Walter; Aeppli, Gabriel; Warburton, Paul A.

2016-01-01

Optimisation problems typically involve finding the ground state (i.e. the minimum energy configuration) of a cost function with respect to many variables. If the variables are corrupted by noise then this maximises the likelihood that the solution is correct. The maximum entropy solution on the other hand takes the form of a Boltzmann distribution over the ground and excited states of the cost function to correct for noise. Here we use a programmable annealer for the information decoding problem which we simulate as a random Ising model in a field. We show experimentally that finite temperature maximum entropy decoding can give slightly better bit-error-rates than the maximum likelihood approach, confirming that useful information can be extracted from the excited states of the annealer. Furthermore we introduce a bit-by-bit analytical method which is agnostic to the specific application and use it to show that the annealer samples from a highly Boltzmann-like distribution. Machines of this kind are therefore candidates for use in a variety of machine learning applications which exploit maximum entropy inference, including language processing and image recognition. PMID:26936311

Phase characterization of oscillatory components of the cerebral concentrations of oxy-hemoglobin and deoxy-hemoglobin

NASA Astrophysics Data System (ADS)

Pierro, Michele; Sassaroli, Angelo; Zheng, Feng; Fantini, Sergio

2011-02-01

We present a study of the relative phase of oscillations of cerebral oxy- and deoxy-hemoglobin concentrations in the low-frequency range, namely 0.04-0.12 Hz. We have characterized the potential contributions of noise to the measured phase distributions, and we have performed phase measurements on the brain of a human subject at rest, and on the brain of a human subject during stage I sleep. While phase distributions of pseudo hemodynamic oscillations generated from noise (obtained by applying to two independent sets of random numbers the same linear transformation that converts absorption coefficients at 690 and 830 nm into concentrations of oxy- and deoxy-hemoglobin) are peaked at 180º, those associated with real hemodynamic changes can be peaked around any value depending on the underlying physiology and hemodynamics. In particular, preliminary results reported here indicate a greater phase lead of deoxy-hemoglobin vs. oxy-hemoglobin low-frequency oscillations during stage I sleep (82º +/- 55º) than while the subject is awake (19º +/- 58º).

Estimating the signal-to-noise ratio of AVIRIS data

NASA Technical Reports Server (NTRS)

Curran, Paul J.; Dungan, Jennifer L.

1988-01-01

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

Transcranial Random Noise Stimulation of Visual Cortex: Stochastic Resonance Enhances Central Mechanisms of Perception.

PubMed

van der Groen, Onno; Wenderoth, Nicole

2016-05-11

Random noise enhances the detectability of weak signals in nonlinear systems, a phenomenon known as stochastic resonance (SR). Though counterintuitive at first, SR has been demonstrated in a variety of naturally occurring processes, including human perception, where it has been shown that adding noise directly to weak visual, tactile, or auditory stimuli enhances detection performance. These results indicate that random noise can push subthreshold receptor potentials across the transfer threshold, causing action potentials in an otherwise silent afference. Despite the wealth of evidence demonstrating SR for noise added to a stimulus, relatively few studies have explored whether or not noise added directly to cortical networks enhances sensory detection. Here we administered transcranial random noise stimulation (tRNS; 100-640 Hz zero-mean Gaussian white noise) to the occipital region of human participants. For increasing tRNS intensities (ranging from 0 to 1.5 mA), the detection accuracy of a visual stimuli changed according to an inverted-U-shaped function, typical of the SR phenomenon. When the optimal level of noise was added to visual cortex, detection performance improved significantly relative to a zero noise condition (9.7 ± 4.6%) and to a similar extent as optimal noise added to the visual stimuli (11.2 ± 4.7%). Our results demonstrate that adding noise to cortical networks can improve human behavior and that tRNS is an appropriate tool to exploit this mechanism. Our findings suggest that neural processing at the network level exhibits nonlinear system properties that are sensitive to the stochastic resonance phenomenon and highlight the usefulness of tRNS as a tool to modulate human behavior. Since tRNS can be applied to all cortical areas, exploiting the SR phenomenon is not restricted to the perceptual domain, but can be used for other functions that depend on nonlinear neural dynamics (e.g., decision making, task switching, response inhibition, and many other processes). This will open new avenues for using tRNS to investigate brain function and enhance the behavior of healthy individuals or patients. Copyright © 2016 the authors 0270-6474/16/365289-10$15.00/0.

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

PubMed Central

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

2016-01-01

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. PMID:27258276

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

PubMed

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.

Oscillations and chaos in neural networks: an exactly solvable model.

PubMed Central

Wang, L P; Pichler, E E; Ross, J

1990-01-01

We consider a randomly diluted higher-order network with noise, consisting of McCulloch-Pitts neurons that interact by Hebbian-type connections. For this model, exact dynamical equations are derived and solved for both parallel and random sequential updating algorithms. For parallel dynamics, we find a rich spectrum of different behaviors including static retrieving and oscillatory and chaotic phenomena in different parts of the parameter space. The bifurcation parameters include first- and second-order neuronal interaction coefficients and a rescaled noise level, which represents the combined effects of the random synaptic dilution, interference between stored patterns, and additional background noise. We show that a marked difference in terms of the occurrence of oscillations or chaos exists between neural networks with parallel and random sequential dynamics. Images PMID:2251287

Autocorrelation peaks in congruential pseudorandom number generators

NASA Technical Reports Server (NTRS)

Neuman, F.; Merrick, R. B.

1976-01-01

The complete correlation structure of several congruential pseudorandom number generators (PRNG) of the same type and small cycle length was studied to deal with the problem of congruential PRNG almost repeating themselves at intervals smaller than their cycle lengths, during simulation of bandpass filtered normal random noise. Maximum period multiplicative and mixed congruential generators were studied, with inferences drawn from examination of several tractable members of a class of random number generators, and moduli from 2 to the 5th power to 2 to the 9th power. High correlation is shown to exist in mixed and multiplicative congruential random number generators and prime moduli Lehmer generators for shifts a fraction of their cycle length. The random noise sequences in question are required when simulating electrical noise, air turbulence, or time variation of wind parameters.

An airport community noise-impact assessment model

NASA Technical Reports Server (NTRS)

Deloach, R.

1980-01-01

A computer model was developed to assess the noise impact of an airport on the community which it serves. Assessments are made using the Fractional Impact Method by which a single number describes the community aircraft noise environment in terms of exposed population and multiple event noise level. The model is comprised of three elements: a conventional noise footprint model, a site specific population distribution model, and a dose response transfer function. The footprint model provides the noise distribution for a given aircraft operating scenario. This is combined with the site specific population distribution obtained from a national census data base to yield the number of residents exposed to a given level of noise. The dose response relationship relates noise exposure levels to the percentage of individuals highly annoyed by those levels.

Noise-enhanced Parametric Resonance in Perturbed Galaxies

NASA Astrophysics Data System (ADS)

Sideris, Ioannis V.; Kandrup, Henry E.

2004-02-01

This paper describes how parametric resonances associated with a galactic potential subjected to relatively low-amplitude, strictly periodic time-dependent perturbations can be impacted by pseudo-random variations in the pulsation frequency, modeled as colored noise. One aim thereby is to allow for the effects of a changing oscillation frequency as the density distribution associated with a galaxy evolves during violent relaxation. Another is to mimic the possible effects of internal substructures, satellite galaxies, and/or a high-density environment. The principal conclusions are that allowing for a variable frequency does not vitiate the effects of parametric resonance, and that, in at least some cases, such variations can increase the overall importance of parametric resonance associated with systematic pulsations. In memory of Professor H. E. Kandrup, a brilliant scientist, excellent teacher, and good friend. His genius and sense of humor will be greatly missed.

Computational wavelength resolution for in-line lensless holography: phase-coded diffraction patterns and wavefront group-sparsity

NASA Astrophysics Data System (ADS)

Katkovnik, Vladimir; Shevkunov, Igor; Petrov, Nikolay V.; Egiazarian, Karen

2017-06-01

In-line lensless holography is considered with a random phase modulation at the object plane. The forward wavefront propagation is modelled using the Fourier transform with the angular spectrum transfer function. The multiple intensities (holograms) recorded by the sensor are random due to the random phase modulation and noisy with Poissonian noise distribution. It is shown by computational experiments that high-accuracy reconstructions can be achieved with resolution going up to the two thirds of the wavelength. With respect to the sensor pixel size it is a super-resolution with a factor of 32. The algorithm designed for optimal superresolution phase/amplitude reconstruction from Poissonian data is based on the general methodology developed for phase retrieval with a pixel-wise resolution in V. Katkovnik, "Phase retrieval from noisy data based on sparse approximation of object phase and amplitude", http://www.cs.tut.fi/ lasip/DDT/index3.html.

Validation of optical codes based on 3D nanostructures

NASA Astrophysics Data System (ADS)

Carnicer, Artur; Javidi, Bahram

2017-05-01

Image information encoding using random phase masks produce speckle-like noise distributions when the sample is propagated in the Fresnel domain. As a result, information cannot be accessed by simple visual inspection. Phase masks can be easily implemented in practice by attaching cello-tape to the plain-text message. Conventional 2D-phase masks can be generalized to 3D by combining glass and diffusers resulting in a more complex, physical unclonable function. In this communication, we model the behavior of a 3D phase mask using a simple approach: light is propagated trough glass using the angular spectrum of plane waves whereas the diffusor is described as a random phase mask and a blurring effect on the amplitude of the propagated wave. Using different designs for the 3D phase mask and multiple samples, we demonstrate that classification is possible using the k-nearest neighbors and random forests machine learning algorithms.

Using Temporal Correlations and Full Distributions to Separate Intrinsic and Extrinsic Fluctuations in Biological Systems

NASA Astrophysics Data System (ADS)

Hilfinger, Andreas; Chen, Mark; Paulsson, Johan

2012-12-01

Studies of stochastic biological dynamics typically compare observed fluctuations to theoretically predicted variances, sometimes after separating the intrinsic randomness of the system from the enslaving influence of changing environments. But variances have been shown to discriminate surprisingly poorly between alternative mechanisms, while for other system properties no approaches exist that rigorously disentangle environmental influences from intrinsic effects. Here, we apply the theory of generalized random walks in random environments to derive exact rules for decomposing time series and higher statistics, rather than just variances. We show for which properties and for which classes of systems intrinsic fluctuations can be analyzed without accounting for extrinsic stochasticity and vice versa. We derive two independent experimental methods to measure the separate noise contributions and show how to use the additional information in temporal correlations to detect multiplicative effects in dynamical systems.

Tapered fiber based Brillouin random fiber laser and its application for linewidth measurement.

PubMed

Gao, Song; Zhang, Liang; Xu, Yanping; Lu, Ping; Chen, Liang; Bao, Xiaoyi

2016-12-12

A one-end pumping Brillouin random fiber laser (BRFL) based on a 5-km tapered fiber (TF) is demonstrated. The enhanced Rayleigh scattering and the increased power density from tapering in the TF provide good directionality and a high degree of coherent feedback. Both the transmitting and TF enhanced Rayleigh scattered pump lights formed effective bi-direction pumping for the Brillouin gain in the standing cavity configuration in the distributed way as the gain and random feedback in the same fiber. The linewidth of the laser shows ~1.17 kHz while the relative intensity noise (RIN) has been verified to be suppressed comparing with that of the two-end pumping of the standard single mode fiber (SMF). Furthermore, utilizing the proposed laser, a high-resolution (~kHz) linewidth measurement method is demonstrated without long delay fiber (>100km) and extra frequency shifter thanks to the acoustic frequency shift from fiber itself.

Stochastic models for regulatory networks of the genetic toggle switch.

PubMed

Tian, Tianhai; Burrage, Kevin

2006-05-30

Bistability arises within a wide range of biological systems from the lambda phage switch in bacteria to cellular signal transduction pathways in mammalian cells. Changes in regulatory mechanisms may result in genetic switching in a bistable system. Recently, more and more experimental evidence in the form of bimodal population distributions indicates that noise plays a very important role in the switching of bistable systems. Although deterministic models have been used for studying the existence of bistability properties under various system conditions, these models cannot realize cell-to-cell fluctuations in genetic switching. However, there is a lag in the development of stochastic models for studying the impact of noise in bistable systems because of the lack of detailed knowledge of biochemical reactions, kinetic rates, and molecular numbers. In this work, we develop a previously undescribed general technique for developing quantitative stochastic models for large-scale genetic regulatory networks by introducing Poisson random variables into deterministic models described by ordinary differential equations. Two stochastic models have been proposed for the genetic toggle switch interfaced with either the SOS signaling pathway or a quorum-sensing signaling pathway, and we have successfully realized experimental results showing bimodal population distributions. Because the introduced stochastic models are based on widely used ordinary differential equation models, the success of this work suggests that this approach is a very promising one for studying noise in large-scale genetic regulatory networks.

Stochastic models for regulatory networks of the genetic toggle switch

PubMed Central

Tian, Tianhai; Burrage, Kevin

2006-01-01

Bistability arises within a wide range of biological systems from the λ phage switch in bacteria to cellular signal transduction pathways in mammalian cells. Changes in regulatory mechanisms may result in genetic switching in a bistable system. Recently, more and more experimental evidence in the form of bimodal population distributions indicates that noise plays a very important role in the switching of bistable systems. Although deterministic models have been used for studying the existence of bistability properties under various system conditions, these models cannot realize cell-to-cell fluctuations in genetic switching. However, there is a lag in the development of stochastic models for studying the impact of noise in bistable systems because of the lack of detailed knowledge of biochemical reactions, kinetic rates, and molecular numbers. In this work, we develop a previously undescribed general technique for developing quantitative stochastic models for large-scale genetic regulatory networks by introducing Poisson random variables into deterministic models described by ordinary differential equations. Two stochastic models have been proposed for the genetic toggle switch interfaced with either the SOS signaling pathway or a quorum-sensing signaling pathway, and we have successfully realized experimental results showing bimodal population distributions. Because the introduced stochastic models are based on widely used ordinary differential equation models, the success of this work suggests that this approach is a very promising one for studying noise in large-scale genetic regulatory networks. PMID:16714385

Crustal and uppermost mantle S-wave velocity structure beneath the Japanese islands from seismic ambient noise tomography

NASA Astrophysics Data System (ADS)

Guo, Zhi; Gao, Xing; Shi, Heng; Wang, Weiming

2013-04-01

In this study, the crustal and uppermost mantle shear wave velocities beneath the Japanese islands have been determined by inversion from seismic ambient noise tomography using data recorded at 75 Full Range Seismograph Network of Japan broad-band seismic stations, which are uniformly distributed across the Japanese islands. By cross-correlating 2 yr of vertical component seismic ambient noise recordings, we are able to extract Rayleigh wave empirical Green's functions, which are subsequently used to measure phase velocity dispersion in the period band of 6-50 s. The dispersion data are then inverted to yield 2-D tomographic phase velocity maps and 3-D shear wave velocity models. Our results show that the velocity variations at short periods (˜10 s), or in the uppermost crust, correlate well with the major known surface geological and tectonic features. In particular, the distribution of low-velocity anomalies shows good spatial correlation with active faults, volcanoes and terrains of sediment exposure, whereas the high-velocity anomalies are mainly associated with the mountain ranges. We also observe that large upper crustal earthquakes (5.0 ≤ M ≤ 8.0, depth ≤ 25 km) mainly occurred in low-velocity anomalies or along the boundary between low- and high-velocity anomalies, suggesting that large upper crustal earthquakes do not strike randomly or uniformly; rather they are inclined to nucleate within or adjacent to low-velocity areas.

Optimal source coding, removable noise elimination, and natural coordinate system construction for general vector sources using replicator neural networks

NASA Astrophysics Data System (ADS)

Hecht-Nielsen, Robert

1997-04-01

A new universal one-chart smooth manifold model for vector information sources is introduced. Natural coordinates (a particular type of chart) for such data manifolds are then defined. Uniformly quantized natural coordinates form an optimal vector quantization code for a general vector source. Replicator neural networks (a specialized type of multilayer perceptron with three hidden layers) are the introduced. As properly configured examples of replicator networks approach minimum mean squared error (e.g., via training and architecture adjustment using randomly chosen vectors from the source), these networks automatically develop a mapping which, in the limit, produces natural coordinates for arbitrary source vectors. The new concept of removable noise (a noise model applicable to a wide variety of real-world noise processes) is then discussed. Replicator neural networks, when configured to approach minimum mean squared reconstruction error (e.g., via training and architecture adjustment on randomly chosen examples from a vector source, each with randomly chosen additive removable noise contamination), in the limit eliminate removable noise and produce natural coordinates for the data vector portions of the noise-corrupted source vectors. Consideration regarding selection of the dimension of a data manifold source model and the training/configuration of replicator neural networks are discussed.

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

NASA Astrophysics Data System (ADS)

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.

Stochastic detecting images from strong noise field in visual communications

NASA Astrophysics Data System (ADS)

Cai, Defu

1991-11-01

Random noise interference in image pick-up and image transmission is an important restriction for vision systems. In this paper, interframe shift sampling (IFSS) transform has been used for diminishing noise interference and detecting weak image signal submerged by strong noise in communication systems.

Visibility graphs of random scalar fields and spatial data

NASA Astrophysics Data System (ADS)

Lacasa, Lucas; Iacovacci, Jacopo

2017-07-01

We extend the family of visibility algorithms to map scalar fields of arbitrary dimension into graphs, enabling the analysis of spatially extended data structures as networks. We introduce several possible extensions and provide analytical results on the topological properties of the graphs associated to different types of real-valued matrices, which can be understood as the high and low disorder limits of real-valued scalar fields. In particular, we find a closed expression for the degree distribution of these graphs associated to uncorrelated random fields of generic dimension. This result holds independently of the field's marginal distribution and it directly yields a statistical randomness test, applicable in any dimension. We showcase its usefulness by discriminating spatial snapshots of two-dimensional white noise from snapshots of a two-dimensional lattice of diffusively coupled chaotic maps, a system that generates high dimensional spatiotemporal chaos. The range of potential applications of this combinatorial framework includes image processing in engineering, the description of surface growth in material science, soft matter or medicine, and the characterization of potential energy surfaces in chemistry, disordered systems, and high energy physics. An illustration on the applicability of this method for the classification of the different stages involved in carcinogenesis is briefly discussed.

Aerodynamic design of a rotor blade for minimum noise radiation

NASA Technical Reports Server (NTRS)

Karamcheti, K.; Yu, Y. H.

1974-01-01

An analysis of the aerodynamic design of a hovering rotor blade for obtaining minimum aerodynamic rotor noise has been carried out. In this analysis, which is based on both acoustical and aerodynamic considerations, attention is given only to the rotational noise due to the pressure fluctuations on the blade surfaces. The lift distribution obtained in this analysis has different characteristics from those of the conventional distribution. The present distribution shows negative lift values over a quarter of the span from the blade tip, and a maximum lift at about the midspan. Results are presented to show that the noise field is considerably affected by the shape of the lift distribution along the blade and that noise reduction of about 5 dB may be obtained by designing the rotor blade to yield minimum noise.

Computational ghost imaging using deep learning

NASA Astrophysics Data System (ADS)

Shimobaba, Tomoyoshi; Endo, Yutaka; Nishitsuji, Takashi; Takahashi, Takayuki; Nagahama, Yuki; Hasegawa, Satoki; Sano, Marie; Hirayama, Ryuji; Kakue, Takashi; Shiraki, Atsushi; Ito, Tomoyoshi

2018-04-01

Computational ghost imaging (CGI) is a single-pixel imaging technique that exploits the correlation between known random patterns and the measured intensity of light transmitted (or reflected) by an object. Although CGI can obtain two- or three-dimensional images with a single or a few bucket detectors, the quality of the reconstructed images is reduced by noise due to the reconstruction of images from random patterns. In this study, we improve the quality of CGI images using deep learning. A deep neural network is used to automatically learn the features of noise-contaminated CGI images. After training, the network is able to predict low-noise images from new noise-contaminated CGI images.

Seismic noise attenuation using an online subspace tracking algorithm

NASA Astrophysics Data System (ADS)

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.

Digital simulation of an arbitrary stationary stochastic process by spectral representation.

PubMed

Yura, Harold T; Hanson, Steen G

2011-04-01

In this paper we present a straightforward, efficient, and computationally fast method for creating a large number of discrete samples with an arbitrary given probability density function and a specified spectral content. The method relies on initially transforming a white noise sample set of random Gaussian distributed numbers into a corresponding set with the desired spectral distribution, after which this colored Gaussian probability distribution is transformed via an inverse transform into the desired probability distribution. In contrast to previous work, where the analyses were limited to auto regressive and or iterative techniques to obtain satisfactory results, we find that a single application of the inverse transform method yields satisfactory results for a wide class of arbitrary probability distributions. Although a single application of the inverse transform technique does not conserve the power spectra exactly, it yields highly accurate numerical results for a wide range of probability distributions and target power spectra that are sufficient for system simulation purposes and can thus be regarded as an accurate engineering approximation, which can be used for wide range of practical applications. A sufficiency condition is presented regarding the range of parameter values where a single application of the inverse transform method yields satisfactory agreement between the simulated and target power spectra, and a series of examples relevant for the optics community are presented and discussed. Outside this parameter range the agreement gracefully degrades but does not distort in shape. Although we demonstrate the method here focusing on stationary random processes, we see no reason why the method could not be extended to simulate non-stationary random processes. © 2011 Optical Society of America

Data-driven probability concentration and sampling on manifold

DOE Office of Scientific and Technical Information (OSTI.GOV)

Soize, C., E-mail: christian.soize@univ-paris-est.fr; Ghanem, R., E-mail: ghanem@usc.edu

2016-09-15

A new methodology is proposed for generating realizations of a random vector with values in a finite-dimensional Euclidean space that are statistically consistent with a dataset of observations of this vector. The probability distribution of this random vector, while a priori not known, is presumed to be concentrated on an unknown subset of the Euclidean space. A random matrix is introduced whose columns are independent copies of the random vector and for which the number of columns is the number of data points in the dataset. The approach is based on the use of (i) the multidimensional kernel-density estimation methodmore » for estimating the probability distribution of the random matrix, (ii) a MCMC method for generating realizations for the random matrix, (iii) the diffusion-maps approach for discovering and characterizing the geometry and the structure of the dataset, and (iv) a reduced-order representation of the random matrix, which is constructed using the diffusion-maps vectors associated with the first eigenvalues of the transition matrix relative to the given dataset. The convergence aspects of the proposed methodology are analyzed and a numerical validation is explored through three applications of increasing complexity. The proposed method is found to be robust to noise levels and data complexity as well as to the intrinsic dimension of data and the size of experimental datasets. Both the methodology and the underlying mathematical framework presented in this paper contribute new capabilities and perspectives at the interface of uncertainty quantification, statistical data analysis, stochastic modeling and associated statistical inverse problems.« less

Analog model for quantum gravity effects: phonons in random fluids.

PubMed

Krein, G; Menezes, G; Svaiter, N F

2010-09-24

We describe an analog model for quantum gravity effects in condensed matter physics. The situation discussed is that of phonons propagating in a fluid with a random velocity wave equation. We consider that there are random fluctuations in the reciprocal of the bulk modulus of the system and study free phonons in the presence of Gaussian colored noise with zero mean. We show that, in this model, after performing the random averages over the noise function a free conventional scalar quantum field theory describing free phonons becomes a self-interacting model.

Cooperation in the noisy case: Prisoner's dilemma game on two types of regular random graphs

NASA Astrophysics Data System (ADS)

Vukov, Jeromos; Szabó, György; Szolnoki, Attila

2006-06-01

We have studied an evolutionary prisoner’s dilemma game with players located on two types of random regular graphs with a degree of 4. The analysis is focused on the effects of payoffs and noise (temperature) on the maintenance of cooperation. When varying the noise level and/or the highest payoff, the system exhibits a second-order phase transition from a mixed state of cooperators and defectors to an absorbing state where only defectors remain alive. For the random regular graph (and Bethe lattice) the behavior of the system is similar to those found previously on the square lattice with nearest neighbor interactions, although the measure of cooperation is enhanced by the absence of loops in the connectivity structure. For low noise the optimal connectivity structure is built up from randomly connected triangles.

The effect of shot noise on the start up of the fundamental and harmonics in free-electron lasers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Freund, H. P.; Miner, W. H. Jr.; Giannessi, L.

2008-12-15

The problem of radiation start up in free-electron lasers (FELs) is important in the simulation of virtually all FEL configurations including oscillators and amplifiers in both seeded master oscillator power amplifier (MOPA) and self-amplified spontaneous emission (SASE) modes. Both oscillators and SASE FELs start up from spontaneous emission due to shot noise on the electron beam, which arises from the random fluctuations in the phase distribution of the electrons. The injected power in a MOPA is usually large enough to overwhelm the shot noise. However, this noise must be treated correctly in order to model the initial start up ofmore » the harmonics. In this paper, we discuss and compare two different shot noise models that are implemented in both one-dimensional wiggler-averaged (PERSEO) and non-wiggler-averaged (MEDUSA1D) simulation codes, and a three-dimensional non-wiggler-averaged (MEDUSA) formulation. These models are compared for examples describing both SASE and MOPA configurations in one dimension, in steady-state, and time-dependent simulations. Remarkable agreement is found between PERSEO and MEDUSA1D for the evolution of the fundamental and harmonics. In addition, three-dimensional correction factors have been included in the MEDUSA1D and PERSEO, which show reasonable agreement with MEDUSA for a sample MOPA in steady-state and time-dependent simulations.« less

Listening to the Noise: Random Fluctuations Reveal Gene Network Parameters

NASA Astrophysics Data System (ADS)

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.

Low-frequency random telegraphic noise and 1/f noise in the rare-earth manganite Pr0.63Ca0.37MnO3 near the charge-ordering transition

NASA Astrophysics Data System (ADS)

Bid, Aveek; Guha, Ayan; Raychaudhuri, A. K.

2003-05-01

We have studied low-frequency resistance fluctuations (noise) in a single crystal of the rare-earth perovskite manganite Pr0.63Ca0.37MnO3, which shows a charge-ordering transition at a temperature TCO≈245 K. The measurements were made across the charge-ordering transition covering the temperature range 200 K

Towards a Full Waveform Ambient Noise Inversion

NASA Astrophysics Data System (ADS)

Sager, K.; Ermert, L. A.; Boehm, C.; Fichtner, A.

2015-12-01

Noise tomography usually works under the assumption that the inter-station ambient noise correlation is equal to a scaled version of the Green's function between the two receivers. This assumption, however, is only met under specific conditions, for instance, wavefield diffusivity and equipartitioning, zero attenuation, etc., that are typically not satisfied in the Earth. This inconsistency inhibits the exploitation of the full waveform information contained in noise correlations regarding Earth structure and noise generation. To overcome this limitation we attempt to develop a method that consistently accounts for noise distribution, 3D heterogeneous Earth structure and the full seismic wave propagation physics in order to improve the current resolution of tomographic images of the Earth. As an initial step towards a full waveform ambient noise inversion we develop a preliminary inversion scheme based on a 2D finite-difference code simulating correlation functions and on adjoint techniques. With respect to our final goal, a simultaneous inversion for noise distribution and Earth structure, we address the following two aspects: (1) the capabilities of different misfit functionals to image wave speed anomalies and source distribution and (2) possible source-structure trade-offs, especially to what extent unresolvable structure could be mapped into the inverted noise source distribution and vice versa.

Generation of a tunable environment for electrical oscillator systems.

PubMed

León-Montiel, R de J; Svozilík, J; Torres, Juan P

2014-07-01

Many physical, chemical, and biological systems can be modeled by means of random-frequency harmonic oscillator systems. Even though the noise-free evolution of harmonic oscillator systems can be easily implemented, the way to experimentally introduce, and control, noise effects due to a surrounding environment remains a subject of lively interest. Here, we experimentally demonstrate a setup that provides a unique tool to generate a fully tunable environment for classical electrical oscillator systems. We illustrate the operation of the setup by implementing the case of a damped random-frequency harmonic oscillator. The high degree of tunability and control of our scheme is demonstrated by gradually modifying the statistics of the oscillator's frequency fluctuations. This tunable system can readily be used to experimentally study interesting noise effects, such as noise-induced transitions in systems driven by multiplicative noise, and noise-induced transport, a phenomenon that takes place in quantum and classical coupled oscillator networks.

Investigation of Diesel’s Residual Noise on Predictive Vehicles Noise Cancelling using LMS Adaptive Algorithm

NASA Astrophysics Data System (ADS)

Arttini Dwi Prasetyowati, Sri; Susanto, Adhi; Widihastuti, Ida

2017-04-01

Every noise problems require different solution. In this research, the noise that must be cancelled comes from roadway. Least Mean Square (LMS) adaptive is one of the algorithm that can be used to cancel that noise. Residual noise always appears and could not be erased completely. This research aims to know the characteristic of residual noise from vehicle’s noise and analysis so that it is no longer appearing as a problem. LMS algorithm was used to predict the vehicle’s noise and minimize the error. The distribution of the residual noise could be observed to determine the specificity of the residual noise. The statistic of the residual noise close to normal distribution with = 0,0435, = 1,13 and the autocorrelation of the residual noise forming impulse. As a conclusion the residual noise is insignificant.

Comparison between beamforming and super resolution imaging algorithms for non-destructive evaluation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fan, Chengguang; Drinkwater, Bruce W.

In this paper the performance of total focusing method is compared with the widely used time-reversal MUSIC super resolution technique. The algorithms are tested with simulated and experimental ultrasonic array data, each containing different noise levels. The simulated time domain signals allow the effects of array geometry, frequency, scatterer location, scatterer size, scatterer separation and random noise to be carefully controlled. The performance of the imaging algorithms is evaluated in terms of resolution and sensitivity to random noise. It is shown that for the low noise situation, time-reversal MUSIC provides enhanced lateral resolution when compared to the total focusing method.more » However, for higher noise levels, the total focusing method shows robustness, whilst the performance of time-reversal MUSIC is significantly degraded.« less

Simultaneous monitoring technique for ASE and MPI noises in distributed Raman Amplified Systems.

PubMed

Choi, H Y; Jun, S B; Shin, S K; Chung, Y C

2007-07-09

We develop a new technique for simultaneously monitoring the amplified spontaneous emission (ASE) and multi-path interference (MPI) noises in distributed Raman amplified (DRA) systems. This technique utilizes the facts that the degree-of polarization (DOP) of the MPI noise is 1/9, while the ASE noise is unpolarized. The results show that the proposed technique can accurately monitor both of these noises regardless of the bit rates, modulation formats, and optical signal-to-noise ratio (OSNR) levels of the signals.

Towards Full-Waveform Ambient Noise Inversion

NASA Astrophysics Data System (ADS)

Sager, K.; Ermert, L. A.; Boehm, C.; Fichtner, A.

2016-12-01

Noise tomography usually works under the assumption that the inter-station ambient noise correlation is equal to a scaled version of the Green function between the two receivers. This assumption, however, is only met under specific conditions, e.g. wavefield diffusivity and equipartitioning, or the isotropic distribution of both mono- and dipolar uncorrelated noise sources. These assumptions are typically not satisfied in the Earth. This inconsistency inhibits the exploitation of the full waveform information contained in noise correlations in order to constrain Earth structure and noise generation. To overcome this limitation, we attempt to develop a method that consistently accounts for the distribution of noise sources, 3D heterogeneous Earth structure and the full seismic wave propagation physics. This is intended to improve the resolution of tomographic images, to refine noise source location, and thereby to contribute to a better understanding of noise generation. We introduce an operator-based formulation for the computation of correlation functions and apply the continuous adjoint method that allows us to compute first and second derivatives of misfit functionals with respect to source distribution and Earth structure efficiently. Based on these developments we design an inversion scheme using a 2D finite-difference code. To enable a joint inversion for noise sources and Earth structure, we investigate the following aspects: The capability of different misfit functionals to image wave speed anomalies and source distribution. Possible source-structure trade-offs, especially to what extent unresolvable structure can be mapped into the inverted noise source distribution and vice versa. In anticipation of real-data applications, we present an extension of the open-source waveform modelling and inversion package Salvus, which allows us to compute correlation functions in 3D media with heterogeneous noise sources at the surface.

The Low-Noise Potential of Distributed Propulsion on a Catamaran Aircraft

NASA Technical Reports Server (NTRS)

Posey, Joe W.; Tinetti, A. F.; Dunn, M. H.

2006-01-01

The noise shielding potential of an inboard-wing catamaran aircraft when coupled with distributed propulsion is examined. Here, only low-frequency jet noise from mid-wing-mounted engines is considered. Because low frequencies are the most difficult to shield, these calculations put a lower bound on the potential shielding benefit. In this proof-of-concept study, simple physical models are used to describe the 3-D scattering of jet noise by conceptualized catamaran aircraft. The Fast Scattering Code is used to predict noise levels on and about the aircraft. Shielding results are presented for several catamaran type geometries and simple noise source configurations representative of distributed propulsion radiation. Computational analyses are presented that demonstrate the shielding benefits of distributed propulsion and of increasing the width of the inboard wing. Also, sample calculations using the FSC are presented that demonstrate additional noise reduction on the aircraft fuselage by the use of acoustic liners on the inboard wing trailing edge. A full conceptual aircraft design would have to be analyzed over a complete mission to more accurately quantify community noise levels and aircraft performance, but the present shielding calculations show that a large acoustic benefit could be achieved by combining distributed propulsion and liner technology with a twin-fuselage planform.

Rough Sets and Stomped Normal Distribution for Simultaneous Segmentation and Bias Field Correction in Brain MR Images.

PubMed

Banerjee, Abhirup; Maji, Pradipta

2015-12-01

The segmentation of brain MR images into different tissue classes is an important task for automatic image analysis technique, particularly due to the presence of intensity inhomogeneity artifact in MR images. In this regard, this paper presents a novel approach for simultaneous segmentation and bias field correction in brain MR images. It integrates judiciously the concept of rough sets and the merit of a novel probability distribution, called stomped normal (SN) distribution. The intensity distribution of a tissue class is represented by SN distribution, where each tissue class consists of a crisp lower approximation and a probabilistic boundary region. The intensity distribution of brain MR image is modeled as a mixture of finite number of SN distributions and one uniform distribution. The proposed method incorporates both the expectation-maximization and hidden Markov random field frameworks to provide an accurate and robust segmentation. The performance of the proposed approach, along with a comparison with related methods, is demonstrated on a set of synthetic and real brain MR images for different bias fields and noise levels.

Noise characteristics of nanoscaled redox-cycling sensors: investigations based on random walks.

PubMed

Kätelhön, Enno; Krause, Kay J; Singh, Pradyumna S; Lemay, Serge G; Wolfrum, Bernhard

2013-06-19

We investigate noise effects in nanoscaled electrochemical sensors using a three-dimensional simulation based on random walks. The presented approach allows the prediction of time-dependent signals and noise characteristics for redox cycling devices of arbitrary geometry. We demonstrate that the simulation results closely match experimental data as well as theoretical expectations with regard to measured currents and noise power spectra. We further analyze the impact of the sensor design on characteristics of the noise power spectrum. Specific transitions between independent noise sources in the frequency domain are indicative of the sensor-reservoir coupling and can be used to identify stationary design features or time-dependent blocking mechanisms. We disclose the source code of our simulation. Since our approach is highly flexible with regard to the implemented boundary conditions, it opens up the possibility for integrating a variety of surface-specific molecular reactions in arbitrary electrochemical systems. Thus, it may become a useful tool for the investigation of a wide range of noise effects in nanoelectrochemical sensors.

Sources of noise in magneto-optical readout

NASA Technical Reports Server (NTRS)

Mansuripur, M.

1991-01-01

The various sources of noise which are often encountered in magneto-optical readout systems are analyzed. Although the focus is on magneto-optics, most sources of noise are common among the various optical recording systems and one can easily adapt the results to other media and systems. A description of the magneto-optical readout system under consideration is given, and the standard methods and the relevant terminology of signal and noise measurement are described. The characteristics of thermal noise, which originates in the electronic circuitry of the readout system, are described. The most fundamental of all sources of noise, the shot noise, is considered, and a detailed account of its statistical properties is given. Shot noise, which is due to random fluctuations in photon arrival times, is an ever-present noise in optical detection. Since the performance of magneto-optical recording devices in use today is approaching the limit imposed by the shot noise, it is important that the reader have a good grasp of this particular source of noise. A model for the laser noise is described, and measurement results which yield numerical values for the strength of the laser power fluctuations are presented. Spatial variations of the disk reflectivity and random depolarization phenomena also contribute to the overall level of noise in readout; these and related issues are treated. Numerical simulation results describing some of the more frequently encountered sources of noise which accompany the recorded waveform itself, namely, jitter noise and signal-amplitude fluctuation noise are presented.

Investigation of image components affecting the detection of lung nodules in digital chest radiography

NASA Astrophysics Data System (ADS)

Bath, Magnus; Hakansson, Markus; Borjesson, Sara; Hoeschen, Christoph; Tischenko, Oleg; Bochud, Francois O.; Verdun, Francis R.; Ullman, Gustaf; Kheddache, Susanne; Tingberg, Anders; Mansson, Lars Gunnar

2005-04-01

The aim of this work was to investigate and quantify the effects of system noise, nodule location, anatomical noise and anatomical background on the detection of lung nodules in different regions of the chest x-ray. Simulated lung nodules of diameter 10 mm but with varying detail contrast were randomly positioned in four different kinds of images: 1) clinical images collected with a 200 speed CR system, 2) images containing only system noise (including quantum noise) at the same level as the clinical images, 3) clinical images with removed anatomical noise, 4) artificial images with similar power spectrum as the clinical images but random phase spectrum. An ROC study was conducted with 5 observers. The detail contrast needed to obtain an Az of 0.80, C0.8, was used as measure of detectability. Five different regions of the chest x-ray were investigated separately. The C0.8 of the system noise images ranged from only 2% (the hilar regions) to 20% (the lateral pulmonary regions) of those of the clinical images. Compared with the original clinical images, the C0.8 was 16% lower for the de-noised clinical images and 71% higher for the random phase images, respectively, averaged over all five regions. In conclusion, regarding the detection of lung nodules with a diameter of 10 mm, the system noise is of minor importance at clinically relevant dose levels. The removal of anatomical noise and other noise sources uncorrelated from image to image leads to somewhat better detection, but the major component disturbing the detection is the overlapping of recognizable structures, which are, however, the main aspect of an x-ray image.

Delving into α-stable distribution in noise suppression for seizure detection from scalp EEG

NASA Astrophysics Data System (ADS)

Wang, Yueming; Qi, Yu; Wang, Yiwen; Lei, Zhen; Zheng, Xiaoxiang; Pan, Gang

2016-10-01

Objective. There is serious noise in EEG caused by eye blink and muscle activities. The noise exhibits similar morphologies to epileptic seizure signals, leading to relatively high false alarms in most existing seizure detection methods. The objective in this paper is to develop an effective noise suppression method in seizure detection and explore the reason why it works. Approach. Based on a state-space model containing a non-linear observation function and multiple features as the observations, this paper delves deeply into the effect of the α-stable distribution in the noise suppression for seizure detection from scalp EEG. Compared with the Gaussian distribution, the α-stable distribution is asymmetric and has relatively heavy tails. These properties make it more powerful in modeling impulsive noise in EEG, which usually can not be handled by the Gaussian distribution. Specially, we give a detailed analysis in the state estimation process to show the reason why the α-stable distribution can suppress the impulsive noise. Main results. To justify each component in our model, we compare our method with 4 different models with different settings on a collected 331-hour epileptic EEG data. To show the superiority of our method, we compare it with the existing approaches on both our 331-hour data and 892-hour public data. The results demonstrate that our method is most effective in both the detection rate and the false alarm. Significance. This is the first attempt to incorporate the α-stable distribution to a state-space model for noise suppression in seizure detection and achieves the state-of-the-art performance.

The Signal Importance of Noise

ERIC Educational Resources Information Center

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…

Classroom Noise and Teachers' Voice Production

ERIC Educational Resources Information Center

Rantala, Leena M.; Hakala, Suvi; Holmqvist, Sofia; Sala, Eeva

2015-01-01

Purpose: The aim of this study was to research the associations between noise (ambient and activity noise) and objective metrics of teachers' voices in real working environments (i.e., classrooms). Method: Thirty-two female and 8 male teachers from 14 elementary schools were randomly selected for the study. Ambient noise was measured during breaks…

Dependence of image quality on image operator and noise for optical diffusion tomography

NASA Astrophysics Data System (ADS)

Chang, Jenghwa; Graber, Harry L.; Barbour, Randall L.

1998-04-01

By applying linear perturbation theory to the radiation transport equation, the inverse problem of optical diffusion tomography can be reduced to a set of linear equations, W(mu) equals R, where W is the weight function, (mu) are the cross- section perturbations to be imaged, and R is the detector readings perturbations. We have studied the dependence of image quality on added systematic error and/or random noise in W and R. Tomographic data were collected from cylindrical phantoms, with and without added inclusions, using Monte Carlo methods. Image reconstruction was accomplished using a constrained conjugate gradient descent method. Result show that accurate images containing few artifacts are obtained when W is derived from a reference states whose optical thickness matches that of the unknown teste medium. Comparable image quality was also obtained for unmatched W, but the location of the target becomes more inaccurate as the mismatch increases. Results of the noise study show that image quality is much more sensitive to noise in W than in R, and the impact of noise increase with the number of iterations. Images reconstructed after pure noise was substituted for R consistently contain large peaks clustered about the cylinder axis, which was an initially unexpected structure. In other words, random input produces a non- random output. This finding suggests that algorithms sensitive to the evolution of this feature could be developed to suppress noise effects.

Modeling of Thermal Phase Noise in a Solid Core Photonic Crystal Fiber-Optic Gyroscope.

PubMed

Song, Ningfang; Ma, Kun; Jin, Jing; Teng, Fei; Cai, Wei

2017-10-26

A theoretical model of the thermal phase noise in a square-wave modulated solid core photonic crystal fiber-optic gyroscope has been established, and then verified by measurements. The results demonstrate a good agreement between theory and experiment. The contribution of the thermal phase noise to the random walk coefficient of the gyroscope is derived. A fiber coil with 2.8 km length is used in the experimental solid core photonic crystal fiber-optic gyroscope, showing a random walk coefficient of 9.25 × 10 -5 deg/√h.

Optically phase-locked electronic speckle pattern interferometer system performance for vibration measurement in random displacement fields

NASA Astrophysics Data System (ADS)

Moran, Steve E.; Lugannani, Robert; Craig, Peter N.; Law, Robert L.

1989-02-01

An analysis is made of the performance of an optically phase-locked electronic speckle pattern interferometer in the presence of random noise displacements. Expressions for the phase-locked speckle contrast for single-frame imagery and the composite rms exposure for two sequentially subtracted frames are obtained in terms of the phase-locked composite and single-frame fringe functions. The noise fringe functions are evaluated for stationary, coherence-separable noise displacements obeying Gauss-Markov temporal statistics. The theoretical findings presented here are qualitatively supported by experimental results.

A Comparison of Three Random Number Generators for Aircraft Dynamic Modeling Applications

NASA Technical Reports Server (NTRS)

Grauer, Jared A.

2017-01-01

Three random number generators, which produce Gaussian white noise sequences, were compared to assess their suitability in aircraft dynamic modeling applications. The first generator considered was the MATLAB (registered) implementation of the Mersenne-Twister algorithm. The second generator was a website called Random.org, which processes atmospheric noise measured using radios to create the random numbers. The third generator was based on synthesis of the Fourier series, where the random number sequences are constructed from prescribed amplitude and phase spectra. A total of 200 sequences, each having 601 random numbers, for each generator were collected and analyzed in terms of the mean, variance, normality, autocorrelation, and power spectral density. These sequences were then applied to two problems in aircraft dynamic modeling, namely estimating stability and control derivatives from simulated onboard sensor data, and simulating flight in atmospheric turbulence. In general, each random number generator had good performance and is well-suited for aircraft dynamic modeling applications. Specific strengths and weaknesses of each generator are discussed. For Monte Carlo simulation, the Fourier synthesis method is recommended because it most accurately and consistently approximated Gaussian white noise and can be implemented with reasonable computational effort.

Resonant paramagnetic enhancement of the thermal and zero-point Nyquist noise

NASA Astrophysics Data System (ADS)

França, H. M.; Santos, R. B. B.

1999-01-01

The interaction between a very thin macroscopic solenoid, and a single magnetic particle precessing in a external magnetic field B0, is described by taking into account the thermal and the zero-point fluctuations of stochastic electrodynamics. The inductor belongs to a RLC circuit without batteries and the random motion of the magnetic dipole generates in the solenoid a fluctuating current Idip( t), and a fluctuating voltage εdip( t), with spectral distribution quite different from the Nyquist noise. We show that the mean square value < Idip2> presents an enormous variation when the frequency of precession approaches the frequency of the circuit, but it is still much smaller than the Nyquist current in the circuit. However, we also show that < Idip2> can reach measurable values if the inductor is interacting with a macroscopic sample of magnetic particles (atoms or nuclei) which are close enough to its coils.

Speckle reduction in digital holography with resampling ring masks

NASA Astrophysics Data System (ADS)

Zhang, Wenhui; Cao, Liangcai; Jin, Guofan

2018-01-01

One-shot digital holographic imaging has the advantages of high stability and low temporal cost. However, the reconstruction is affected by the speckle noise. Resampling ring-mask method in spectrum domain is proposed for speckle reduction. The useful spectrum of one hologram is divided into several sub-spectra by ring masks. In the reconstruction, angular spectrum transform is applied to guarantee the calculation accuracy which has no approximation. N reconstructed amplitude images are calculated from the corresponding sub-spectra. Thanks to speckle's random distribution, superimposing these N uncorrelated amplitude images would lead to a final reconstructed image with lower speckle noise. Normalized relative standard deviation values of the reconstructed image are used to evaluate the reduction of speckle. Effect of the method on the spatial resolution of the reconstructed image is also quantitatively evaluated. Experimental and simulation results prove the feasibility and effectiveness of the proposed method.

Statistics of optimal information flow in ensembles of regulatory motifs

NASA Astrophysics Data System (ADS)

Crisanti, Andrea; De Martino, Andrea; Fiorentino, Jonathan

2018-02-01

Genetic regulatory circuits universally cope with different sources of noise that limit their ability to coordinate input and output signals. In many cases, optimal regulatory performance can be thought to correspond to configurations of variables and parameters that maximize the mutual information between inputs and outputs. Since the mid-2000s, such optima have been well characterized in several biologically relevant cases. Here we use methods of statistical field theory to calculate the statistics of the maximal mutual information (the "capacity") achievable by tuning the input variable only in an ensemble of regulatory motifs, such that a single controller regulates N targets. Assuming (i) sufficiently large N , (ii) quenched random kinetic parameters, and (iii) small noise affecting the input-output channels, we can accurately reproduce numerical simulations both for the mean capacity and for the whole distribution. Our results provide insight into the inherent variability in effectiveness occurring in regulatory systems with heterogeneous kinetic parameters.

Noise Response Data Reveal Novel Controllability Gramian for Nonlinear Network Dynamics

PubMed Central

Kashima, Kenji

2016-01-01

Control of nonlinear large-scale dynamical networks, e.g., collective behavior of agents interacting via a scale-free connection topology, is a central problem in many scientific and engineering fields. For the linear version of this problem, the so-called controllability Gramian has played an important role to quantify how effectively the dynamical states are reachable by a suitable driving input. In this paper, we first extend the notion of the controllability Gramian to nonlinear dynamics in terms of the Gibbs distribution. Next, we show that, when the networks are open to environmental noise, the newly defined Gramian is equal to the covariance matrix associated with randomly excited, but uncontrolled, dynamical state trajectories. This fact theoretically justifies a simple Monte Carlo simulation that can extract effectively controllable subdynamics in nonlinear complex networks. In addition, the result provides a novel insight into the relationship between controllability and statistical mechanics. PMID:27264780

Error Mitigation for Short-Depth Quantum Circuits

NASA Astrophysics Data System (ADS)

Temme, Kristan; Bravyi, Sergey; Gambetta, Jay M.

2017-11-01

Two schemes are presented that mitigate the effect of errors and decoherence in short-depth quantum circuits. The size of the circuits for which these techniques can be applied is limited by the rate at which the errors in the computation are introduced. Near-term applications of early quantum devices, such as quantum simulations, rely on accurate estimates of expectation values to become relevant. Decoherence and gate errors lead to wrong estimates of the expectation values of observables used to evaluate the noisy circuit. The two schemes we discuss are deliberately simple and do not require additional qubit resources, so to be as practically relevant in current experiments as possible. The first method, extrapolation to the zero noise limit, subsequently cancels powers of the noise perturbations by an application of Richardson's deferred approach to the limit. The second method cancels errors by resampling randomized circuits according to a quasiprobability distribution.

Feasibility of continuous-variable quantum key distribution with noisy coherent states

DOE Office of Scientific and Technical Information (OSTI.GOV)

Usenko, Vladyslav C.; Department of Optics, Palacky University, CZ-772 07 Olomouc; Filip, Radim

2010-02-15

We address security of the quantum key distribution scheme based on the noisy modulation of coherent states and investigate how it is robust against noise in the modulation regardless of the particular technical implementation. As the trusted preparation noise is shown to be security breaking even for purely lossy channels, we reveal the essential difference between two types of trusted noise, namely sender-side preparation noise and receiver-side detection noise, the latter being security preserving. We consider the method of sender-side state purification to compensate the preparation noise and show its applicability in the realistic conditions of channel loss, untrusted channelmore » excess noise, and trusted detection noise. We show that purification makes the scheme robust to the preparation noise (i.e., even the arbitrary noisy coherent states can in principle be used for the purpose of quantum key distribution). We also take into account the effect of realistic reconciliation and show that the purification method is still efficient in this case up to a limited value of preparation noise.« less

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

NASA Technical Reports Server (NTRS)

Hinedi, S.; Polydoros, A.

1988-01-01

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

Weighted Optimization-Based Distributed Kalman Filter for Nonlinear Target Tracking in Collaborative Sensor Networks.

PubMed

Chen, Jie; Li, Jiahong; Yang, Shuanghua; Deng, Fang

2017-11-01

The identification of the nonlinearity and coupling is crucial in nonlinear target tracking problem in collaborative sensor networks. According to the adaptive Kalman filtering (KF) method, the nonlinearity and coupling can be regarded as the model noise covariance, and estimated by minimizing the innovation or residual errors of the states. However, the method requires large time window of data to achieve reliable covariance measurement, making it impractical for nonlinear systems which are rapidly changing. To deal with the problem, a weighted optimization-based distributed KF algorithm (WODKF) is proposed in this paper. The algorithm enlarges the data size of each sensor by the received measurements and state estimates from its connected sensors instead of the time window. A new cost function is set as the weighted sum of the bias and oscillation of the state to estimate the "best" estimate of the model noise covariance. The bias and oscillation of the state of each sensor are estimated by polynomial fitting a time window of state estimates and measurements of the sensor and its neighbors weighted by the measurement noise covariance. The best estimate of the model noise covariance is computed by minimizing the weighted cost function using the exhaustive method. The sensor selection method is in addition to the algorithm to decrease the computation load of the filter and increase the scalability of the sensor network. The existence, suboptimality and stability analysis of the algorithm are given. The local probability data association method is used in the proposed algorithm for the multitarget tracking case. The algorithm is demonstrated in simulations on tracking examples for a random signal, one nonlinear target, and four nonlinear targets. Results show the feasibility and superiority of WODKF against other filtering algorithms for a large class of systems.

Identification of damage in structural systems using modal data

DOT National Transportation Integrated Search

2001-04-01

To develop a useful global damage identification scheme, noise and spareseness of the measured modal data must be taken into account. Measurement noise if inevitable. If one does not consider noise and its random nature, the damage evaluation algorit...

Understanding the amplitudes of noise correlation measurements

USGS Publications Warehouse

Tsai, Victor C.

2011-01-01

Cross correlation of ambient seismic noise is known to result in time series from which station-station travel-time measurements can be made. Part of the reason that these cross-correlation travel-time measurements are reliable is that there exists a theoretical framework that quantifies how these travel times depend on the features of the ambient noise. However, corresponding theoretical results do not currently exist to describe how the amplitudes of the cross correlation depend on such features. For example, currently it is not possible to take a given distribution of noise sources and calculate the cross correlation amplitudes one would expect from such a distribution. Here, we provide a ray-theoretical framework for calculating cross correlations. This framework differs from previous work in that it explicitly accounts for attenuation as well as the spatial distribution of sources and therefore can address the issue of quantifying amplitudes in noise correlation measurements. After introducing the general framework, we apply it to two specific problems. First, we show that we can quantify the amplitudes of coherency measurements, and find that the decay of coherency with station-station spacing depends crucially on the distribution of noise sources. We suggest that researchers interested in performing attenuation measurements from noise coherency should first determine how the dominant sources of noise are distributed. Second, we show that we can quantify the signal-to-noise ratio of noise correlations more precisely than previous work, and that these signal-to-noise ratios can be estimated for given situations prior to the deployment of seismometers. It is expected that there are applications of the theoretical framework beyond the two specific cases considered, but these applications await future work.

Noise generator for tinnitus treatment based on look-up tables

NASA Astrophysics Data System (ADS)

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.

Arbitrary-step randomly delayed robust filter with application to boost phase tracking

NASA Astrophysics Data System (ADS)

Qin, Wutao; Wang, Xiaogang; Bai, Yuliang; Cui, Naigang

2018-04-01

The conventional filters such as extended Kalman filter, unscented Kalman filter and cubature Kalman filter assume that the measurement is available in real-time and the measurement noise is Gaussian white noise. But in practice, both two assumptions are invalid. To solve this problem, a novel algorithm is proposed by taking the following four steps. At first, the measurement model is modified by the Bernoulli random variables to describe the random delay. Then, the expression of predicted measurement and covariance are reformulated, which could get rid of the restriction that the maximum number of delay must be one or two and the assumption that probabilities of Bernoulli random variables taking the value one are equal. Next, the arbitrary-step randomly delayed high-degree cubature Kalman filter is derived based on the 5th-degree spherical-radial rule and the reformulated expressions. Finally, the arbitrary-step randomly delayed high-degree cubature Kalman filter is modified to the arbitrary-step randomly delayed high-degree cubature Huber-based filter based on the Huber technique, which is essentially an M-estimator. Therefore, the proposed filter is not only robust to the randomly delayed measurements, but robust to the glint noise. The application to the boost phase tracking example demonstrate the superiority of the proposed algorithms.

Quantum Entanglement Growth under Random Unitary Dynamics

NASA Astrophysics Data System (ADS)

Nahum, Adam; Ruhman, Jonathan; Vijay, Sagar; Haah, Jeongwan

2017-07-01

Characterizing how entanglement grows with time in a many-body system, for example, after a quantum quench, is a key problem in nonequilibrium quantum physics. We study this problem for the case of random unitary dynamics, representing either Hamiltonian evolution with time-dependent noise or evolution by a random quantum circuit. Our results reveal a universal structure behind noisy entanglement growth, and also provide simple new heuristics for the "entanglement tsunami" in Hamiltonian systems without noise. In 1D, we show that noise causes the entanglement entropy across a cut to grow according to the celebrated Kardar-Parisi-Zhang (KPZ) equation. The mean entanglement grows linearly in time, while fluctuations grow like (time )1/3 and are spatially correlated over a distance ∝(time )2/3. We derive KPZ universal behavior in three complementary ways, by mapping random entanglement growth to (i) a stochastic model of a growing surface, (ii) a "minimal cut" picture, reminiscent of the Ryu-Takayanagi formula in holography, and (iii) a hydrodynamic problem involving the dynamical spreading of operators. We demonstrate KPZ universality in 1D numerically using simulations of random unitary circuits. Importantly, the leading-order time dependence of the entropy is deterministic even in the presence of noise, allowing us to propose a simple coarse grained minimal cut picture for the entanglement growth of generic Hamiltonians, even without noise, in arbitrary dimensionality. We clarify the meaning of the "velocity" of entanglement growth in the 1D entanglement tsunami. We show that in higher dimensions, noisy entanglement evolution maps to the well-studied problem of pinning of a membrane or domain wall by disorder.

Thermal noise calculation method for precise estimation of the signal-to-noise ratio of ultra-low-field MRI with an atomic magnetometer.

PubMed

Yamashita, Tatsuya; Oida, Takenori; Hamada, Shoji; Kobayashi, Tetsuo

2012-02-01

In recent years, there has been considerable interest in developing an ultra-low-field magnetic resonance imaging (ULF-MRI) system using an optically pumped atomic magnetometer (OPAM). However, a precise estimation of the signal-to-noise ratio (SNR) of ULF-MRI has not been carried out. Conventionally, to calculate the SNR of an MR image, thermal noise, also called Nyquist noise, has been estimated by considering a resistor that is electrically equivalent to a biological-conductive sample and is connected in series to a pickup coil. However, this method has major limitations in that the receiver has to be a coil and that it cannot be applied directly to a system using OPAM. In this paper, we propose a method to estimate the thermal noise of an MRI system using OPAM. We calculate the thermal noise from the variance of the magnetic sensor output produced by current-dipole moments that simulate thermally fluctuating current sources in a biological sample. We assume that the random magnitude of the current dipole in each volume element of the biological sample is described by the Maxwell-Boltzmann distribution. The sensor output produced by each current-dipole moment is calculated either by an analytical formula or a numerical method based on the boundary element method. We validate the proposed method by comparing our results with those obtained by conventional methods that consider resistors connected in series to a pickup coil using single-layered sphere, multi-layered sphere, and realistic head models. Finally, we apply the proposed method to the ULF-MRI model using OPAM as the receiver with multi-layered sphere and realistic head models and estimate their SNR. Copyright © 2011 Elsevier Inc. All rights reserved.

Averaging of phase noise in PSK signals by an opto-electrical feed-forward circuit

NASA Astrophysics Data System (ADS)

Inoue, K.; Ohta, M.

2013-10-01

This paper proposes an opto-electrical feed-forward circuit that reduces phase noise in binary PSK signals by averaging the noise. Random and independent phase noise is averaged over several bit slots by externally modulating a phase-fluctuating PSK signal with feed-forward signal obtained from signal processing of the outputs of delay interferometers. The simulation results demonstrate a reduction in the phase noise.

Robust Image Regression Based on the Extended Matrix Variate Power Exponential Distribution of Dependent Noise.

PubMed

Luo, Lei; Yang, Jian; Qian, Jianjun; Tai, Ying; Lu, Gui-Fu

2017-09-01

Dealing with partial occlusion or illumination is one of the most challenging problems in image representation and classification. In this problem, the characterization of the representation error plays a crucial role. In most current approaches, the error matrix needs to be stretched into a vector and each element is assumed to be independently corrupted. This ignores the dependence between the elements of error. In this paper, it is assumed that the error image caused by partial occlusion or illumination changes is a random matrix variate and follows the extended matrix variate power exponential distribution. This has the heavy tailed regions and can be used to describe a matrix pattern of l×m dimensional observations that are not independent. This paper reveals the essence of the proposed distribution: it actually alleviates the correlations between pixels in an error matrix E and makes E approximately Gaussian. On the basis of this distribution, we derive a Schatten p -norm-based matrix regression model with L q regularization. Alternating direction method of multipliers is applied to solve this model. To get a closed-form solution in each step of the algorithm, two singular value function thresholding operators are introduced. In addition, the extended Schatten p -norm is utilized to characterize the distance between the test samples and classes in the design of the classifier. Extensive experimental results for image reconstruction and classification with structural noise demonstrate that the proposed algorithm works much more robustly than some existing regression-based methods.

Bearings fault detection in helicopters using frequency readjustment and cyclostationary analysis

NASA Astrophysics Data System (ADS)

Girondin, Victor; Pekpe, Komi Midzodzi; Morel, Herve; Cassar, Jean-Philippe

2013-07-01

The objective of this paper is to propose a vibration-based automated framework dealing with local faults occurring on bearings in the transmission of a helicopter. The knowledge of the shaft speed and kinematic computation provide theoretical frequencies that reveal deteriorations on the inner and outer races, on the rolling elements or on the cage. In practice, the theoretical frequencies of bearing faults may be shifted. They may also be masked by parasitical frequencies because the numerous noisy vibrations and the complexity of the transmission mechanics make the signal spectrum very profuse. Consequently, detection methods based on the monitoring of the theoretical frequencies may lead to wrong decisions. In order to deal with this drawback, we propose to readjust the fault frequencies from the theoretical frequencies using the redundancy introduced by the harmonics. The proposed method provides the confidence index of the readjusted frequency. Minor variations in shaft speed may induce random jitters. The change of the contact surface or of the transmission path brings also a random component in amplitude and phase. These random components in the signal destroy spectral localization of frequencies and thus hide the fault occurrence in the spectrum. Under the hypothesis that these random signals can be modeled as cyclostationary signals, the envelope spectrum can reveal that hidden patterns. In order to provide an indicator estimating fault severity, statistics are proposed. They make the hypothesis that the harmonics at the readjusted frequency are corrupted with an additive normally distributed noise. In this case, the statistics computed from the spectra are chi-square distributed and a signal-to-noise indicator is proposed. The algorithms are then tested with data from two test benches and from flight conditions. The bearing type and the radial load are the main differences between the experiences on the benches. The fault is mainly visible in the spectrum for the radially constrained bearing and only visible in the envelope spectrum for the "load-free" bearing. Concerning results in flight conditions, frequency readjustment demonstrates good performances when applied on the spectrum, showing that a fully automated bearing decision procedure is applicable for operational helicopter monitoring.

THE EFFECTS OF SPATIAL SMOOTHING ON SOLAR MAGNETIC HELICITY PARAMETERS AND THE HEMISPHERIC HELICITY SIGN RULE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ocker, Stella Koch; Petrie, Gordon, E-mail: socker@oberlin.edu, E-mail: gpetrie@nso.edu

The hemispheric preference for negative/positive helicity to occur in the northern/southern solar hemisphere provides clues to the causes of twisted, flaring magnetic fields. Previous studies on the hemisphere rule may have been affected by seeing from atmospheric turbulence. Using Hinode /SOT-SP data spanning 2006–2013, we studied the effects of two spatial smoothing tests that imitate atmospheric seeing: noise reduction by ignoring pixel values weaker than the estimated noise threshold, and Gaussian spatial smoothing. We studied in detail the effects of atmospheric seeing on the helicity distributions across various field strengths for active regions (ARs) NOAA 11158 and NOAA 11243, in addition tomore » studying the average helicities of 179 ARs with and without smoothing. We found that, rather than changing trends in the helicity distributions, spatial smoothing modified existing trends by reducing random noise and by regressing outliers toward the mean, or removing them altogether. Furthermore, the average helicity parameter values of the 179 ARs did not conform to the hemisphere rule: independent of smoothing, the weak-vertical-field values tended to be negative in both hemispheres, and the strong-vertical-field values tended to be positive, especially in the south. We conclude that spatial smoothing does not significantly affect the overall statistics for space-based data, and thus seeing from atmospheric turbulence seems not to have significantly affected previous studies’ ground-based results on the hemisphere rule.« less

Scene-based nonuniformity correction using local constant statistics.

PubMed

Zhang, Chao; Zhao, Wenyi

2008-06-01

In scene-based nonuniformity correction, the statistical approach assumes all possible values of the true-scene pixel are seen at each pixel location. This global-constant-statistics assumption does not distinguish fixed pattern noise from spatial variations in the average image. This often causes the "ghosting" artifacts in the corrected images since the existing spatial variations are treated as noises. We introduce a new statistical method to reduce the ghosting artifacts. Our method proposes a local-constant statistics that assumes that the temporal signal distribution is not constant at each pixel but is locally true. This considers statistically a constant distribution in a local region around each pixel but uneven distribution in a larger scale. Under the assumption that the fixed pattern noise concentrates in a higher spatial-frequency domain than the distribution variation, we apply a wavelet method to the gain and offset image of the noise and separate out the pattern noise from the spatial variations in the temporal distribution of the scene. We compare the results to the global-constant-statistics method using a clean sequence with large artificial pattern noises. We also apply the method to a challenging CCD video sequence and a LWIR sequence to show how effective it is in reducing noise and the ghosting artifacts.

The noise impact of proposed runway alternatives at Craig Airport

NASA Technical Reports Server (NTRS)

Deloach, R.

1982-01-01

Four proposed runway expansion alternatives at Craig Airport in Jacksonville, Florida have been assessed with respect to their forecasted noise impact in the year 2005. The assessment accounts for population distributions around the airport and human subjective response to noise, as well as the distribution of noise levels in the surrounding community (footprints). The impact analysis was performed using the Airport-noise Levels and Annoyance Model (ALAMO), an airport community response model recently developd at Langley Research Center.

Statistical methods for efficient design of community surveys of response to noise: Random coefficients regression models

NASA Technical Reports Server (NTRS)

Tomberlin, T. J.

1985-01-01

Research studies of residents' responses to noise consist of interviews with samples of individuals who are drawn from a number of different compact study areas. The statistical techniques developed provide a basis for those sample design decisions. These techniques are suitable for a wide range of sample survey applications. A sample may consist of a random sample of residents selected from a sample of compact study areas, or in a more complex design, of a sample of residents selected from a sample of larger areas (e.g., cities). The techniques may be applied to estimates of the effects on annoyance of noise level, numbers of noise events, the time-of-day of the events, ambient noise levels, or other factors. Methods are provided for determining, in advance, how accurately these effects can be estimated for different sample sizes and study designs. Using a simple cost function, they also provide for optimum allocation of the sample across the stages of the design for estimating these effects. These techniques are developed via a regression model in which the regression coefficients are assumed to be random, with components of variance associated with the various stages of a multi-stage sample design.

Binaural comodulation masking release: Effects of masker interaural correlation

PubMed Central

Hall, Joseph W.; Buss, Emily; Grose, John H.

2007-01-01

Binaural detection was examined for a signal presented in a narrow band of noise centered on the on-signal masking band (OSB) or in the presence of flanking noise bands that were random or comodulated with respect to the OSB. The noise had an interaural correlation of 1.0 (No), 0.99 or 0.95. In No noise, random flanking bands worsened Sπ detection and comodulated bands improved Sπ detection for some listeners but had no effect for other listeners. For the 0.99 or 0.95 interaural correlation conditions, random flanking bands were less detrimental to Sπ detection and comodulated flanking bands improved Sπ detection for all listeners. Analyses based on signal detection theory indicated that the improvement in Sπ thresholds obtained with comodulated bands was not compatible with an optimal combination of monaural and binaural cues or to across-frequency analyses of dynamic interaural phase differences. Two accounts consistent with the improvement in Sπ thresholds in comodulated noise were (1) envelope information carried by the flanking bands improves the weighting of binaural cues associated with the signal; (2) the auditory system is sensitive to across-frequency differences in ongoing interaural correlation. PMID:17225415

Application of the Radon-FCL approach to seismic random noise suppression and signal preservation

NASA Astrophysics Data System (ADS)

Meng, Fanlei; Li, Yue; Liu, Yanping; Tian, Yanan; Wu, Ning

2016-08-01

The fractal conservation law (FCL) is a linear partial differential equation that is modified by an anti-diffusive term of lower order. The analysis indicated that this algorithm could eliminate high frequencies and preserve or amplify low/medium-frequencies. Thus, this method is quite suitable for the simultaneous noise suppression and enhancement or preservation of seismic signals. However, the conventional FCL filters seismic data only along the time direction, thereby ignoring the spatial coherence between neighbouring traces, which leads to the loss of directional information. Therefore, we consider the development of the conventional FCL into the time-space domain and propose a Radon-FCL approach. We applied a Radon transform to implement the FCL method in this article; performing FCL filtering in the Radon domain achieves a higher level of noise attenuation. Using this method, seismic reflection events can be recovered with the sacrifice of fewer frequency components while effectively attenuating more random noise than conventional FCL filtering. Experiments using both synthetic and common shot point data demonstrate the advantages of the Radon-FCL approach versus the conventional FCL method with regard to both random noise attenuation and seismic signal preservation.

Iterative dip-steering median filter

NASA Astrophysics Data System (ADS)

Huo, Shoudong; Zhu, Weihong; Shi, Taikun

2017-09-01

Seismic data are always contaminated with high noise components, which present processing challenges especially for signal preservation and its true amplitude response. This paper deals with an extension of the conventional median filter, which is widely used in random noise attenuation. It is known that the standard median filter works well with laterally aligned coherent events but cannot handle steep events, especially events with conflicting dips. In this paper, an iterative dip-steering median filter is proposed for the attenuation of random noise in the presence of multiple dips. The filter first identifies the dominant dips inside an optimized processing window by a Fourier-radial transform in the frequency-wavenumber domain. The optimum size of the processing window depends on the intensity of random noise that needs to be attenuated and the amount of signal to be preserved. It then applies median filter along the dominant dip and retains the signals. Iterations are adopted to process the residual signals along the remaining dominant dips in a descending sequence, until all signals have been retained. The method is tested by both synthetic and field data gathers and also compared with the commonly used f-k least squares de-noising and f-x deconvolution.

Propeller noise minimization without thrust loss due to asymmetric blade distribution

NASA Astrophysics Data System (ADS)

Dobrzynski, Werner

1990-11-01

Measures which can be taken to minimize propeller noise caused by asymmetric blade distribution, without loss of thrust, are discussed. The theoretical optimization of angular separation and its relation to the minimization of noise is reviewed. Experimental results on various propellers are discussed.

Fisher information and Cramér-Rao lower bound for experimental design in parallel imaging.

PubMed

Bouhrara, Mustapha; Spencer, Richard G

2018-06-01

The Cramér-Rao lower bound (CRLB) is widely used in the design of magnetic resonance (MR) experiments for parameter estimation. Previous work has considered only Gaussian or Rician noise distributions in this calculation. However, the noise distribution for multi-coil acquisitions, such as in parallel imaging, obeys the noncentral χ-distribution under many circumstances. The purpose of this paper is to present the CRLB calculation for parameter estimation from multi-coil acquisitions. We perform explicit calculations of Fisher matrix elements and the associated CRLB for noise distributions following the noncentral χ-distribution. The special case of diffusion kurtosis is examined as an important example. For comparison with analytic results, Monte Carlo (MC) simulations were conducted to evaluate experimental minimum standard deviations (SDs) in the estimation of diffusion kurtosis model parameters. Results were obtained for a range of signal-to-noise ratios (SNRs), and for both the conventional case of Gaussian noise distribution and noncentral χ-distribution with different numbers of coils, m. At low-to-moderate SNR, the noncentral χ-distribution deviates substantially from the Gaussian distribution. Our results indicate that this departure is more pronounced for larger values of m. As expected, the minimum SDs (i.e., CRLB) in derived diffusion kurtosis model parameters assuming a noncentral χ-distribution provided a closer match to the MC simulations as compared to the Gaussian results. Estimates of minimum variance for parameter estimation and experimental design provided by the CRLB must account for the noncentral χ-distribution of noise in multi-coil acquisitions, especially in the low-to-moderate SNR regime. Magn Reson Med 79:3249-3255, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Adaptive photoacoustic imaging quality optimization with EMD and reconstruction

NASA Astrophysics Data System (ADS)

Guo, Chengwen; Ding, Yao; Yuan, Jie; Xu, Guan; Wang, Xueding; Carson, Paul L.

2016-10-01

Biomedical photoacoustic (PA) signal is characterized with extremely low signal to noise ratio which will yield significant artifacts in photoacoustic tomography (PAT) images. Since PA signals acquired by ultrasound transducers are non-linear and non-stationary, traditional data analysis methods such as Fourier and wavelet method cannot give useful information for further research. In this paper, we introduce an adaptive method to improve the quality of PA imaging based on empirical mode decomposition (EMD) and reconstruction. Data acquired by ultrasound transducers are adaptively decomposed into several intrinsic mode functions (IMFs) after a sifting pre-process. Since noise is randomly distributed in different IMFs, depressing IMFs with more noise while enhancing IMFs with less noise can effectively enhance the quality of reconstructed PAT images. However, searching optimal parameters by means of brute force searching algorithms will cost too much time, which prevent this method from practical use. To find parameters within reasonable time, heuristic algorithms, which are designed for finding good solutions more efficiently when traditional methods are too slow, are adopted in our method. Two of the heuristic algorithms, Simulated Annealing Algorithm, a probabilistic method to approximate the global optimal solution, and Artificial Bee Colony Algorithm, an optimization method inspired by the foraging behavior of bee swarm, are selected to search optimal parameters of IMFs in this paper. The effectiveness of our proposed method is proved both on simulated data and PA signals from real biomedical tissue, which might bear the potential for future clinical PA imaging de-noising.

Seismic fault zone trapped noise

NASA Astrophysics Data System (ADS)

Hillers, G.; Campillo, M.; Ben-Zion, Y.; Roux, P.

2014-07-01

Systematic velocity contrasts across and within fault zones can lead to head and trapped waves that provide direct information on structural units that are important for many aspects of earthquake and fault mechanics. Here we construct trapped waves from the scattered seismic wavefield recorded by a fault zone array. The frequency-dependent interaction between the ambient wavefield and the fault zone environment is studied using properties of the noise correlation field. A critical frequency fc ≈ 0.5 Hz defines a threshold above which the in-fault scattered wavefield has increased isotropy and coherency compared to the ambient noise. The increased randomization of in-fault propagation directions produces a wavefield that is trapped in a waveguide/cavity-like structure associated with the low-velocity damage zone. Dense spatial sampling allows the resolution of a near-field focal spot, which emerges from the superposition of a collapsing, time reversed wavefront. The shape of the focal spot depends on local medium properties, and a focal spot-based fault normal distribution of wave speeds indicates a ˜50% velocity reduction consistent with estimates from a far-field travel time inversion. The arrival time pattern of a synthetic correlation field can be tuned to match properties of an observed pattern, providing a noise-based imaging tool that can complement analyses of trapped ballistic waves. The results can have wide applicability for investigating the internal properties of fault damage zones, because mechanisms controlling the emergence of trapped noise have less limitations compared to trapped ballistic waves.

Shot noise: from Schottky's vacuum tube to present-day quantum devices

NASA Astrophysics Data System (ADS)

Schonenberger, Christian; Oberholzer, Stefan

2004-05-01

Shot-noise in the electrical current through a 'device' is caused by random processes that determine the electron transport from source to drain. Two sources can be distinguished: on the hand, electrons may randomly emanate from the contacts (source and drain), because the relevant states in the reservoirs fluctuate. On the other hand, the transmission through the device is non-deterministic (non-classical). As we demonstrate in this article the former dominates noise in the vacuum tube, whereas the latter applies to coherent mesoscopic devices, which have been studied in great detail during the last decade.

Modeling of Thermal Phase Noise in a Solid Core Photonic Crystal Fiber-Optic Gyroscope

PubMed Central

Song, Ningfang; Ma, Kun; Jin, Jing; Teng, Fei; Cai, Wei

2017-01-01

A theoretical model of the thermal phase noise in a square-wave modulated solid core photonic crystal fiber-optic gyroscope has been established, and then verified by measurements. The results demonstrate a good agreement between theory and experiment. The contribution of the thermal phase noise to the random walk coefficient of the gyroscope is derived. A fiber coil with 2.8 km length is used in the experimental solid core photonic crystal fiber-optic gyroscope, showing a random walk coefficient of 9.25 × 10−5 deg/h. PMID:29072605

Building a high resolution national elevation model from SRTM: The Australian experience

NASA Astrophysics Data System (ADS)

Gallant, J. C.; Read, A.; Dowling, T. I.

2011-12-01

The global SRTM DEM is a valuable global data set that, for many countries including Australia, provides the best basis for a fine resolution national DEM. But the SRTM data suffers from a variety of artefacts and errors that prevent its routine application with familiar terrain analysis tools. The most important of these are stripes, voids, random noise and offsets due to trees. The tree offsets are particularly disruptive in riparian areas where they make rivers appear as ridge lines. This paper describes how a suite of tools was applied to the 1 second SRTM data for Australia to treat each of these artefacts. An FFT-based tool was developed to detect and remove regular striping. Voids were filled using a modification of the delta surface fill method. Offsets due to trees were modelled and removed using a vegetation mask derived from remotely sensed imagery and a statistical estimate of the offset at vegetation patch boundaries. Random noise was removed using an adaptive smoothing method that responds to variations in both local relief and noise magnitude. Finally, mapped channel networks were imposed using a modified version of the ANUDEM software to enforce hydrological connectivity. The resulting products are being distributed by Geoscience Australia and the smoothed and drainage enforced products in particular are suitable for use in routine terrain analysis tasks. With some adaptation, the same processes could be applied to the global SRTM to derive a product that, in combination with an improved ASTER G-DEM, would provide a high quality comprehensive global elevation model suitable for most purposes.

Noise enhances information transfer in hierarchical networks.

PubMed

Czaplicka, Agnieszka; Holyst, Janusz A; Sloot, Peter M A

2013-01-01

We study the influence of noise on information transmission in the form of packages shipped between nodes of hierarchical networks. Numerical simulations are performed for artificial tree networks, scale-free Ravasz-Barabási networks as well for a real network formed by email addresses of former Enron employees. Two types of noise are considered. One is related to packet dynamics and is responsible for a random part of packets paths. The second one originates from random changes in initial network topology. We find that the information transfer can be enhanced by the noise. The system possesses optimal performance when both kinds of noise are tuned to specific values, this corresponds to the Stochastic Resonance phenomenon. There is a non-trivial synergy present for both noisy components. We found also that hierarchical networks built of nodes of various degrees are more efficient in information transfer than trees with a fixed branching factor.

Noise enhances information transfer in hierarchical networks

PubMed Central

Czaplicka, Agnieszka; Holyst, Janusz A.; Sloot, Peter M. A.

2013-01-01

We study the influence of noise on information transmission in the form of packages shipped between nodes of hierarchical networks. Numerical simulations are performed for artificial tree networks, scale-free Ravasz-Barabási networks as well for a real network formed by email addresses of former Enron employees. Two types of noise are considered. One is related to packet dynamics and is responsible for a random part of packets paths. The second one originates from random changes in initial network topology. We find that the information transfer can be enhanced by the noise. The system possesses optimal performance when both kinds of noise are tuned to specific values, this corresponds to the Stochastic Resonance phenomenon. There is a non-trivial synergy present for both noisy components. We found also that hierarchical networks built of nodes of various degrees are more efficient in information transfer than trees with a fixed branching factor. PMID:23390574

Estimation of beam material random field properties via sensitivity-based model updating using experimental frequency response functions

NASA Astrophysics Data System (ADS)

Machado, M. R.; Adhikari, S.; Dos Santos, J. M. C.; Arruda, J. R. F.

2018-03-01

Structural parameter estimation is affected not only by measurement noise but also by unknown uncertainties which are present in the system. Deterministic structural model updating methods minimise the difference between experimentally measured data and computational prediction. Sensitivity-based methods are very efficient in solving structural model updating problems. Material and geometrical parameters of the structure such as Poisson's ratio, Young's modulus, mass density, modal damping, etc. are usually considered deterministic and homogeneous. In this paper, the distributed and non-homogeneous characteristics of these parameters are considered in the model updating. The parameters are taken as spatially correlated random fields and are expanded in a spectral Karhunen-Loève (KL) decomposition. Using the KL expansion, the spectral dynamic stiffness matrix of the beam is expanded as a series in terms of discretized parameters, which can be estimated using sensitivity-based model updating techniques. Numerical and experimental tests involving a beam with distributed bending rigidity and mass density are used to verify the proposed method. This extension of standard model updating procedures can enhance the dynamic description of structural dynamic models.

Continuous operation of four-state continuous-variable quantum key distribution system

NASA Astrophysics Data System (ADS)

Matsubara, Takuto; Ono, Motoharu; Oguri, Yusuke; Ichikawa, Tsubasa; Hirano, Takuya; Kasai, Kenta; Matsumoto, Ryutaroh; Tsurumaru, Toyohiro

2016-10-01

We report on the development of continuous-variable quantum key distribution (CV-QKD) system that are based on discrete quadrature amplitude modulation (QAM) and homodyne detection of coherent states of light. We use a pulsed light source whose wavelength is 1550 nm and repetition rate is 10 MHz. The CV-QKD system can continuously generate secret key which is secure against entangling cloner attack. Key generation rate is 50 kbps when the quantum channel is a 10 km optical fiber. The CV-QKD system we have developed utilizes the four-state and post-selection protocol [T. Hirano, et al., Phys. Rev. A 68, 042331 (2003).]; Alice randomly sends one of four states {|+/-α⟩,|+/-𝑖α⟩}, and Bob randomly performs x- or p- measurement by homodyne detection. A commercially available balanced receiver is used to realize shot-noise-limited pulsed homodyne detection. GPU cards are used to accelerate the software-based post-processing. We use a non-binary LDPC code for error correction (reverse reconciliation) and the Toeplitz matrix multiplication for privacy amplification.

Mean-field theory of a plastic network of integrate-and-fire neurons.

PubMed

Chen, Chun-Chung; Jasnow, David

2010-01-01

We consider a noise-driven network of integrate-and-fire neurons. The network evolves as result of the activities of the neurons following spike-timing-dependent plasticity rules. We apply a self-consistent mean-field theory to the system to obtain the mean activity level for the system as a function of the mean synaptic weight, which predicts a first-order transition and hysteresis between a noise-dominated regime and a regime of persistent neural activity. Assuming Poisson firing statistics for the neurons, the plasticity dynamics of a synapse under the influence of the mean-field environment can be mapped to the dynamics of an asymmetric random walk in synaptic-weight space. Using a master equation for small steps, we predict a narrow distribution of synaptic weights that scales with the square root of the plasticity rate for the stationary state of the system given plausible physiological parameter values describing neural transmission and plasticity. The dependence of the distribution on the synaptic weight of the mean-field environment allows us to determine the mean synaptic weight self-consistently. The effect of fluctuations in the total synaptic conductance and plasticity step sizes are also considered. Such fluctuations result in a smoothing of the first-order transition for low number of afferent synapses per neuron and a broadening of the synaptic-weight distribution, respectively.

Nonequilibrium steady state of a weakly-driven Kardar–Parisi–Zhang equation

NASA Astrophysics Data System (ADS)

Meerson, Baruch; Sasorov, Pavel V.; Vilenkin, Arkady

2018-05-01

We consider an infinite interface of d  >  2 dimensions, governed by the Kardar–Parisi–Zhang (KPZ) equation with a weak Gaussian noise which is delta-correlated in time and has short-range spatial correlations. We study the probability distribution of the interface height H at a point of the substrate, when the interface is initially flat. We show that, in stark contrast with the KPZ equation in d  <  2, this distribution approaches a non-equilibrium steady state. The time of relaxation toward this state scales as the diffusion time over the correlation length of the noise. We study the steady-state distribution using the optimal-fluctuation method. The typical, small fluctuations of height are Gaussian. For these fluctuations the activation path of the system coincides with the time-reversed relaxation path, and the variance of can be found from a minimization of the (nonlocal) equilibrium free energy of the interface. In contrast, the tails of are nonequilibrium, non-Gaussian and strongly asymmetric. To determine them we calculate, analytically and numerically, the activation paths of the system, which are different from the time-reversed relaxation paths. We show that the slower-decaying tail of scales as , while the faster-decaying tail scales as . The slower-decaying tail has important implications for the statistics of directed polymers in random potential.

Population density equations for stochastic processes with memory kernels

NASA Astrophysics Data System (ADS)

Lai, Yi Ming; de Kamps, Marc

2017-06-01

We present a method for solving population density equations (PDEs)-a mean-field technique describing homogeneous populations of uncoupled neurons—where the populations can be subject to non-Markov noise for arbitrary distributions of jump sizes. The method combines recent developments in two different disciplines that traditionally have had limited interaction: computational neuroscience and the theory of random networks. The method uses a geometric binning scheme, based on the method of characteristics, to capture the deterministic neurodynamics of the population, separating the deterministic and stochastic process cleanly. We can independently vary the choice of the deterministic model and the model for the stochastic process, leading to a highly modular numerical solution strategy. We demonstrate this by replacing the master equation implicit in many formulations of the PDE formalism by a generalization called the generalized Montroll-Weiss equation—a recent result from random network theory—describing a random walker subject to transitions realized by a non-Markovian process. We demonstrate the method for leaky- and quadratic-integrate and fire neurons subject to spike trains with Poisson and gamma-distributed interspike intervals. We are able to model jump responses for both models accurately to both excitatory and inhibitory input under the assumption that all inputs are generated by one renewal process.

Iteration and superposition encryption scheme for image sequences based on multi-dimensional keys

NASA Astrophysics Data System (ADS)

Han, Chao; Shen, Yuzhen; Ma, Wenlin

2017-12-01

An iteration and superposition encryption scheme for image sequences based on multi-dimensional keys is proposed for high security, big capacity and low noise information transmission. Multiple images to be encrypted are transformed into phase-only images with the iterative algorithm and then are encrypted by different random phase, respectively. The encrypted phase-only images are performed by inverse Fourier transform, respectively, thus new object functions are generated. The new functions are located in different blocks and padded zero for a sparse distribution, then they propagate to a specific region at different distances by angular spectrum diffraction, respectively and are superposed in order to form a single image. The single image is multiplied with a random phase in the frequency domain and then the phase part of the frequency spectrums is truncated and the amplitude information is reserved. The random phase, propagation distances, truncated phase information in frequency domain are employed as multiple dimensional keys. The iteration processing and sparse distribution greatly reduce the crosstalk among the multiple encryption images. The superposition of image sequences greatly improves the capacity of encrypted information. Several numerical experiments based on a designed optical system demonstrate that the proposed scheme can enhance encrypted information capacity and make image transmission at a highly desired security level.

Continuous-variable quantum key distribution with Gaussian source noise

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shen Yujie; Peng Xiang; Yang Jian

2011-05-15

Source noise affects the security of continuous-variable quantum key distribution (CV QKD) and is difficult to analyze. We propose a model to characterize Gaussian source noise through introducing a neutral party (Fred) who induces the noise with a general unitary transformation. Without knowing Fred's exact state, we derive the security bounds for both reverse and direct reconciliations and show that the bound for reverse reconciliation is tight.

A Visual Detection Learning Model

NASA Technical Reports Server (NTRS)

Beard, Bettina L.; Ahumada, Albert J., Jr.; Trejo, Leonard (Technical Monitor)

1998-01-01

Our learning model has memory templates representing the target-plus-noise and noise-alone stimulus sets. The best correlating template determines the response. The correlations and the feedback participate in the additive template updating rule. The model can predict the relative thresholds for detection in random, fixed and twin noise.

Robustifying blind image deblurring methods by simple filters

NASA Astrophysics Data System (ADS)

Liu, Yan; Zeng, Xiangrong; Huangpeng, Qizi; Fan, Jun; Zhou, Jinglun; Feng, Jing

2016-07-01

The state-of-the-art blind image deblurring (BID) methods are sensitive to noise, and most of them can deal with only small levels of Gaussian noise. In this paper, we use simple filters to present a robust BID framework which is able to robustify exiting BID methods to high-level Gaussian noise or/and Non-Gaussian noise. Experiments on images in presence of Gaussian noise, impulse noise (salt-and-pepper noise and random-valued noise) and mixed Gaussian-impulse noise, and a real-world blurry and noisy image show that the proposed method can faster estimate sharper kernels and better images, than that obtained by other methods.

ON NONSTATIONARY STOCHASTIC MODELS FOR EARTHQUAKES.

USGS Publications Warehouse

Safak, Erdal; Boore, David M.

1986-01-01

A seismological stochastic model for earthquake ground-motion description is presented. Seismological models are based on the physical properties of the source and the medium and have significant advantages over the widely used empirical models. The model discussed here provides a convenient form for estimating structural response by using random vibration theory. A commonly used random process for ground acceleration, filtered white-noise multiplied by an envelope function, introduces some errors in response calculations for structures whose periods are longer than the faulting duration. An alternate random process, filtered shot-noise process, eliminates these errors.

Effect of laser frequency noise on fiber-optic frequency reference distribution

NASA Technical Reports Server (NTRS)

Logan, R. T., Jr.; Lutes, G. F.; Maleki, L.

1989-01-01

The effect of the linewidth of a single longitude-mode laser on the frequency stability of a frequency reference transmitted over a single-mode optical fiber is analyzed. The interaction of the random laser frequency deviations with the dispersion of the optical fiber is considered to determine theoretically the effect on the Allan deviation (square root of the Allan variance) of the transmitted frequency reference. It is shown that the magnitude of this effect may determine the limit of the ultimate stability possible for frequency reference transmission on optical fiber, but is not a serious limitation to present system performance.

Dynamical behavior of a stochastic SVIR epidemic model with vaccination

NASA Astrophysics Data System (ADS)

Zhang, Xinhong; Jiang, Daqing; Hayat, Tasawar; Ahmad, Bashir

2017-10-01

In this paper, we investigate the dynamical behavior of SVIR models in random environments. Firstly, we show that if R0s < 1, the disease of stochastic autonomous SVIR model will die out exponentially; if R˜0s > 1, the disease will be prevail. Moreover, this system admits a unique stationary distribution and it is ergodic when R˜0s > 1. Results show that environmental white noise is helpful for disease control. Secondly, we give sufficient conditions for the existence of nontrivial periodic solutions to stochastic SVIR model with periodic parameters. Finally, numerical simulations validate the analytical results.

Continuous Variable Quantum Key Distribution Using Polarized Coherent States

NASA Astrophysics Data System (ADS)

Vidiella-Barranco, A.; Borelli, L. F. M.

We discuss a continuous variables method of quantum key distribution employing strongly polarized coherent states of light. The key encoding is performed using the variables known as Stokes parameters, rather than the field quadratures. Their quantum counterpart, the Stokes operators Ŝi (i=1,2,3), constitute a set of non-commuting operators, being the precision of simultaneous measurements of a pair of them limited by an uncertainty-like relation. Alice transmits a conveniently modulated two-mode coherent state, and Bob randomly measures one of the Stokes parameters of the incoming beam. After performing reconciliation and privacy amplification procedures, it is possible to distill a secret common key. We also consider a non-ideal situation, in which coherent states with thermal noise, instead of pure coherent states, are used for encoding.

Microscopic origin of read current noise in TaOx-based resistive switching memory by ultra-low temperature measurement

NASA Astrophysics Data System (ADS)

Pan, Yue; Cai, Yimao; Liu, Yefan; Fang, Yichen; Yu, Muxi; Tan, Shenghu; Huang, Ru

2016-04-01

TaOx-based resistive random access memory (RRAM) attracts considerable attention for the development of next generation nonvolatile memories. However, read current noise in RRAM is one of the critical concerns for storage application, and its microscopic origin is still under debate. In this work, the read current noise in TaOx-based RRAM was studied thoroughly. Based on a noise power spectral density analysis at room temperature and at ultra-low temperature of 25 K, discrete random telegraph noise (RTN) and continuous average current fluctuation (ACF) are identified and decoupled from the total read current noise in TaOx RRAM devices. A statistical comparison of noise amplitude further reveals that ACF depends strongly on the temperature, whereas RTN is independent of the temperature. Measurement results combined with conduction mechanism analysis show that RTN in TaOx RRAM devices arises from electron trapping/detrapping process in the hopping conduction, and ACF is originated from the thermal activation of conduction centers that form the percolation network. At last, a unified model in the framework of hopping conduction is proposed to explain the underlying mechanism of both RTN and ACF noise, which can provide meaningful guidelines for designing noise-immune RRAM devices.

Continuous-variable phase estimation with unitary and random linear disturbance

NASA Astrophysics Data System (ADS)

Delgado de Souza, Douglas; Genoni, Marco G.; Kim, M. S.

2014-10-01

We address the problem of continuous-variable quantum phase estimation in the presence of linear disturbance at the Hamiltonian level by means of Gaussian probe states. In particular we discuss both unitary and random disturbance by considering the parameter which characterizes the unwanted linear term present in the Hamiltonian as fixed (unitary disturbance) or random with a given probability distribution (random disturbance). We derive the optimal input Gaussian states at fixed energy, maximizing the quantum Fisher information over the squeezing angle and the squeezing energy fraction, and we discuss the scaling of the quantum Fisher information in terms of the output number of photons, nout. We observe that, in the case of unitary disturbance, the optimal state is a squeezed vacuum state and the quadratic scaling is conserved. As regards the random disturbance, we observe that the optimal squeezing fraction may not be equal to one and, for any nonzero value of the noise parameter, the quantum Fisher information scales linearly with the average number of photons. Finally, we discuss the performance of homodyne measurement by comparing the achievable precision with the ultimate limit imposed by the quantum Cramér-Rao bound.

The Physical Mechanism for Retinal Discrete Dark Noise: Thermal Activation or Cellular Ultraweak Photon Emission?

PubMed

Salari, Vahid; Scholkmann, Felix; Bokkon, Istvan; Shahbazi, Farhad; Tuszynski, Jack

2016-01-01

For several decades the physical mechanism underlying discrete dark noise of photoreceptors in the eye has remained highly controversial and poorly understood. It is known that the Arrhenius equation, which is based on the Boltzmann distribution for thermal activation, can model only a part (e.g. half of the activation energy) of the retinal dark noise experimentally observed for vertebrate rod and cone pigments. Using the Hinshelwood distribution instead of the Boltzmann distribution in the Arrhenius equation has been proposed as a solution to the problem. Here, we show that the using the Hinshelwood distribution does not solve the problem completely. As the discrete components of noise are indistinguishable in shape and duration from those produced by real photon induced photo-isomerization, the retinal discrete dark noise is most likely due to 'internal photons' inside cells and not due to thermal activation of visual pigments. Indeed, all living cells exhibit spontaneous ultraweak photon emission (UPE), mainly in the optical wavelength range, i.e., 350-700 nm. We show here that the retinal discrete dark noise has a similar rate as UPE and therefore dark noise is most likely due to spontaneous cellular UPE and not due to thermal activation.

Survival behavior in the cyclic Lotka-Volterra model with a randomly switching reaction rate

NASA Astrophysics Data System (ADS)

West, Robert; Mobilia, Mauro; Rucklidge, Alastair M.

2018-02-01

We study the influence of a randomly switching reproduction-predation rate on the survival behavior of the nonspatial cyclic Lotka-Volterra model, also known as the zero-sum rock-paper-scissors game, used to metaphorically describe the cyclic competition between three species. In large and finite populations, demographic fluctuations (internal noise) drive two species to extinction in a finite time, while the species with the smallest reproduction-predation rate is the most likely to be the surviving one (law of the weakest). Here we model environmental (external) noise by assuming that the reproduction-predation rate of the strongest species (the fastest to reproduce and predate) in a given static environment randomly switches between two values corresponding to more and less favorable external conditions. We study the joint effect of environmental and demographic noise on the species survival probabilities and on the mean extinction time. In particular, we investigate whether the survival probabilities follow the law of the weakest and analyze their dependence on the external noise intensity and switching rate. Remarkably, when, on average, there is a finite number of switches prior to extinction, the survival probability of the predator of the species whose reaction rate switches typically varies nonmonotonically with the external noise intensity (with optimal survival about a critical noise strength). We also outline the relationship with the case where all reaction rates switch on markedly different time scales.

Origin and evolution of circular waves and spirals in Dictyostelium discoideum territories.

PubMed

Pálsson, E; Cox, E C

1996-02-06

Randomly distributed Dictyostelium discoideum cells form cooperative territories by signaling to each other with cAMP. Cells initiate the process by sending out pulsatile signals, which propagate as waves. With time, circular and spiral patterns form. We show that by adding spatial and temporal noise to the levels of an important regulator of external cAMP levels, the cAMP phosphodiesterase inhibitor, we can explain the natural progression of the system from randomly firing cells to circular waves whose symmetries break to form double- and single- or multi-armed spirals. When phosphodiesterase inhibitor is increased with time, mimicking experimental data, the wavelength of the spirals shortens, and a proportion of them evolve into pairs of connected spirals. We compare these results to recent experiments, finding that the temporal and spatial correspondence between experiment and model is very close.

Analysis of crackling noise using the maximum-likelihood method: Power-law mixing and exponential damping.

PubMed

Salje, Ekhard K H; Planes, Antoni; Vives, Eduard

2017-10-01

Crackling noise can be initiated by competing or coexisting mechanisms. These mechanisms can combine to generate an approximate scale invariant distribution that contains two or more contributions. The overall distribution function can be analyzed, to a good approximation, using maximum-likelihood methods and assuming that it follows a power law although with nonuniversal exponents depending on a varying lower cutoff. We propose that such distributions are rather common and originate from a simple superposition of crackling noise distributions or exponential damping.

Application of the Hotelling and ideal observers to detection and localization of exoplanets.

PubMed

Caucci, Luca; Barrett, Harrison H; Devaney, Nicholas; Rodríguez, Jeffrey J

2007-12-01

The ideal linear discriminant or Hotelling observer is widely used for detection tasks and image-quality assessment in medical imaging, but it has had little application in other imaging fields. We apply it to detection of planets outside of our solar system with long-exposure images obtained from ground-based or space-based telescopes. The statistical limitations in this problem include Poisson noise arising mainly from the host star, electronic noise in the image detector, randomness or uncertainty in the point-spread function (PSF) of the telescope, and possibly a random background. PSF randomness is reduced but not eliminated by the use of adaptive optics. We concentrate here on the effects of Poisson and electronic noise, but we also show how to extend the calculation to include a random PSF. For the case where the PSF is known exactly, we compare the Hotelling observer to other observers commonly used for planet detection; comparison is based on receiver operating characteristic (ROC) and localization ROC (LROC) curves.

Application of the Hotelling and ideal observers to detection and localization of exoplanets

PubMed Central

Caucci, Luca; Barrett, Harrison H.; Devaney, Nicholas; Rodríguez, Jeffrey J.

2008-01-01

The ideal linear discriminant or Hotelling observer is widely used for detection tasks and image-quality assessment in medical imaging, but it has had little application in other imaging fields. We apply it to detection of planets outside of our solar system with long-exposure images obtained from ground-based or space-based telescopes. The statistical limitations in this problem include Poisson noise arising mainly from the host star, electronic noise in the image detector, randomness or uncertainty in the point-spread function (PSF) of the telescope, and possibly a random background. PSF randomness is reduced but not eliminated by the use of adaptive optics. We concentrate here on the effects of Poisson and electronic noise, but we also show how to extend the calculation to include a random PSF. For the case where the PSF is known exactly, we compare the Hotelling observer to other observers commonly used for planet detection; comparison is based on receiver operating characteristic (ROC) and localization ROC (LROC) curves. PMID:18059905

Quantum Entanglement Growth under Random Unitary Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nahum, Adam; Ruhman, Jonathan; Vijay, Sagar

Characterizing how entanglement grows with time in a many-body system, for example, after a quantum quench, is a key problem in nonequilibrium quantum physics. We study this problem for the case of random unitary dynamics, representing either Hamiltonian evolution with time-dependent noise or evolution by a random quantum circuit. Our results reveal a universal structure behind noisy entanglement growth, and also provide simple new heuristics for the “entanglement tsunami” in Hamiltonian systems without noise. In 1D, we show that noise causes the entanglement entropy across a cut to grow according to the celebrated Kardar-Parisi-Zhang (KPZ) equation. The mean entanglement growsmore » linearly in time, while fluctuations grow like (time) 1/3 and are spatially correlated over a distance ∝(time) 2/3. We derive KPZ universal behavior in three complementary ways, by mapping random entanglement growth to (i) a stochastic model of a growing surface, (ii) a “minimal cut” picture, reminiscent of the Ryu-Takayanagi formula in holography, and (iii) a hydrodynamic problem involving the dynamical spreading of operators. We demonstrate KPZ universality in 1D numerically using simulations of random unitary circuits. Importantly, the leading-order time dependence of the entropy is deterministic even in the presence of noise, allowing us to propose a simple coarse grained minimal cut picture for the entanglement growth of generic Hamiltonians, even without noise, in arbitrary dimensionality. We clarify the meaning of the “velocity” of entanglement growth in the 1D entanglement tsunami. We show that in higher dimensions, noisy entanglement evolution maps to the well-studied problem of pinning of a membrane or domain wall by disorder.« less

Quantum Entanglement Growth under Random Unitary Dynamics

DOE PAGES

Nahum, Adam; Ruhman, Jonathan; Vijay, Sagar; ...

2017-07-24

Characterizing how entanglement grows with time in a many-body system, for example, after a quantum quench, is a key problem in nonequilibrium quantum physics. We study this problem for the case of random unitary dynamics, representing either Hamiltonian evolution with time-dependent noise or evolution by a random quantum circuit. Our results reveal a universal structure behind noisy entanglement growth, and also provide simple new heuristics for the “entanglement tsunami” in Hamiltonian systems without noise. In 1D, we show that noise causes the entanglement entropy across a cut to grow according to the celebrated Kardar-Parisi-Zhang (KPZ) equation. The mean entanglement growsmore » linearly in time, while fluctuations grow like (time) 1/3 and are spatially correlated over a distance ∝(time) 2/3. We derive KPZ universal behavior in three complementary ways, by mapping random entanglement growth to (i) a stochastic model of a growing surface, (ii) a “minimal cut” picture, reminiscent of the Ryu-Takayanagi formula in holography, and (iii) a hydrodynamic problem involving the dynamical spreading of operators. We demonstrate KPZ universality in 1D numerically using simulations of random unitary circuits. Importantly, the leading-order time dependence of the entropy is deterministic even in the presence of noise, allowing us to propose a simple coarse grained minimal cut picture for the entanglement growth of generic Hamiltonians, even without noise, in arbitrary dimensionality. We clarify the meaning of the “velocity” of entanglement growth in the 1D entanglement tsunami. We show that in higher dimensions, noisy entanglement evolution maps to the well-studied problem of pinning of a membrane or domain wall by disorder.« less

Constraining the noise-free distribution of halo spin parameters

NASA Astrophysics Data System (ADS)

Benson, Andrew J.

2017-11-01

Any measurement made using an N-body simulation is subject to noise due to the finite number of particles used to sample the dark matter distribution function, and the lack of structure below the simulation resolution. This noise can be particularly significant when attempting to measure intrinsically small quantities, such as halo spin. In this work, we develop a model to describe the effects of particle noise on halo spin parameters. This model is calibrated using N-body simulations in which the particle noise can be treated as a Poisson process on the underlying dark matter distribution function, and we demonstrate that this calibrated model reproduces measurements of halo spin parameter error distributions previously measured in N-body convergence studies. Utilizing this model, along with previous measurements of the distribution of halo spin parameters in N-body simulations, we place constraints on the noise-free distribution of halo spins. We find that the noise-free median spin is 3 per cent lower than that measured directly from the N-body simulation, corresponding to a shift of approximately 40 times the statistical uncertainty in this measurement arising purely from halo counting statistics. We also show that measurement of the spin of an individual halo to 10 per cent precision requires at least 4 × 104 particles in the halo - for haloes containing 200 particles, the fractional error on spins measured for individual haloes is of order unity. N-body simulations should be viewed as the results of a statistical experiment applied to a model of dark matter structure formation. When viewed in this way, it is clear that determination of any quantity from such a simulation should be made through forward modelling of the effects of particle noise.

Statistical Characteristics of the Gaussian-Noise Spikes Exceeding the Specified Threshold as Applied to Discharges in a Thundercloud

NASA Astrophysics Data System (ADS)

Klimenko, V. V.

2017-12-01

We obtain expressions for the probabilities of the normal-noise spikes with the Gaussian correlation function and for the probability density of the inter-spike intervals. As distinct from the delta-correlated noise, in which the intervals are distributed by the exponential law, the probability of the subsequent spike depends on the previous spike and the interval-distribution law deviates from the exponential one for a finite noise-correlation time (frequency-bandwidth restriction). This deviation is the most pronounced for a low detection threshold. Similarity of the behaviors of the distributions of the inter-discharge intervals in a thundercloud and the noise spikes for the varying repetition rate of the discharges/spikes, which is determined by the ratio of the detection threshold to the root-mean-square value of noise, is observed. The results of this work can be useful for the quantitative description of the statistical characteristics of the noise spikes and studying the role of fluctuations for the discharge emergence in a thundercloud.

Worst case encoder-decoder policies for a communication system in the presence of an unknown probabilistic jammer

NASA Astrophysics Data System (ADS)

Cascio, David M.

1988-05-01

States of nature or observed data are often stochastically modelled as Gaussian random variables. At times it is desirable to transmit this information from a source to a destination with minimal distortion. Complicating this objective is the possible presence of an adversary attempting to disrupt this communication. In this report, solutions are provided to a class of minimax and maximin decision problems, which involve the transmission of a Gaussian random variable over a communications channel corrupted by both additive Gaussian noise and probabilistic jamming noise. The jamming noise is termed probabilistic in the sense that with nonzero probability 1-P, the jamming noise is prevented from corrupting the channel. We shall seek to obtain optimal linear encoder-decoder policies which minimize given quadratic distortion measures.

Faxed document image restoration method based on local pixel patterns

NASA Astrophysics Data System (ADS)

Akiyama, Teruo; Miyamoto, Nobuo; Oguro, Masami; Ogura, Kenji

1998-04-01

A method for restoring degraded faxed document images using the patterns of pixels that construct small areas in a document is proposed. The method effectively restores faxed images that contain the halftone textures and/or density salt-and-pepper noise that degrade OCR system performance. The halftone image restoration process, white-centered 3 X 3 pixels, in which black-and-white pixels alternate, are identified first using the distribution of the pixel values as halftone textures, and then the white center pixels are inverted to black. To remove high-density salt- and-pepper noise, it is assumed that the degradation is caused by ill-balanced bias and inappropriate thresholding of the sensor output which results in the addition of random noise. Restored image can be estimated using an approximation that uses the inverse operation of the assumed original process. In order to process degraded faxed images, the algorithms mentioned above are combined. An experiment is conducted using 24 especially poor quality examples selected from data sets that exemplify what practical fax- based OCR systems cannot handle. The maximum recovery rate in terms of mean square error was 98.8 percent.

Intrinsic speckle noise in in-line particle holography due to polydisperse and continuous particle sizes

NASA Astrophysics Data System (ADS)

Edwards, Philip J.; Hobson, Peter R.; Rodgers, G. J.

2000-08-01

In-line particle holography is subject to image deterioration due to intrinsic speckle noise. The resulting reduction in the signal to noise ratio (SNR) of the replayed image can become critical for applications such as holographic particle velocimetry (HPV) and 3D visualisation of marine plankton. Work has been done to extend the mono-disperse model relevant to HPV to include poly-disperse particle fields appropriate for the visualisation of marine plankton. Continuous and discrete particle fields are both considered. It is found that random walk statistics still apply for the poly-disperse case. The speckle field is simply the summation of the individual speckle patters due to each scatter size. Therefor the characteristic speckle parameter (which encompasses particle diameter, concentration and sample depth) is alos just the summation of the individual speckle parameters. This reduces the SNR calculation to the same form as for the mono-disperse case. For the continuous situation three distributions, power, exponential and Gaussian are discussed with the resulting SNR calcuated. The work presented here was performed as part of the Holomar project to produce a working underwater holographic camera for recording plankton.

Visuo‐manual tracking: does intermittent control with aperiodic sampling explain linear power and non‐linear remnant without sensorimotor noise?

PubMed Central

Gawthrop, Peter J.; Lakie, Martin; Loram, Ian D.

2017-01-01

Key points A human controlling an external system is described most easily and conventionally as linearly and continuously translating sensory input to motor output, with the inevitable output remnant, non‐linearly related to the input, attributed to sensorimotor noise.Recent experiments show sustained manual tracking involves repeated refractoriness (insensitivity to sensory information for a certain duration), with the temporary 200–500 ms periods of irresponsiveness to sensory input making the control process intrinsically non‐linear.This evidence calls for re‐examination of the extent to which random sensorimotor noise is required to explain the non‐linear remnant.This investigation of manual tracking shows how the full motor output (linear component and remnant) can be explained mechanistically by aperiodic sampling triggered by prediction error thresholds.Whereas broadband physiological noise is general to all processes, aperiodic sampling is associated with sensorimotor decision making within specific frontal, striatal and parietal networks; we conclude that manual tracking utilises such slow serial decision making pathways up to several times per second. Abstract The human operator is described adequately by linear translation of sensory input to motor output. Motor output also always includes a non‐linear remnant resulting from random sensorimotor noise from multiple sources, and non‐linear input transformations, for example thresholds or refractory periods. Recent evidence showed that manual tracking incurs substantial, serial, refractoriness (insensitivity to sensory information of 350 and 550 ms for 1st and 2nd order systems respectively). Our two questions are: (i) What are the comparative merits of explaining the non‐linear remnant using noise or non‐linear transformations? (ii) Can non‐linear transformations represent serial motor decision making within the sensorimotor feedback loop intrinsic to tracking? Twelve participants (instructed to act in three prescribed ways) manually controlled two systems (1st and 2nd order) subject to a periodic multi‐sine disturbance. Joystick power was analysed using three models, continuous‐linear‐control (CC), continuous‐linear‐control with calculated noise spectrum (CCN), and intermittent control with aperiodic sampling triggered by prediction error thresholds (IC). Unlike the linear mechanism, the intermittent control mechanism explained the majority of total power (linear and remnant) (77–87% vs. 8–48%, IC vs. CC). Between conditions, IC used thresholds and distributions of open loop intervals consistent with, respectively, instructions and previous measured, model independent values; whereas CCN required changes in noise spectrum deviating from broadband, signal dependent noise. We conclude that manual tracking uses open loop predictive control with aperiodic sampling. Because aperiodic sampling is inherent to serial decision making within previously identified, specific frontal, striatal and parietal networks we suggest that these structures are intimately involved in visuo‐manual tracking. PMID:28833126

Robust shot-noise measurement for continuous-variable quantum key distribution

NASA Astrophysics Data System (ADS)

Kunz-Jacques, Sébastien; Jouguet, Paul

2015-02-01

We study a practical method to measure the shot noise in real time in continuous-variable quantum key distribution systems. The amount of secret key that can be extracted from the raw statistics depends strongly on this quantity since it affects in particular the computation of the excess noise (i.e., noise in excess of the shot noise) added by an eavesdropper on the quantum channel. Some powerful quantum hacking attacks relying on faking the estimated value of the shot noise to hide an intercept and resend strategy were proposed. Here, we provide experimental evidence that our method can defeat the saturation attack and the wavelength attack.

Predicting Anthropogenic Noise Contributions to US Waters.

PubMed

Gedamke, Jason; Ferguson, Megan; Harrison, Jolie; Hatch, Leila; Henderson, Laurel; Porter, Michael B; Southall, Brandon L; Van Parijs, Sofie

2016-01-01

To increase understanding of the potential effects of chronic underwater noise in US waters, the National Oceanic and Atmospheric Administration (NOAA) organized two working groups in 2011, collectively called "CetSound," to develop tools to map the density and distribution of cetaceans (CetMap) and predict the contribution of human activities to underwater noise (SoundMap). The SoundMap effort utilized data on density, distribution, acoustic signatures of dominant noise sources, and environmental descriptors to map estimated temporal, spatial, and spectral contributions to background noise. These predicted soundscapes are an initial step toward assessing chronic anthropogenic noise impacts on the ocean's varied acoustic habitats and the animals utilizing them.

Validation of CT dose-reduction simulation

PubMed Central

Massoumzadeh, Parinaz; Don, Steven; Hildebolt, Charles F.; Bae, Kyongtae T.; Whiting, Bruce R.

2009-01-01

The objective of this research was to develop and validate a custom computed tomography dose-reduction simulation technique for producing images that have an appearance consistent with the same scan performed at a lower mAs (with fixed kVp, rotation time, and collimation). Synthetic noise is added to projection (sinogram) data, incorporating a stochastic noise model that includes energy-integrating detectors, tube-current modulation, bowtie beam filtering, and electronic system noise. Experimental methods were developed to determine the parameters required for each component of the noise model. As a validation, the outputs of the simulations were compared to measurements with cadavers in the image domain and with phantoms in both the sinogram and image domain, using an unbiased root-mean-square relative error metric to quantify agreement in noise processes. Four-alternative forced-choice (4AFC) observer studies were conducted to confirm the realistic appearance of simulated noise, and the effects of various system model components on visual noise were studied. The “just noticeable difference (JND)” in noise levels was analyzed to determine the sensitivity of observers to changes in noise level. Individual detector measurements were shown to be normally distributed (p>0.54), justifying the use of a Gaussian random noise generator for simulations. Phantom tests showed the ability to match original and simulated noise variance in the sinogram domain to within 5.6%±1.6% (standard deviation), which was then propagated into the image domain with errors less than 4.1%±1.6%. Cadaver measurements indicated that image noise was matched to within 2.6%±2.0%. More importantly, the 4AFC observer studies indicated that the simulated images were realistic, i.e., no detectable difference between simulated and original images (p=0.86) was observed. JND studies indicated that observers’ sensitivity to change in noise levels corresponded to a 25% difference in dose, which is far larger than the noise accuracy achieved by simulation. In summary, the dose-reduction simulation tool demonstrated excellent accuracy in providing realistic images. The methodology promises to be a useful tool for researchers and radiologists to explore dose reduction protocols in an effort to produce diagnostic images with radiation dose “as low as reasonably achievable.” PMID:19235386

Calibration of Predictor Models Using Multiple Validation Experiments

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2015-01-01

This paper presents a framework for calibrating computational models using data from several and possibly dissimilar validation experiments. The offset between model predictions and observations, which might be caused by measurement noise, model-form uncertainty, and numerical error, drives the process by which uncertainty in the models parameters is characterized. The resulting description of uncertainty along with the computational model constitute a predictor model. Two types of predictor models are studied: Interval Predictor Models (IPMs) and Random Predictor Models (RPMs). IPMs use sets to characterize uncertainty, whereas RPMs use random vectors. The propagation of a set through a model makes the response an interval valued function of the state, whereas the propagation of a random vector yields a random process. Optimization-based strategies for calculating both types of predictor models are proposed. Whereas the formulations used to calculate IPMs target solutions leading to the interval value function of minimal spread containing all observations, those for RPMs seek to maximize the models' ability to reproduce the distribution of observations. Regarding RPMs, we choose a structure for the random vector (i.e., the assignment of probability to points in the parameter space) solely dependent on the prediction error. As such, the probabilistic description of uncertainty is not a subjective assignment of belief, nor is it expected to asymptotically converge to a fixed value, but instead it casts the model's ability to reproduce the experimental data. This framework enables evaluating the spread and distribution of the predicted response of target applications depending on the same parameters beyond the validation domain.

Noise-enhanced convolutional neural networks.

PubMed

Audhkhasi, Kartik; Osoba, Osonde; Kosko, Bart

2016-06-01

Injecting carefully chosen noise can speed convergence in the backpropagation training of a convolutional neural network (CNN). The Noisy CNN algorithm speeds training on average because the backpropagation algorithm is a special case of the generalized expectation-maximization (EM) algorithm and because such carefully chosen noise always speeds up the EM algorithm on average. The CNN framework gives a practical way to learn and recognize images because backpropagation scales with training data. It has only linear time complexity in the number of training samples. The Noisy CNN algorithm finds a special separating hyperplane in the network's noise space. The hyperplane arises from the likelihood-based positivity condition that noise-boosts the EM algorithm. The hyperplane cuts through a uniform-noise hypercube or Gaussian ball in the noise space depending on the type of noise used. Noise chosen from above the hyperplane speeds training on average. Noise chosen from below slows it on average. The algorithm can inject noise anywhere in the multilayered network. Adding noise to the output neurons reduced the average per-iteration training-set cross entropy by 39% on a standard MNIST image test set of handwritten digits. It also reduced the average per-iteration training-set classification error by 47%. Adding noise to the hidden layers can also reduce these performance measures. The noise benefit is most pronounced for smaller data sets because the largest EM hill-climbing gains tend to occur in the first few iterations. This noise effect can assist random sampling from large data sets because it allows a smaller random sample to give the same or better performance than a noiseless sample gives. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comparison of Image Processing Techniques using Random Noise Radar

DTIC Science & Technology

2014-03-27

detection UWB ultra-wideband EM electromagnetic CW continuous wave RCS radar cross section RFI radio frequency interference FFT fast Fourier transform...several factors including radar cross section (RCS), orientation, and material makeup. A single monostatic radar at some position collects only range and...Chapter 2 is to provide the theory behind noise radar and SAR imaging. Section 2.1 presents the basic concepts in transmitting and receiving random

Applications of fractional lower order S transform time frequency filtering algorithm to machine fault diagnosis

PubMed Central

Wang, Haibin; Zha, Daifeng; Li, Peng; Xie, Huicheng; Mao, Lili

2017-01-01

Stockwell transform(ST) time-frequency representation(ST-TFR) is a time frequency analysis method which combines short time Fourier transform with wavelet transform, and ST time frequency filtering(ST-TFF) method which takes advantage of time-frequency localized spectra can separate the signals from Gaussian noise. The ST-TFR and ST-TFF methods are used to analyze the fault signals, which is reasonable and effective in general Gaussian noise cases. However, it is proved that the mechanical bearing fault signal belongs to Alpha(α) stable distribution process(1 < α < 2) in this paper, even the noise also is α stable distribution in some special cases. The performance of ST-TFR method will degrade under α stable distribution noise environment, following the ST-TFF method fail. Hence, a new fractional lower order ST time frequency representation(FLOST-TFR) method employing fractional lower order moment and ST and inverse FLOST(IFLOST) are proposed in this paper. A new FLOST time frequency filtering(FLOST-TFF) algorithm based on FLOST-TFR method and IFLOST is also proposed, whose simplified method is presented in this paper. The discrete implementation of FLOST-TFF algorithm is deduced, and relevant steps are summarized. Simulation results demonstrate that FLOST-TFR algorithm is obviously better than the existing ST-TFR algorithm under α stable distribution noise, which can work better under Gaussian noise environment, and is robust. The FLOST-TFF method can effectively filter out α stable distribution noise, and restore the original signal. The performance of FLOST-TFF algorithm is better than the ST-TFF method, employing which mixed MSEs are smaller when α and generalized signal noise ratio(GSNR) change. Finally, the FLOST-TFR and FLOST-TFF methods are applied to analyze the outer race fault signal and extract their fault features under α stable distribution noise, where excellent performances can be shown. PMID:28406916

Event-Based Variance-Constrained ${\\mathcal {H}}_{\\infty }$ Filtering for Stochastic Parameter Systems Over Sensor Networks With Successive Missing Measurements.

PubMed

Wang, Licheng; Wang, Zidong; Han, Qing-Long; Wei, Guoliang

2018-03-01

This paper is concerned with the distributed filtering problem for a class of discrete time-varying stochastic parameter systems with error variance constraints over a sensor network where the sensor outputs are subject to successive missing measurements. The phenomenon of the successive missing measurements for each sensor is modeled via a sequence of mutually independent random variables obeying the Bernoulli binary distribution law. To reduce the frequency of unnecessary data transmission and alleviate the communication burden, an event-triggered mechanism is introduced for the sensor node such that only some vitally important data is transmitted to its neighboring sensors when specific events occur. The objective of the problem addressed is to design a time-varying filter such that both the requirements and the variance constraints are guaranteed over a given finite-horizon against the random parameter matrices, successive missing measurements, and stochastic noises. By recurring to stochastic analysis techniques, sufficient conditions are established to ensure the existence of the time-varying filters whose gain matrices are then explicitly characterized in term of the solutions to a series of recursive matrix inequalities. A numerical simulation example is provided to illustrate the effectiveness of the developed event-triggered distributed filter design strategy.

Towards full waveform ambient noise inversion

NASA Astrophysics Data System (ADS)

Sager, Korbinian; Ermert, Laura; Boehm, Christian; Fichtner, Andreas

2018-01-01

In this work we investigate fundamentals of a method—referred to as full waveform ambient noise inversion—that improves the resolution of tomographic images by extracting waveform information from interstation correlation functions that cannot be used without knowing the distribution of noise sources. The fundamental idea is to drop the principle of Green function retrieval and to establish correlation functions as self-consistent observables in seismology. This involves the following steps: (1) We introduce an operator-based formulation of the forward problem of computing correlation functions. It is valid for arbitrary distributions of noise sources in both space and frequency, and for any type of medium, including 3-D elastic, heterogeneous and attenuating media. In addition, the formulation allows us to keep the derivations independent of time and frequency domain and it facilitates the application of adjoint techniques, which we use to derive efficient expressions to compute first and also second derivatives. The latter are essential for a resolution analysis that accounts for intra- and interparameter trade-offs. (2) In a forward modelling study we investigate the effect of noise sources and structure on different observables. Traveltimes are hardly affected by heterogeneous noise source distributions. On the other hand, the amplitude asymmetry of correlations is at least to first order insensitive to unmodelled Earth structure. Energy and waveform differences are sensitive to both structure and the distribution of noise sources. (3) We design and implement an appropriate inversion scheme, where the extraction of waveform information is successively increased. We demonstrate that full waveform ambient noise inversion has the potential to go beyond ambient noise tomography based on Green function retrieval and to refine noise source location, which is essential for a better understanding of noise generation. Inherent trade-offs between source and structure are quantified using Hessian-vector products.

Experimental study of a quantum random-number generator based on two independent lasers

NASA Astrophysics Data System (ADS)

Sun, Shi-Hai; Xu, Feihu

2017-12-01

A quantum random-number generator (QRNG) can produce true randomness by utilizing the inherent probabilistic nature of quantum mechanics. Recently, the spontaneous-emission quantum phase noise of the laser has been widely deployed for quantum random-number generation, due to its high rate, its low cost, and the feasibility of chip-scale integration. Here, we perform a comprehensive experimental study of a phase-noise-based QRNG with two independent lasers, each of which operates in either continuous-wave (CW) or pulsed mode. We implement the QRNG by operating the two lasers in three configurations, namely, CW + CW, CW + pulsed, and pulsed + pulsed, and demonstrate their trade-offs, strengths, and weaknesses.

Continuous variable quantum key distribution with modulated entangled states.

PubMed

Madsen, Lars S; Usenko, Vladyslav C; Lassen, Mikael; Filip, Radim; Andersen, Ulrik L

2012-01-01

Quantum key distribution enables two remote parties to grow a shared key, which they can use for unconditionally secure communication over a certain distance. The maximal distance depends on the loss and the excess noise of the connecting quantum channel. Several quantum key distribution schemes based on coherent states and continuous variable measurements are resilient to high loss in the channel, but are strongly affected by small amounts of channel excess noise. Here we propose and experimentally address a continuous variable quantum key distribution protocol that uses modulated fragile entangled states of light to greatly enhance the robustness to channel noise. We experimentally demonstrate that the resulting quantum key distribution protocol can tolerate more noise than the benchmark set by the ideal continuous variable coherent state protocol. Our scheme represents a very promising avenue for extending the distance for which secure communication is possible.

Probability theory plus noise: Replies to Crupi and Tentori (2016) and to Nilsson, Juslin, and Winman (2016).

PubMed

Costello, Fintan; Watts, Paul

2016-01-01

A standard assumption in much of current psychology is that people do not reason about probability using the rules of probability theory but instead use various heuristics or "rules of thumb," which can produce systematic reasoning biases. In Costello and Watts (2014), we showed that a number of these biases can be explained by a model where people reason according to probability theory but are subject to random noise. More importantly, that model also predicted agreement with probability theory for certain expressions that cancel the effects of random noise: Experimental results strongly confirmed this prediction, showing that probabilistic reasoning is simultaneously systematically biased and "surprisingly rational." In their commentaries on that paper, both Crupi and Tentori (2016) and Nilsson, Juslin, and Winman (2016) point to various experimental results that, they suggest, our model cannot explain. In this reply, we show that our probability theory plus noise model can in fact explain every one of the results identified by these authors. This gives a degree of additional support to the view that people's probability judgments embody the rational rules of probability theory and that biases in those judgments can be explained as simply effects of random noise. (c) 2015 APA, all rights reserved).

Collective Poisson process with periodic rates: applications in physics from micro-to nanodevices.

PubMed

da Silva, Roberto; Lamb, Luis C; Wirth, Gilson Inacio

2011-01-28

Continuous reductions in the dimensions of semiconductor devices have led to an increasing number of noise sources, including random telegraph signals (RTS) due to the capture and emission of electrons by traps at random positions between oxide and semiconductor. The models traditionally used for microscopic devices become of limited validity in nano- and mesoscale systems since, in such systems, distributed quantities such as electron and trap densities, and concepts like electron mobility, become inadequate to model electrical behaviour. In addition, current experimental works have shown that RTS in semiconductor devices based on carbon nanotubes lead to giant current fluctuations. Therefore, the physics of this phenomenon and techniques to decrease the amplitudes of RTS need to be better understood. This problem can be described as a collective Poisson process under different, but time-independent, rates, τ(c) and τ(e), that control the capture and emission of electrons by traps distributed over the oxide. Thus, models that consider calculations performed under time-dependent periodic capture and emission rates should be of interest in order to model more efficient devices. We show a complete theoretical description of a model that is capable of showing a noise reduction of current fluctuations in the time domain, and a reduction of the power spectral density in the frequency domain, in semiconductor devices as predicted by previous experimental work. We do so through numerical integrations and a novel Monte Carlo Markov chain (MCMC) algorithm based on microscopic discrete values. The proposed model also handles the ballistic regime, relevant in nano- and mesoscale devices. Finally, we show that the ballistic regime leads to nonlinearity in the electrical behaviour.

Social Noise: Generating Random Numbers from Twitter Streams

NASA Astrophysics Data System (ADS)

Fernández, Norberto; Quintas, Fernando; Sánchez, Luis; Arias, Jesús

2015-12-01

Due to the multiple applications of random numbers in computer systems (cryptography, online gambling, computer simulation, etc.) it is important to have mechanisms to generate these numbers. True Random Number Generators (TRNGs) are commonly used for this purpose. TRNGs rely on non-deterministic sources to generate randomness. Physical processes (like noise in semiconductors, quantum phenomenon, etc.) play this role in state of the art TRNGs. In this paper, we depart from previous work and explore the possibility of defining social TRNGs using the stream of public messages of the microblogging service Twitter as randomness source. Thus, we define two TRNGs based on Twitter stream information and evaluate them using the National Institute of Standards and Technology (NIST) statistical test suite. The results of the evaluation confirm the feasibility of the proposed approach.

Detection and characterization of lesions on low-radiation-dose abdominal CT images postprocessed with noise reduction filters.

PubMed

Kalra, Mannudeep K; Maher, Michael M; Blake, Michael A; Lucey, Brian C; Karau, Kelly; Toth, Thomas L; Avinash, Gopal; Halpern, Elkan F; Saini, Sanjay

2004-09-01

To assess the effect of noise reduction filters on detection and characterization of lesions on low-radiation-dose abdominal computed tomographic (CT) images. Low-dose CT images of abdominal lesions in 19 consecutive patients (11 women, eight men; age range, 32-78 years) were obtained at reduced tube currents (120-144 mAs). These baseline low-dose CT images were postprocessed with six noise reduction filters; the resulting postprocessed images were then randomly assorted with baseline images. Three radiologists performed independent evaluation of randomized images for presence, number, margins, attenuation, conspicuity, calcification, and enhancement of lesions, as well as image noise. Side-by-side comparison of baseline images with postprocessed images was performed by using a five-point scale for assessing lesion conspicuity and margins, image noise, beam hardening, and diagnostic acceptability. Quantitative noise and contrast-to-noise ratio were obtained for all liver lesions. Statistical analysis was performed by using the Wilcoxon signed rank test, Student t test, and kappa test of agreement. Significant reduction of noise was observed in images postprocessed with filter F compared with the noise in baseline nonfiltered images (P =.004). Although the number of lesions seen on baseline images and that seen on postprocessed images were identical, lesions were less conspicuous on postprocessed images than on baseline images. A decrease in quantitative image noise and contrast-to-noise ratio for liver lesions was noted with all noise reduction filters. There was good interobserver agreement (kappa = 0.7). Although the use of currently available noise reduction filters improves image noise and ameliorates beam-hardening artifacts at low-dose CT, such filters are limited by a compromise in lesion conspicuity and appearance in comparison with lesion conspicuity and appearance on baseline low-dose CT images. Copyright RSNA, 2004

Identifying early-warning signals of critical transitions with strong noise by dynamical network markers

PubMed Central

Liu, Rui; Chen, Pei; Aihara, Kazuyuki; Chen, Luonan

2015-01-01

Identifying early-warning signals of a critical transition for a complex system is difficult, especially when the target system is constantly perturbed by big noise, which makes the traditional methods fail due to the strong fluctuations of the observed data. In this work, we show that the critical transition is not traditional state-transition but probability distribution-transition when the noise is not sufficiently small, which, however, is a ubiquitous case in real systems. We present a model-free computational method to detect the warning signals before such transitions. The key idea behind is a strategy: “making big noise smaller” by a distribution-embedding scheme, which transforms the data from the observed state-variables with big noise to their distribution-variables with small noise, and thus makes the traditional criteria effective because of the significantly reduced fluctuations. Specifically, increasing the dimension of the observed data by moment expansion that changes the system from state-dynamics to probability distribution-dynamics, we derive new data in a higher-dimensional space but with much smaller noise. Then, we develop a criterion based on the dynamical network marker (DNM) to signal the impending critical transition using the transformed higher-dimensional data. We also demonstrate the effectiveness of our method in biological, ecological and financial systems. PMID:26647650

The Physical Mechanism for Retinal Discrete Dark Noise: Thermal Activation or Cellular Ultraweak Photon Emission?

PubMed Central

Salari, Vahid; Scholkmann, Felix; Bokkon, Istvan; Shahbazi, Farhad; Tuszynski, Jack

2016-01-01

For several decades the physical mechanism underlying discrete dark noise of photoreceptors in the eye has remained highly controversial and poorly understood. It is known that the Arrhenius equation, which is based on the Boltzmann distribution for thermal activation, can model only a part (e.g. half of the activation energy) of the retinal dark noise experimentally observed for vertebrate rod and cone pigments. Using the Hinshelwood distribution instead of the Boltzmann distribution in the Arrhenius equation has been proposed as a solution to the problem. Here, we show that the using the Hinshelwood distribution does not solve the problem completely. As the discrete components of noise are indistinguishable in shape and duration from those produced by real photon induced photo-isomerization, the retinal discrete dark noise is most likely due to ‘internal photons’ inside cells and not due to thermal activation of visual pigments. Indeed, all living cells exhibit spontaneous ultraweak photon emission (UPE), mainly in the optical wavelength range, i.e., 350–700 nm. We show here that the retinal discrete dark noise has a similar rate as UPE and therefore dark noise is most likely due to spontaneous cellular UPE and not due to thermal activation. PMID:26950936

The joint time-frequency spectrogram structure of heptanes boilover noise

NASA Astrophysics Data System (ADS)

Xu, Qiang

2006-04-01

An experiment was conducted to study the noise characteristics in the boilover phenomena. The boilover occurs in the combustion of a liquid fuel floating on water. It will cause a sharp increase in burning rate and external radiation. Explosive burning of the fuel would cause potential safety consequence. Combustion noise accompanies the development of fire and displays different characteristics in typical period. These characteristics can be used to predict the start time of boilover. The acoustic signal in boilover procedure during the combustion of heptanes-water mixture is obtained in a set of experiments. Joint time-frequency analysis (JTFA) method is applied in the treatment of noise data. Several JTFA algorithms were used in the evaluation. These algorithms include Gabor, adaptive spectrogram, cone shape distribution, choi-williams distribution, Wigner-Ville Distribution, and Short Time Fourier Transform with different windows such as rectangular, Blackman, Hamming and Hanning. Time-frequency distribution patterns of the combustion noise are obtained, and they are compared with others from jet flow and small plastic bubble blow up.

Parametric and non-parametric masking of randomness in sequence alignments can be improved and leads to better resolved trees.

PubMed

Kück, Patrick; Meusemann, Karen; Dambach, Johannes; Thormann, Birthe; von Reumont, Björn M; Wägele, Johann W; Misof, Bernhard

2010-03-31

Methods of alignment masking, which refers to the technique of excluding alignment blocks prior to tree reconstructions, have been successful in improving the signal-to-noise ratio in sequence alignments. However, the lack of formally well defined methods to identify randomness in sequence alignments has prevented a routine application of alignment masking. In this study, we compared the effects on tree reconstructions of the most commonly used profiling method (GBLOCKS) which uses a predefined set of rules in combination with alignment masking, with a new profiling approach (ALISCORE) based on Monte Carlo resampling within a sliding window, using different data sets and alignment methods. While the GBLOCKS approach excludes variable sections above a certain threshold which choice is left arbitrary, the ALISCORE algorithm is free of a priori rating of parameter space and therefore more objective. ALISCORE was successfully extended to amino acids using a proportional model and empirical substitution matrices to score randomness in multiple sequence alignments. A complex bootstrap resampling leads to an even distribution of scores of randomly similar sequences to assess randomness of the observed sequence similarity. Testing performance on real data, both masking methods, GBLOCKS and ALISCORE, helped to improve tree resolution. The sliding window approach was less sensitive to different alignments of identical data sets and performed equally well on all data sets. Concurrently, ALISCORE is capable of dealing with different substitution patterns and heterogeneous base composition. ALISCORE and the most relaxed GBLOCKS gap parameter setting performed best on all data sets. Correspondingly, Neighbor-Net analyses showed the most decrease in conflict. Alignment masking improves signal-to-noise ratio in multiple sequence alignments prior to phylogenetic reconstruction. Given the robust performance of alignment profiling, alignment masking should routinely be used to improve tree reconstructions. Parametric methods of alignment profiling can be easily extended to more complex likelihood based models of sequence evolution which opens the possibility of further improvements.

Microscopic origin of read current noise in TaO{sub x}-based resistive switching memory by ultra-low temperature measurement

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pan, Yue; Cai, Yimao, E-mail: caiyimao@pku.edu.cn; Liu, Yefan

TaO{sub x}-based resistive random access memory (RRAM) attracts considerable attention for the development of next generation nonvolatile memories. However, read current noise in RRAM is one of the critical concerns for storage application, and its microscopic origin is still under debate. In this work, the read current noise in TaO{sub x}-based RRAM was studied thoroughly. Based on a noise power spectral density analysis at room temperature and at ultra-low temperature of 25 K, discrete random telegraph noise (RTN) and continuous average current fluctuation (ACF) are identified and decoupled from the total read current noise in TaO{sub x} RRAM devices. A statisticalmore » comparison of noise amplitude further reveals that ACF depends strongly on the temperature, whereas RTN is independent of the temperature. Measurement results combined with conduction mechanism analysis show that RTN in TaO{sub x} RRAM devices arises from electron trapping/detrapping process in the hopping conduction, and ACF is originated from the thermal activation of conduction centers that form the percolation network. At last, a unified model in the framework of hopping conduction is proposed to explain the underlying mechanism of both RTN and ACF noise, which can provide meaningful guidelines for designing noise-immune RRAM devices.« less

A homodyne detector integrated onto a photonic chip for measuring quantum states and generating random numbers

NASA Astrophysics Data System (ADS)

Raffaelli, Francesco; Ferranti, Giacomo; Mahler, Dylan H.; Sibson, Philip; Kennard, Jake E.; Santamato, Alberto; Sinclair, Gary; Bonneau, Damien; Thompson, Mark G.; Matthews, Jonathan C. F.

2018-04-01

Optical homodyne detection has found use as a characterisation tool in a range of quantum technologies. So far implementations have been limited to bulk optics. Here we present the optical integration of a homodyne detector onto a silicon photonics chip. The resulting device operates at high speed, up 150 MHz, it is compact and it operates with low noise, quantified with 11 dB clearance between shot noise and electronic noise. We perform on-chip quantum tomography of coherent states with the detector and show that it meets the requirements for characterising more general quantum states of light. We also show that the detector is able to produce quantum random numbers at a rate of 1.2 Gbps, by measuring the vacuum state of the electromagnetic field and applying off-line post processing. The produced random numbers pass all the statistical tests provided by the NIST test suite.

Moment Lyapunov Exponent and Stochastic Stability of Binary Airfoil under Combined Harmonic and Non-Gaussian Colored Noise Excitations

NASA Astrophysics Data System (ADS)

Hu, D. L.; Liu, X. B.

Both periodic loading and random forces commonly co-exist in real engineering applications. However, the dynamic behavior, especially dynamic stability of systems under parametric periodic and random excitations has been reported little in the literature. In this study, the moment Lyapunov exponent and stochastic stability of binary airfoil under combined harmonic and non-Gaussian colored noise excitations are investigated. The noise is simplified to an Ornstein-Uhlenbeck process by applying the path-integral method. Via the singular perturbation method, the second-order expansions of the moment Lyapunov exponent are obtained, which agree well with the results obtained by the Monte Carlo simulation. Finally, the effects of the noise and parametric resonance (such as subharmonic resonance and combination additive resonance) on the stochastic stability of the binary airfoil system are discussed.

Calibration of visually guided reaching is driven by error-corrective learning and internal dynamics.

PubMed

Cheng, Sen; Sabes, Philip N

2007-04-01

The sensorimotor calibration of visually guided reaching changes on a trial-to-trial basis in response to random shifts in the visual feedback of the hand. We show that a simple linear dynamical system is sufficient to model the dynamics of this adaptive process. In this model, an internal variable represents the current state of sensorimotor calibration. Changes in this state are driven by error feedback signals, which consist of the visually perceived reach error, the artificial shift in visual feedback, or both. Subjects correct for > or =20% of the error observed on each movement, despite being unaware of the visual shift. The state of adaptation is also driven by internal dynamics, consisting of a decay back to a baseline state and a "state noise" process. State noise includes any source of variability that directly affects the state of adaptation, such as variability in sensory feedback processing, the computations that drive learning, or the maintenance of the state. This noise is accumulated in the state across trials, creating temporal correlations in the sequence of reach errors. These correlations allow us to distinguish state noise from sensorimotor performance noise, which arises independently on each trial from random fluctuations in the sensorimotor pathway. We show that these two noise sources contribute comparably to the overall magnitude of movement variability. Finally, the dynamics of adaptation measured with random feedback shifts generalizes to the case of constant feedback shifts, allowing for a direct comparison of our results with more traditional blocked-exposure experiments.

Reducing Modeling Error of Graphical Methods for Estimating Volume of Distribution Measurements in PIB-PET study

PubMed Central

Guo, Hongbin; Renaut, Rosemary A; Chen, Kewei; Reiman, Eric M

2010-01-01

Graphical analysis methods are widely used in positron emission tomography quantification because of their simplicity and model independence. But they may, particularly for reversible kinetics, lead to bias in the estimated parameters. The source of the bias is commonly attributed to noise in the data. Assuming a two-tissue compartmental model, we investigate the bias that originates from modeling error. This bias is an intrinsic property of the simplified linear models used for limited scan durations, and it is exaggerated by random noise and numerical quadrature error. Conditions are derived under which Logan's graphical method either over- or under-estimates the distribution volume in the noise-free case. The bias caused by modeling error is quantified analytically. The presented analysis shows that the bias of graphical methods is inversely proportional to the dissociation rate. Furthermore, visual examination of the linearity of the Logan plot is not sufficient for guaranteeing that equilibrium has been reached. A new model which retains the elegant properties of graphical analysis methods is presented, along with a numerical algorithm for its solution. We perform simulations with the fibrillar amyloid β radioligand [11C] benzothiazole-aniline using published data from the University of Pittsburgh and Rotterdam groups. The results show that the proposed method significantly reduces the bias due to modeling error. Moreover, the results for data acquired over a 70 minutes scan duration are at least as good as those obtained using existing methods for data acquired over a 90 minutes scan duration. PMID:20493196

Optical Logarithmic Transformation of Speckle Images with Bacteriorhodopsin Films

NASA Technical Reports Server (NTRS)

Downie, John D.

1995-01-01

The application of logarithmic transformations to speckle images is sometimes desirable in converting the speckle noise distribution into an additive, constant-variance noise distribution. The optical transmission properties of some bacteriorhodopsin films are well suited to implement such a transformation optically in a parallel fashion. I present experimental results of the optical conversion of a speckle image into a transformed image with signal-independent noise statistics, using the real-time photochromic properties of bacteriorhodopsin. The original and transformed noise statistics are confirmed by histogram analysis.

Noise parameter estimation for poisson corrupted images using variance stabilization transforms.

PubMed

Jin, Xiaodan; Xu, Zhenyu; Hirakawa, Keigo

2014-03-01

Noise is present in all images captured by real-world image sensors. Poisson distribution is said to model the stochastic nature of the photon arrival process and agrees with the distribution of measured pixel values. We propose a method for estimating unknown noise parameters from Poisson corrupted images using properties of variance stabilization. With a significantly lower computational complexity and improved stability, the proposed estimation technique yields noise parameters that are comparable in accuracy to the state-of-art methods.

Performance Improvement of Raman Distributed Temperature System by Using Noise Suppression

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

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

NASA Astrophysics Data System (ADS)

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.

Comprehensive analysis of low-frequency noise variability components in bulk and fully depleted silicon-on-insulator metal–oxide–semiconductor field-effect transistor

NASA Astrophysics Data System (ADS)

Maekawa, Keiichi; Makiyama, Hideki; Yamamoto, Yoshiki; Hasegawa, Takumi; Okanishi, Shinobu; Sonoda, Kenichiro; Shinkawata, Hiroki; Yamashita, Tomohiro; Kamohara, Shiro; Yamaguchi, Yasuo

2018-04-01

The low-frequency noise (LFN) variability in bulk and fully depleted silicon-on-insulator (FDSOI) metal–oxide–semiconductor field-effect transistor (MOSFET) with silicon on thin box (SOTB) technology was investigated. LFN typically shows a flicker noise component and a signal Lorentzian component by random telegraph noise (RTN). At a weak inversion state, the random dopant fluctuation (RDF) in a channel is strongly affected to not only RTN variability but also flicker noise variability in the bulk MOSFET compared with SOTB MOSFET because of local carrier number fluctuation in the channel. On the other hand, the typical level of LFN in SOTB MOSFET is slightly larger than that in the bulk MOSFET because of an additional interface on the buried oxide layer. However, considering the tailing characteristics of LFN variability, LFN in SOTB MOSFET can be assumed to be smaller than that in the bulk MOSFET, which enables the low-voltage operation of analog circuits.

Synaptic shot noise and conductance fluctuations affect the membrane voltage with equal significance.

PubMed

Richardson, Magnus J E; Gerstner, Wulfram

2005-04-01

The subthreshold membrane voltage of a neuron in active cortical tissue is a fluctuating quantity with a distribution that reflects the firing statistics of the presynaptic population. It was recently found that conductance-based synaptic drive can lead to distributions with a significant skew. Here it is demonstrated that the underlying shot noise caused by Poissonian spike arrival also skews the membrane distribution, but in the opposite sense. Using a perturbative method, we analyze the effects of shot noise on the distribution of synaptic conductances and calculate the consequent voltage distribution. To first order in the perturbation theory, the voltage distribution is a gaussian modulated by a prefactor that captures the skew. The gaussian component is identical to distributions derived using current-based models with an effective membrane time constant. The well-known effective-time-constant approximation can therefore be identified as the leading-order solution to the full conductance-based model. The higher-order modulatory prefactor containing the skew comprises terms due to both shot noise and conductance fluctuations. The diffusion approximation misses these shot-noise effects implying that analytical approaches such as the Fokker-Planck equation or simulation with filtered white noise cannot be used to improve on the gaussian approximation. It is further demonstrated that quantities used for fitting theory to experiment, such as the voltage mean and variance, are robust against these non-Gaussian effects. The effective-time-constant approximation is therefore relevant to experiment and provides a simple analytic base on which other pertinent biological details may be added.

[Evoked Potential Blind Extraction Based on Fractional Lower Order Spatial Time-Frequency Matrix].

PubMed

Long, Junbo; Wang, Haibin; Zha, Daifeng

2015-04-01

The impulsive electroencephalograph (EEG) noises in evoked potential (EP) signals is very strong, usually with a heavy tail and infinite variance characteristics like the acceleration noise impact, hypoxia and etc., as shown in other special tests. The noises can be described by a stable distribution model. In this paper, Wigner-Ville distribution (WVD) and pseudo Wigner-Ville distribution (PWVD) time-frequency distribution based on the fractional lower order moment are presented to be improved. We got fractional lower order WVD (FLO-WVD) and fractional lower order PWVD (FLO-PWVD) time-frequency distribution which could be suitable for a stable distribution process. We also proposed the fractional lower order spatial time-frequency distribution matrix (FLO-STFM) concept. Therefore, combining with time-frequency underdetermined blind source separation (TF-UBSS), we proposed a new fractional lower order spatial time-frequency underdetermined blind source separation (FLO-TF-UBSS) which can work in a stable distribution environment. We used the FLO-TF-UBSS algorithm to extract EPs. Simulations showed that the proposed method could effectively extract EPs in EEG noises, and the separated EPs and EEG signals based on FLO-TF-UBSS were almost the same as the original signal, but blind separation based on TF-UBSS had certain deviation. The correlation coefficient of the FLO-TF-UBSS algorithm was higher than the TF-UBSS algorithm when generalized signal-to-noise ratio (GSNR) changed from 10 dB to 30 dB and a varied from 1. 06 to 1. 94, and was approximately e- qual to 1. Hence, the proposed FLO-TF-UBSS method might be better than the TF-UBSS algorithm based on second order for extracting EP signal under an EEG noise environment.

Socio-psychological airplane noise investigation in the districts of three Swiss airports: Zurich, Geneva and Basel

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graf, R.; Mueller, R.; Meier, H.P.

1980-09-01

The results of noise measurements and calculations are available in the form of noise maps for each of the three areas. To measure the stress due to airplane noise the Noise and Number Index (NNI) was applied. In the vicinities of the airports, 400 households were randomly selected in each of the three noise zones (of 10 NNI intervals each). A total of 3939 questionnaires could be evaluated, one quarter of which came from areas without airplane noise. Concurrently, traffic noise was measured in areas of Basel and expressed in sum total levels L sub 50 and the reaction ofmore » 944 persons was elicited by interrogation.« less

Socio-psychological airplane noise investigation in the districts of three Swiss airports: Zurich, Geneva and Basel

NASA Technical Reports Server (NTRS)

Graf, R.; Mueller, R.; Meier, H. P.

1980-01-01

The results of noise measurements and calculations are available in the form of noise maps for each of the three areas. To measure the stress due to airplane noise the Noise and Number Index (NNI) was applied. In the vicinities of the airports, 400 households were randomly selected in each of the three noise zones (of 10 NNI intervals each). A total of 3939 questionnaires could be evaluated, one quarter of which came from areas without airplane noise. Concurrently, traffic noise was measured in areas of Basel and expressed in sum total levels L sub 50 and the reaction of 944 persons was elicited by interrogation.

Infrared image enhancement based on the edge detection and mathematical morphology

NASA Astrophysics Data System (ADS)

Zhang, Linlin; Zhao, Yuejin; Dong, Liquan; Liu, Xiaohua; Yu, Xiaomei; Hui, Mei; Chu, Xuhong; Gong, Cheng

2010-11-01

The development of the un-cooled infrared imaging technology from military necessity. At present, It is widely applied in industrial, medicine, scientific and technological research and so on. The infrared radiation temperature distribution of the measured object's surface can be observed visually. The collection of infrared images from our laboratory has following characteristics: Strong spatial correlation, Low contrast , Poor visual effect; Without color or shadows because of gray image , and has low resolution; Low definition compare to the visible light image; Many kinds of noise are brought by the random disturbances of the external environment. Digital image processing are widely applied in many areas, it can now be studied up close and in detail in many research field. It has become one kind of important means of the human visual continuation. Traditional methods for image enhancement cannot capture the geometric information of images and tend to amplify noise. In order to remove noise and improve visual effect. Meanwhile, To overcome the above enhancement issues. The mathematical model of FPA unit was constructed based on matrix transformation theory. According to characteristics of FPA, Image enhancement algorithm which combined with mathematical morphology and edge detection are established. First of all, Image profile is obtained by using the edge detection combine with mathematical morphological operators. And then, through filling the template profile by original image to get the ideal background image, The image noise can be removed on the base of the above method. The experiments show that utilizing the proposed algorithm can enhance image detail and the signal to noise ratio.

Optimal post-experiment estimation of poorly modeled dynamic systems

NASA Technical Reports Server (NTRS)

Mook, D. Joseph

1988-01-01

Recently, a novel strategy for post-experiment state estimation of discretely-measured dynamic systems has been developed. The method accounts for errors in the system dynamic model equations in a more general and rigorous manner than do filter-smoother algorithms. The dynamic model error terms do not require the usual process noise assumptions of zero-mean, symmetrically distributed random disturbances. Instead, the model error terms require no prior assumptions other than piecewise continuity. The resulting state estimates are more accurate than filters for applications in which the dynamic model error clearly violates the typical process noise assumptions, and the available measurements are sparse and/or noisy. Estimates of the dynamic model error, in addition to the states, are obtained as part of the solution of a two-point boundary value problem, and may be exploited for numerous reasons. In this paper, the basic technique is explained, and several example applications are given. Included among the examples are both state estimation and exploitation of the model error estimates.

Filtering and left ventricle segmentation of the fetal heart in ultrasound images

NASA Astrophysics Data System (ADS)

Vargas-Quintero, Lorena; Escalante-Ramírez, Boris

2013-11-01

In this paper, we propose to use filtering methods and a segmentation algorithm for the analysis of fetal heart in ultrasound images. Since noise speckle makes difficult the analysis of ultrasound images, the filtering process becomes a useful task in these types of applications. The filtering techniques consider in this work assume that the speckle noise is a random variable with a Rayleigh distribution. We use two multiresolution methods: one based on wavelet decomposition and the another based on the Hermite transform. The filtering process is used as way to strengthen the performance of the segmentation tasks. For the wavelet-based approach, a Bayesian estimator at subband level for pixel classification is employed. The Hermite method computes a mask to find those pixels that are corrupted by speckle. On the other hand, we picked out a method based on a deformable model or "snake" to evaluate the influence of the filtering techniques in the segmentation task of left ventricle in fetal echocardiographic images.

Investigation of Allan variance for determining noise spectral forms with application to microwave radiometry

NASA Technical Reports Server (NTRS)

Stanley, William D.

1994-01-01

An investigation of the Allan variance method as a possible means for characterizing fluctuations in radiometric noise diodes has been performed. The goal is to separate fluctuation components into white noise, flicker noise, and random-walk noise. The primary means is by discrete-time processing, and the study focused primarily on the digital processes involved. Noise satisfying the requirements was generated by direct convolution, fast Fourier transformation (FFT) processing in the time domain, and FFT processing in the frequency domain. Some of the numerous results obtained are presented along with the programs used in the study.

Linear Space-Variant Image Restoration of Photon-Limited Images

DTIC Science & Technology

1978-03-01

levels of performance of the wavefront seisor. The parameter ^ represents the residual rms wavefront error ^measurement noise plus ♦ttting error...known to be optimum only when the signal and noise are uncorrelated stationary random processes «nd when the noise statistics are gaussian. In the...regime of photon-Iimited imaging, the noise is non-gaussian and signaI-dependent, and it is therefore reasonable to assume that tome form of linear

Global synchronization of memristive neural networks subject to random disturbances via distributed pinning control.

PubMed

Guo, Zhenyuan; Yang, Shaofu; Wang, Jun

2016-12-01

This paper presents theoretical results on global exponential synchronization of multiple memristive neural networks in the presence of external noise by means of two types of distributed pinning control. The multiple memristive neural networks are coupled in a general structure via a nonlinear function, which consists of a linear diffusive term and a discontinuous sign term. A pinning impulsive control law is introduced in the coupled system to synchronize all neural networks. Sufficient conditions are derived for ascertaining global exponential synchronization in mean square. In addition, a pinning adaptive control law is developed to achieve global exponential synchronization in mean square. Both pinning control laws utilize only partial state information received from the neighborhood of the controlled neural network. Simulation results are presented to substantiate the theoretical results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Practical security analysis of continuous-variable quantum key distribution with jitter in clock synchronization

NASA Astrophysics Data System (ADS)

Xie, Cailang; Guo, Ying; Liao, Qin; Zhao, Wei; Huang, Duan; Zhang, Ling; Zeng, Guihua

2018-03-01

How to narrow the gap of security between theory and practice has been a notoriously urgent problem in quantum cryptography. Here, we analyze and provide experimental evidence of the clock jitter effect on the practical continuous-variable quantum key distribution (CV-QKD) system. The clock jitter is a random noise which exists permanently in the clock synchronization in the practical CV-QKD system, it may compromise the system security because of its impact on data sampling and parameters estimation. In particular, the practical security of CV-QKD with different clock jitter against collective attack is analyzed theoretically based on different repetition frequencies, the numerical simulations indicate that the clock jitter has more impact on a high-speed scenario. Furthermore, a simplified experiment is designed to investigate the influence of the clock jitter.

Robustness of quantum key distribution with discrete and continuous variables to channel noise

NASA Astrophysics Data System (ADS)

Lasota, Mikołaj; Filip, Radim; Usenko, Vladyslav C.

2017-06-01

We study the robustness of quantum key distribution protocols using discrete or continuous variables to the channel noise. We introduce the model of such noise based on coupling of the signal to a thermal reservoir, typical for continuous-variable quantum key distribution, to the discrete-variable case. Then we perform a comparison of the bounds on the tolerable channel noise between these two kinds of protocols using the same noise parametrization, in the case of implementation which is perfect otherwise. Obtained results show that continuous-variable protocols can exhibit similar robustness to the channel noise when the transmittance of the channel is relatively high. However, for strong loss discrete-variable protocols are superior and can overcome even the infinite-squeezing continuous-variable protocol while using limited nonclassical resources. The requirement on the probability of a single-photon production which would have to be fulfilled by a practical source of photons in order to demonstrate such superiority is feasible thanks to the recent rapid development in this field.

Self-organization of complex networks as a dynamical system

NASA Astrophysics Data System (ADS)

Aoki, Takaaki; Yawata, Koichiro; Aoyagi, Toshio

2015-01-01

To understand the dynamics of real-world networks, we investigate a mathematical model of the interplay between the dynamics of random walkers on a weighted network and the link weights driven by a resource carried by the walkers. Our numerical studies reveal that, under suitable conditions, the co-evolving dynamics lead to the emergence of stationary power-law distributions of the resource and link weights, while the resource quantity at each node ceaselessly changes with time. We analyze the network organization as a deterministic dynamical system and find that the system exhibits multistability, with numerous fixed points, limit cycles, and chaotic states. The chaotic behavior of the system leads to the continual changes in the microscopic network dynamics in the absence of any external random noises. We conclude that the intrinsic interplay between the states of the nodes and network reformation constitutes a major factor in the vicissitudes of real-world networks.

A Cerebellar-model Associative Memory as a Generalized Random-access Memory

NASA Technical Reports Server (NTRS)

Kanerva, Pentti

1989-01-01

A versatile neural-net model is explained in terms familiar to computer scientists and engineers. It is called the sparse distributed memory, and it is a random-access memory for very long words (for patterns with thousands of bits). Its potential utility is the result of several factors: (1) a large pattern representing an object or a scene or a moment can encode a large amount of information about what it represents; (2) this information can serve as an address to the memory, and it can also serve as data; (3) the memory is noise tolerant--the information need not be exact; (4) the memory can be made arbitrarily large and hence an arbitrary amount of information can be stored in it; and (5) the architecture is inherently parallel, allowing large memories to be fast. Such memories can become important components of future computers.

Self-organization of complex networks as a dynamical system.

PubMed

Aoki, Takaaki; Yawata, Koichiro; Aoyagi, Toshio

2015-01-01

To understand the dynamics of real-world networks, we investigate a mathematical model of the interplay between the dynamics of random walkers on a weighted network and the link weights driven by a resource carried by the walkers. Our numerical studies reveal that, under suitable conditions, the co-evolving dynamics lead to the emergence of stationary power-law distributions of the resource and link weights, while the resource quantity at each node ceaselessly changes with time. We analyze the network organization as a deterministic dynamical system and find that the system exhibits multistability, with numerous fixed points, limit cycles, and chaotic states. The chaotic behavior of the system leads to the continual changes in the microscopic network dynamics in the absence of any external random noises. We conclude that the intrinsic interplay between the states of the nodes and network reformation constitutes a major factor in the vicissitudes of real-world networks.

Random noise effects in pulse-mode digital multilayer neural networks.

PubMed

Kim, Y C; Shanblatt, M A

1995-01-01

A pulse-mode digital multilayer neural network (DMNN) based on stochastic computing techniques is implemented with simple logic gates as basic computing elements. The pulse-mode signal representation and the use of simple logic gates for neural operations lead to a massively parallel yet compact and flexible network architecture, well suited for VLSI implementation. Algebraic neural operations are replaced by stochastic processes using pseudorandom pulse sequences. The distributions of the results from the stochastic processes are approximated using the hypergeometric distribution. Synaptic weights and neuron states are represented as probabilities and estimated as average pulse occurrence rates in corresponding pulse sequences. A statistical model of the noise (error) is developed to estimate the relative accuracy associated with stochastic computing in terms of mean and variance. Computational differences are then explained by comparison to deterministic neural computations. DMNN feedforward architectures are modeled in VHDL using character recognition problems as testbeds. Computational accuracy is analyzed, and the results of the statistical model are compared with the actual simulation results. Experiments show that the calculations performed in the DMNN are more accurate than those anticipated when Bernoulli sequences are assumed, as is common in the literature. Furthermore, the statistical model successfully predicts the accuracy of the operations performed in the DMNN.

Bayesian multiple-source localization in an uncertain ocean environment.

PubMed

Dosso, Stan E; Wilmut, Michael J

2011-06-01

This paper considers simultaneous localization of multiple acoustic sources when properties of the ocean environment (water column and seabed) are poorly known. A Bayesian formulation is developed in which the environmental parameters, noise statistics, and locations and complex strengths (amplitudes and phases) of multiple sources are considered to be unknown random variables constrained by acoustic data and prior information. Two approaches are considered for estimating source parameters. Focalization maximizes the posterior probability density (PPD) over all parameters using adaptive hybrid optimization. Marginalization integrates the PPD using efficient Markov-chain Monte Carlo methods to produce joint marginal probability distributions for source ranges and depths, from which source locations are obtained. This approach also provides quantitative uncertainty analysis for all parameters, which can aid in understanding of the inverse problem and may be of practical interest (e.g., source-strength probability distributions). In both approaches, closed-form maximum-likelihood expressions for source strengths and noise variance at each frequency allow these parameters to be sampled implicitly, substantially reducing the dimensionality and difficulty of the inversion. Examples are presented of both approaches applied to single- and multi-frequency localization of multiple sources in an uncertain shallow-water environment, and a Monte Carlo performance evaluation study is carried out. © 2011 Acoustical Society of America

Development of Auditory Selective Attention: Why Children Struggle to Hear in Noisy Environments

ERIC Educational Resources Information Center

Jones, Pete R.; Moore, David R.; Amitay, Sygal

2015-01-01

Children's hearing deteriorates markedly in the presence of unpredictable noise. To explore why, 187 school-age children (4-11 years) and 15 adults performed a tone-in-noise detection task, in which the masking noise varied randomly between every presentation. Selective attention was evaluated by measuring the degree to which listeners were…

Evaluation of domain randomness in periodically poled lithium niobate by diffraction noise measurement.

PubMed

Dwivedi, Prashant Povel; Choi, Hee Joo; Kim, Byoung Joo; Cha, Myoungsik

2013-12-16

Random duty-cycle errors (RDE) in ferroelectric quasi-phase-matching (QPM) devices not only affect the frequency conversion efficiency, but also generate non-phase-matched parasitic noise that can be detrimental to some applications. We demonstrate an accurate but simple method for measuring the RDE in periodically poled lithium niobate. Due to the equivalence between the undepleted harmonic generation spectrum and the diffraction pattern from the QPM grating, we employed linear diffraction measurement which is much simpler than tunable harmonic generation experiments [J. S. Pelc, et al., Opt. Lett.36, 864-866 (2011)]. As a result, we could relate the RDE for the QPM device to the relative noise intensity between the diffraction orders.

Experimental demonstration of robust entanglement distribution over reciprocal noisy channels assisted by a counter-propagating classical reference light.

PubMed

Ikuta, Rikizo; Nozaki, Shota; Yamamoto, Takashi; Koashi, Masato; Imoto, Nobuyuki

2017-07-06

Embedding a quantum state in a decoherence-free subspace (DFS) formed by multiple photons is one of the promising methods for robust entanglement distribution of photonic states over collective noisy channels. In practice, however, such a scheme suffers from a low efficiency proportional to transmittance of the channel to the power of the number of photons forming the DFS. The use of a counter-propagating coherent pulse can improve the efficiency to scale linearly in the channel transmission, but it achieves only protection against phase noises. Recently, it was theoretically proposed [Phys. Rev. A 87, 052325(2013)] that the protection against bit-flip noises can also be achieved if the channel has a reciprocal property. Here we experimentally demonstrate the proposed scheme to distribute polarization-entangled photon pairs against a general collective noise including the bit flip noise and the phase noise. We observed an efficient sharing rate scaling while keeping a high quality of the distributed entangled state. Furthermore, we show that the method is applicable not only to the entanglement distribution but also to the transmission of arbitrary polarization states of a single photon.

Compact quantum random number generator based on superluminescent light-emitting diodes

NASA Astrophysics Data System (ADS)

Wei, Shihai; Yang, Jie; Fan, Fan; Huang, Wei; Li, Dashuang; Xu, Bingjie

2017-12-01

By measuring the amplified spontaneous emission (ASE) noise of the superluminescent light emitting diodes, we propose and realize a quantum random number generator (QRNG) featured with practicability. In the QRNG, after the detection and amplification of the ASE noise, the data acquisition and randomness extraction which is integrated in a field programmable gate array (FPGA) are both implemented in real-time, and the final random bit sequences are delivered to a host computer with a real-time generation rate of 1.2 Gbps. Further, to achieve compactness, all the components of the QRNG are integrated on three independent printed circuit boards with a compact design, and the QRNG is packed in a small enclosure sized 140 mm × 120 mm × 25 mm. The final random bit sequences can pass all the NIST-STS and DIEHARD tests.

Dissociating error-based and reinforcement-based loss functions during sensorimotor learning

PubMed Central

McGregor, Heather R.; Mohatarem, Ayman

2017-01-01

It has been proposed that the sensorimotor system uses a loss (cost) function to evaluate potential movements in the presence of random noise. Here we test this idea in the context of both error-based and reinforcement-based learning. In a reaching task, we laterally shifted a cursor relative to true hand position using a skewed probability distribution. This skewed probability distribution had its mean and mode separated, allowing us to dissociate the optimal predictions of an error-based loss function (corresponding to the mean of the lateral shifts) and a reinforcement-based loss function (corresponding to the mode). We then examined how the sensorimotor system uses error feedback and reinforcement feedback, in isolation and combination, when deciding where to aim the hand during a reach. We found that participants compensated differently to the same skewed lateral shift distribution depending on the form of feedback they received. When provided with error feedback, participants compensated based on the mean of the skewed noise. When provided with reinforcement feedback, participants compensated based on the mode. Participants receiving both error and reinforcement feedback continued to compensate based on the mean while repeatedly missing the target, despite receiving auditory, visual and monetary reinforcement feedback that rewarded hitting the target. Our work shows that reinforcement-based and error-based learning are separable and can occur independently. Further, when error and reinforcement feedback are in conflict, the sensorimotor system heavily weights error feedback over reinforcement feedback. PMID:28753634

Dissociating error-based and reinforcement-based loss functions during sensorimotor learning.

PubMed

Cashaback, Joshua G A; McGregor, Heather R; Mohatarem, Ayman; Gribble, Paul L

2017-07-01

It has been proposed that the sensorimotor system uses a loss (cost) function to evaluate potential movements in the presence of random noise. Here we test this idea in the context of both error-based and reinforcement-based learning. In a reaching task, we laterally shifted a cursor relative to true hand position using a skewed probability distribution. This skewed probability distribution had its mean and mode separated, allowing us to dissociate the optimal predictions of an error-based loss function (corresponding to the mean of the lateral shifts) and a reinforcement-based loss function (corresponding to the mode). We then examined how the sensorimotor system uses error feedback and reinforcement feedback, in isolation and combination, when deciding where to aim the hand during a reach. We found that participants compensated differently to the same skewed lateral shift distribution depending on the form of feedback they received. When provided with error feedback, participants compensated based on the mean of the skewed noise. When provided with reinforcement feedback, participants compensated based on the mode. Participants receiving both error and reinforcement feedback continued to compensate based on the mean while repeatedly missing the target, despite receiving auditory, visual and monetary reinforcement feedback that rewarded hitting the target. Our work shows that reinforcement-based and error-based learning are separable and can occur independently. Further, when error and reinforcement feedback are in conflict, the sensorimotor system heavily weights error feedback over reinforcement feedback.

In vivo evaluation of the effect of stimulus distribution on FIR statistical efficiency in event-related fMRI

PubMed Central

Jansma, J Martijn; de Zwart, Jacco A; van Gelderen, Peter; Duyn, Jeff H; Drevets, Wayne C; Furey, Maura L

2013-01-01

Technical developments in MRI have improved signal to noise, allowing use of analysis methods such as Finite impulse response (FIR) of rapid event related functional MRI (er-fMRI). FIR is one of the most informative analysis methods as it determines onset and full shape of the hemodynamic response function (HRF) without any a-priori assumptions. FIR is however vulnerable to multicollinearity, which is directly related to the distribution of stimuli over time. Efficiency can be optimized by simplifying a design, and restricting stimuli distribution to specific sequences, while more design flexibility necessarily reduces efficiency. However, the actual effect of efficiency on fMRI results has never been tested in vivo. Thus, it is currently difficult to make an informed choice between protocol flexibility and statistical efficiency. The main goal of this study was to assign concrete fMRI signal to noise values to the abstract scale of FIR statistical efficiency. Ten subjects repeated a perception task with five random and m-sequence based protocol, with varying but, according to literature, acceptable levels of multicollinearity. Results indicated substantial differences in signal standard deviation, while the level was a function of multicollinearity. Experiment protocols varied up to 55.4% in standard deviation. Results confirm that quality of fMRI in an FIR analysis can significantly and substantially vary with statistical efficiency. Our in vivo measurements can be used to aid in making an informed decision between freedom in protocol design and statistical efficiency. PMID:23473798

Raman dissipative soliton fiber laser pumped by an ASE source.

PubMed

Pan, Weiwei; Zhang, Lei; Zhou, Jiaqi; Yang, Xuezong; Feng, Yan

2017-12-15

The mode locking of a Raman fiber laser with an amplified spontaneous emission (ASE) pump source is investigated for performance improvement. Raman dissipative solitons with a compressed pulse duration of 1.05 ps at a repetition rate of 2.47 MHz are generated by utilizing nonlinear polarization rotation and all-fiber Lyot filter. A signal-to-noise ratio as high as 85 dB is measured in a radio-frequency spectrum, which suggests excellent temporal stability. Multiple-pulse operation with unique random static distribution is observed for the first time, to the best of our knowledge, at higher pump power in mode-locked Raman fiber lasers.

Mean First Passage Time and Stochastic Resonance in a Transcriptional Regulatory System with Non-Gaussian Noise

NASA Astrophysics Data System (ADS)

Kang, Yan-Mei; Chen, Xi; Lin, Xu-Dong; Tan, Ning

The mean first passage time (MFPT) in a phenomenological gene transcriptional regulatory model with non-Gaussian noise is analytically investigated based on the singular perturbation technique. The effect of the non-Gaussian noise on the phenomenon of stochastic resonance (SR) is then disclosed based on a new combination of adiabatic elimination and linear response approximation. Compared with the results in the Gaussian noise case, it is found that bounded non-Gaussian noise inhibits the transition between different concentrations of protein, while heavy-tailed non-Gaussian noise accelerates the transition. It is also found that the optimal noise intensity for SR in the heavy-tailed noise case is smaller, while the optimal noise intensity in the bounded noise case is larger. These observations can be explained by the heavy-tailed noise easing random transitions.

Effect of noise in principal component analysis with an application to ozone pollution

NASA Astrophysics Data System (ADS)

Tsakiri, Katerina G.

This thesis analyzes the effect of independent noise in principal components of k normally distributed random variables defined by a covariance matrix. We prove that the principal components as well as the canonical variate pairs determined from joint distribution of original sample affected by noise can be essentially different in comparison with those determined from the original sample. However when the differences between the eigenvalues of the original covariance matrix are sufficiently large compared to the level of the noise, the effect of noise in principal components and canonical variate pairs proved to be negligible. The theoretical results are supported by simulation study and examples. Moreover, we compare our results about the eigenvalues and eigenvectors in the two dimensional case with other models examined before. This theory can be applied in any field for the decomposition of the components in multivariate analysis. One application is the detection and prediction of the main atmospheric factor of ozone concentrations on the example of Albany, New York. Using daily ozone, solar radiation, temperature, wind speed and precipitation data, we determine the main atmospheric factor for the explanation and prediction of ozone concentrations. A methodology is described for the decomposition of the time series of ozone and other atmospheric variables into the global term component which describes the long term trend and the seasonal variations, and the synoptic scale component which describes the short term variations. By using the Canonical Correlation Analysis, we show that solar radiation is the only main factor between the atmospheric variables considered here for the explanation and prediction of the global and synoptic scale component of ozone. The global term components are modeled by a linear regression model, while the synoptic scale components by a vector autoregressive model and the Kalman filter. The coefficient of determination, R2, for the prediction of the synoptic scale ozone component was found to be the highest when we consider the synoptic scale component of the time series for solar radiation and temperature. KEY WORDS: multivariate analysis; principal component; canonical variate pairs; eigenvalue; eigenvector; ozone; solar radiation; spectral decomposition; Kalman filter; time series prediction

Robust reliable sampled-data control for switched systems with application to flight control

NASA Astrophysics Data System (ADS)

Sakthivel, R.; Joby, Maya; Shi, P.; Mathiyalagan, K.

2016-11-01

This paper addresses the robust reliable stabilisation problem for a class of uncertain switched systems with random delays and norm bounded uncertainties. The main aim of this paper is to obtain the reliable robust sampled-data control design which involves random time delay with an appropriate gain control matrix for achieving the robust exponential stabilisation for uncertain switched system against actuator failures. In particular, the involved delays are assumed to be randomly time-varying which obeys certain mutually uncorrelated Bernoulli distributed white noise sequences. By constructing an appropriate Lyapunov-Krasovskii functional (LKF) and employing an average-dwell time approach, a new set of criteria is derived for ensuring the robust exponential stability of the closed-loop switched system. More precisely, the Schur complement and Jensen's integral inequality are used in derivation of stabilisation criteria. By considering the relationship among the random time-varying delay and its lower and upper bounds, a new set of sufficient condition is established for the existence of reliable robust sampled-data control in terms of solution to linear matrix inequalities (LMIs). Finally, an illustrative example based on the F-18 aircraft model is provided to show the effectiveness of the proposed design procedures.

Lotka-Volterra system in a random environment.

PubMed

Dimentberg, Mikhail F

2002-03-01

Classical Lotka-Volterra (LV) model for oscillatory behavior of population sizes of two interacting species (predator-prey or parasite-host pairs) is conservative. This may imply unrealistically high sensitivity of the system's behavior to environmental variations. Thus, a generalized LV model is considered with the equation for preys' reproduction containing the following additional terms: quadratic "damping" term that accounts for interspecies competition, and term with white-noise random variations of the preys' reproduction factor that simulates the environmental variations. An exact solution is obtained for the corresponding Fokker-Planck-Kolmogorov equation for stationary probability densities (PDF's) of the population sizes. It shows that both population sizes are independent gamma-distributed stationary random processes. Increasing level of the environmental variations does not lead to extinction of the populations. However it may lead to an intermittent behavior, whereby one or both population sizes experience very rare and violent short pulses or outbreaks while remaining on a very low level most of the time. This intermittency is described analytically by direct use of the solutions for the PDF's as well as by applying theory of excursions of random functions and by predicting PDF of peaks in the predators' population size.

Lotka-Volterra system in a random environment

NASA Astrophysics Data System (ADS)

Dimentberg, Mikhail F.

2002-03-01

Classical Lotka-Volterra (LV) model for oscillatory behavior of population sizes of two interacting species (predator-prey or parasite-host pairs) is conservative. This may imply unrealistically high sensitivity of the system's behavior to environmental variations. Thus, a generalized LV model is considered with the equation for preys' reproduction containing the following additional terms: quadratic ``damping'' term that accounts for interspecies competition, and term with white-noise random variations of the preys' reproduction factor that simulates the environmental variations. An exact solution is obtained for the corresponding Fokker-Planck-Kolmogorov equation for stationary probability densities (PDF's) of the population sizes. It shows that both population sizes are independent γ-distributed stationary random processes. Increasing level of the environmental variations does not lead to extinction of the populations. However it may lead to an intermittent behavior, whereby one or both population sizes experience very rare and violent short pulses or outbreaks while remaining on a very low level most of the time. This intermittency is described analytically by direct use of the solutions for the PDF's as well as by applying theory of excursions of random functions and by predicting PDF of peaks in the predators' population size.

Marine Mammals and Noise-Progress Since 1995

DTIC Science & Technology

2015-09-30

1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Marine Mammals & Noise - Progress Since 1995 Christine...Erbe Centre for Marine Science & Technology Curtin University GPO Box U1987 Perth, WA 6845, Australia phone: +61-8-9266 7380 email: c.erbe...effects of underwater noise on marine mammals has grown steadily over the last few decades. Results and information are scattered across the peer

The effect of noise-induced variance on parameter recovery from reaction times.

PubMed

Vadillo, Miguel A; Garaizar, Pablo

2016-03-31

Technical noise can compromise the precision and accuracy of the reaction times collected in psychological experiments, especially in the case of Internet-based studies. Although this noise seems to have only a small impact on traditional statistical analyses, its effects on model fit to reaction-time distributions remains unexplored. Across four simulations we study the impact of technical noise on parameter recovery from data generated from an ex-Gaussian distribution and from a Ratcliff Diffusion Model. Our results suggest that the impact of noise-induced variance tends to be limited to specific parameters and conditions. Although we encourage researchers to adopt all measures to reduce the impact of noise on reaction-time experiments, we conclude that the typical amount of noise-induced variance found in these experiments does not pose substantial problems for statistical analyses based on model fitting.

Environmental Noise Could Promote Stochastic Local Stability of Behavioral Diversity Evolution

NASA Astrophysics Data System (ADS)

Zheng, Xiu-Deng; Li, Cong; Lessard, Sabin; Tao, Yi

2018-05-01

In this Letter, we investigate stochastic stability in a two-phenotype evolutionary game model for an infinite, well-mixed population undergoing discrete, nonoverlapping generations. We assume that the fitness of a phenotype is an exponential function of its expected payoff following random pairwise interactions whose outcomes randomly fluctuate with time. We show that the stochastic local stability of a constant interior equilibrium can be promoted by the random environmental noise even if the system may display a complicated nonlinear dynamics. This result provides a new perspective for a better understanding of how environmental fluctuations may contribute to the evolution of behavioral diversity.

Stochastic epidemic outbreaks: why epidemics are like lasers

NASA Astrophysics Data System (ADS)

Schwartz, Ira B.; Billings, Lora

2004-05-01

Many diseases, such as childhood diseases, dengue fever, and West Nile virus, appear to oscillate randomly as a function of seasonal environmental or social changes. Such oscillations appear to have a chaotic bursting character, although it is still uncertain how much is due to random fluctuations. Such bursting in the presence of noise is also observed in driven lasers. In this talk, I will show how noise can excite random outbreaks in simple models of seasonally driven outbreaks, as well as lasers. The models for both population dynamics will be shown to share the same class of underlying topology, which plays a major role in the cause of observed stochastic bursting.

Approximating SIR-B response characteristics and estimating wave height and wavelength for ocean imagery

NASA Technical Reports Server (NTRS)

Tilley, David G.

1987-01-01

NASA Space Shuttle Challenger SIR-B ocean scenes are used to derive directional wave spectra for which speckle noise is modeled as a function of Rayleigh random phase coherence downrange and Poisson random amplitude errors inherent in the Doppler measurement of along-track position. A Fourier filter that preserves SIR-B image phase relations is used to correct the stationary and dynamic response characteristics of the remote sensor and scene correlator, as well as to subtract an estimate of the speckle noise component. A two-dimensional map of sea surface elevation is obtained after the filtered image is corrected for both random and deterministic motions.

Method of confidence domains in the analysis of noise-induced extinction for tritrophic population system

NASA Astrophysics Data System (ADS)

Bashkirtseva, Irina; Ryashko, Lev; Ryazanova, Tatyana

2017-09-01

A problem of the analysis of the noise-induced extinction in multidimensional population systems is considered. For the investigation of conditions of the extinction caused by random disturbances, a new approach based on the stochastic sensitivity function technique and confidence domains is suggested, and applied to tritrophic population model of interacting prey, predator and top predator. This approach allows us to analyze constructively the probabilistic mechanisms of the transition to the noise-induced extinction from both equilibrium and oscillatory regimes of coexistence. In this analysis, a method of principal directions for the reducing of the dimension of confidence domains is suggested. In the dispersion of random states, the principal subspace is defined by the ratio of eigenvalues of the stochastic sensitivity matrix. A detailed analysis of two scenarios of the noise-induced extinction in dependence on parameters of considered tritrophic system is carried out.

Reversal time of jump-noise magnetization dynamics in nanomagnets via Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Parthasarathy, Arun; Rakheja, Shaloo

2018-06-01

The jump-noise is a nonhomogeneous Poisson process which models thermal effects in magnetization dynamics, with special applications in low temperature escape rate phenomena. In this work, we develop improved numerical methods for Monte Carlo simulation of the jump-noise dynamics and validate the method by comparing the stationary distribution obtained empirically against the Boltzmann distribution. In accordance with the Néel-Brown theory, the jump-noise dynamics display an exponential relaxation toward equilibrium with a characteristic reversal time, which we extract for nanomagnets with uniaxial and cubic anisotropy. We relate the jump-noise dynamics to the equivalent Landau-Lifshitz dynamics up to second order correction for a general energy landscape and obtain the analogous Néel-Brown theory's solution of the reversal time. We find that the reversal time of jump-noise dynamics is characterized by Néel-Brown theory's solution at the energy saddle point for small noise. For large noise, the magnetization reversal due to jump-noise dynamics phenomenologically represents macroscopic tunneling of magnetization.

Exploring the additivity of binaural and monaural masking release

PubMed Central

Hall, Joseph W.; Buss, Emily; Grose, John H.

2011-01-01

Experiment 1 examined comodulation masking release (CMR) for a 700-Hz tonal signal under conditions of NoSo (noise and signal interaurally in phase) and NoSπ (noise in phase, signal out of phase) stimulation. The baseline stimulus for CMR was either a single 24-Hz wide narrowband noise centered on the signal frequency [on-signal band (OSB)] or the OSB plus, a set of flanking noise bands having random envelopes. Masking noise was either gated or continuous. The CMR, defined with respect to either the OSB or the random noise baseline, was smaller for NoSπ than NoSo stimulation, particularly when the masker was continuous. Experiment 2 examined whether the same pattern of results would be obtained for a 2000-Hz signal frequency; the number of flanking bands was also manipulated (two versus eight). Results again showed smaller CMR for NoSπ than NoSo stimulation for both continuous and gated masking noise. The CMR was larger with eight than with two flanking bands, and this difference was greater for NoSo than NoSπ. The results of this study are compatible with serial mechanisms of binaural and monaural masking release, but they indicate that the combined masking release (binaural masking-level difference and CMR) falls short of being additive. PMID:21476663

The Role of Visual Noise in Influencing Mental Load and Fatigue in a Steady-State Motion Visual Evoked Potential-Based Brain-Computer Interface.

PubMed

Xie, Jun; Xu, Guanghua; Luo, Ailing; Li, Min; Zhang, Sicong; Han, Chengcheng; Yan, Wenqiang

2017-08-14

As a spatial selective attention-based brain-computer interface (BCI) paradigm, steady-state visual evoked potential (SSVEP) BCI has the advantages of high information transfer rate, high tolerance to artifacts, and robust performance across users. However, its benefits come at the cost of mental load and fatigue occurring in the concentration on the visual stimuli. Noise, as a ubiquitous random perturbation with the power of randomness, may be exploited by the human visual system to enhance higher-level brain functions. In this study, a novel steady-state motion visual evoked potential (SSMVEP, i.e., one kind of SSVEP)-based BCI paradigm with spatiotemporal visual noise was used to investigate the influence of noise on the compensation of mental load and fatigue deterioration during prolonged attention tasks. Changes in α , θ , θ + α powers, θ / α ratio, and electroencephalography (EEG) properties of amplitude, signal-to-noise ratio (SNR), and online accuracy, were used to evaluate mental load and fatigue. We showed that presenting a moderate visual noise to participants could reliably alleviate the mental load and fatigue during online operation of visual BCI that places demands on the attentional processes. This demonstrated that noise could provide a superior solution to the implementation of visual attention controlling-based BCI applications.

Effects of noise on a computational model for disease states of mood disorders

NASA Astrophysics Data System (ADS)

Tobias Huber, Martin; Krieg, Jürgen-Christian; Braun, Hans Albert; Moss, Frank

2000-03-01

Nonlinear dynamics are currently proposed to explain the progressive course of recurrent mood disorders starting with isolated episodes and ending with accelerated irregular (``chaotic") mood fluctuations. Such a low-dimensional disease model is attractive because of its principal accordance with biological disease models, i.e. the kindling and biological rhythms model. However, most natural systems are nonlinear and noisy and several studies in the neuro- and physical sciences have demonstrated interesting cooperative behaviors arising from interacting random and deterministic dynamics. Here, we consider the effects of noise on a recent neurodynamical model for the timecourse of affective disorders (Huber et al.: Biological Psychiatry 1999;46:256-262). We describe noise effects on temporal patterns and mean episode frequencies of various in computo disease states. Our simulations demonstrate that noise can cause unstructured randomness or can maximize periodic order. The frequency of episode occurence can increase with noise but it can also remain unaffected or even can decrease. We show further that noise can make visible bifurcations before they would normally occur under deterministic conditions and we quantify this behavior with a recently developed statistical method. All these effects depend critically on both, the dynamic state and the noise intensity. Implications for neurobiology and course of mood disorders are discussed.

Continuous-variable quantum key distribution protocols over noisy channels.

PubMed

García-Patrón, Raúl; Cerf, Nicolas J

2009-04-03

A continuous-variable quantum key distribution protocol based on squeezed states and heterodyne detection is introduced and shown to attain higher secret key rates over a noisy line than any other one-way Gaussian protocol. This increased resistance to channel noise can be understood as resulting from purposely adding noise to the signal that is converted into the secret key. This notion of noise-enhanced tolerance to noise also provides a better physical insight into the poorly understood discrepancies between the previously defined families of Gaussian protocols.

Noise from Two-Blade Propellers

NASA Technical Reports Server (NTRS)

Stowell, E Z; Deming, A F

1936-01-01

The two-blade propeller, one of the most powerful sources of sound known, has been studied with the view of obtaining fundamental information concerning the noise emission. In order to eliminate engine noise, the propeller was mounted on an electric motor. A microphone was used to pick up the sound whose characteristics were studied electrically. The distribution of noise throughout the frequency range, as well as the spatial distribution about the propeller, was studied. The results are given in the form of polar diagrams. An appendix of common acoustical terms is included.

Probability Theory Plus Noise: Descriptive Estimation and Inferential Judgment.

PubMed

Costello, Fintan; Watts, Paul

2018-01-01

We describe a computational model of two central aspects of people's probabilistic reasoning: descriptive probability estimation and inferential probability judgment. This model assumes that people's reasoning follows standard frequentist probability theory, but it is subject to random noise. This random noise has a regressive effect in descriptive probability estimation, moving probability estimates away from normative probabilities and toward the center of the probability scale. This random noise has an anti-regressive effect in inferential judgement, however. These regressive and anti-regressive effects explain various reliable and systematic biases seen in people's descriptive probability estimation and inferential probability judgment. This model predicts that these contrary effects will tend to cancel out in tasks that involve both descriptive estimation and inferential judgement, leading to unbiased responses in those tasks. We test this model by applying it to one such task, described by Gallistel et al. ). Participants' median responses in this task were unbiased, agreeing with normative probability theory over the full range of responses. Our model captures the pattern of unbiased responses in this task, while simultaneously explaining systematic biases away from normatively correct probabilities seen in other tasks. Copyright © 2018 Cognitive Science Society, Inc.

The first observation of Carbon-13 spin noise spectra

PubMed Central

Schlagnitweit, Judith; Müller, Norbert

2012-01-01

We demonstrate the first 13C NMR spin noise spectra obtained without any pulse excitation by direct detection of the randomly fluctuating noise from samples in a cryogenically cooled probe. Noise power spectra were obtained from 13C enriched methanol and glycerol samples at 176 MHz without and with 1H decoupling, which increases the sensitivity without introducing radio frequency interference with the weak spin noise. The multiplet amplitude ratios in 1H coupled spectra indicate that, although pure spin noise prevails in these spectra, the influence of absorbed circuit noise is still significant at the high concentrations used. In accordance with the theory heteronuclear Overhauser enhancements are absent from the 1H-decoupled 13C spin noise spectra. PMID:23041799

Analysis and attenuation of artifacts caused by spatially and temporally correlated noise sources in Green's function estimates

NASA Astrophysics Data System (ADS)

Martin, E. R.; Dou, S.; Lindsey, N.; Chang, J. P.; Biondi, B. C.; Ajo Franklin, J. B.; Wagner, A. M.; Bjella, K.; Daley, T. M.; Freifeld, B. M.; Robertson, M.; Ulrich, C.; Williams, E. F.

2016-12-01

Localized strong sources of noise in an array have been shown to cause artifacts in Green's function estimates obtained via cross-correlation. Their effect is often reduced through the use of cross-coherence. Beyond independent localized sources, temporally or spatially correlated sources of noise frequently occur in practice but violate basic assumptions of much of the theory behind ambient noise Green's function retrieval. These correlated noise sources can occur in urban environments due to transportation infrastructure, or in areas around industrial operations like pumps running at CO2 sequestration sites or oil and gas drilling sites. Better understanding of these artifacts should help us develop and justify methods for their automatic removal from Green's function estimates. We derive expected artifacts in cross-correlations from several distributions of correlated noise sources including point sources that are exact time-lagged repeats of each other and Gaussian-distributed in space and time with covariance that exponentially decays. Assuming the noise distribution stays stationary over time, the artifacts become more coherent as more ambient noise is included in the Green's function estimates. We support our results with simple computational models. We observed these artifacts in Green's function estimates from a 2015 ambient noise study in Fairbanks, AK where a trenched distributed acoustic sensing (DAS) array was deployed to collect ambient noise alongside a road with the goal of developing a permafrost thaw monitoring system. We found that joints in the road repeatedly being hit by cars travelling at roughly the speed limit led to artifacts similar to those expected when several points are time-lagged copies of each other. We also show test results of attenuating the effects of these sources during time-lapse monitoring of an active thaw test in the same location with noise detected by a 2D trenched DAS array.

Eddy-covariance data with low signal-to-noise ratio: time-lag determination, uncertainties and limit of detection

NASA Astrophysics Data System (ADS)

Langford, B.; Acton, W.; Ammann, C.; Valach, A.; Nemitz, E.

2015-10-01

All eddy-covariance flux measurements are associated with random uncertainties which are a combination of sampling error due to natural variability in turbulence and sensor noise. The former is the principal error for systems where the signal-to-noise ratio of the analyser is high, as is usually the case when measuring fluxes of heat, CO2 or H2O. Where signal is limited, which is often the case for measurements of other trace gases and aerosols, instrument uncertainties dominate. Here, we are applying a consistent approach based on auto- and cross-covariance functions to quantify the total random flux error and the random error due to instrument noise separately. As with previous approaches, the random error quantification assumes that the time lag between wind and concentration measurement is known. However, if combined with commonly used automated methods that identify the individual time lag by looking for the maximum in the cross-covariance function of the two entities, analyser noise additionally leads to a systematic bias in the fluxes. Combining data sets from several analysers and using simulations, we show that the method of time-lag determination becomes increasingly important as the magnitude of the instrument error approaches that of the sampling error. The flux bias can be particularly significant for disjunct data, whereas using a prescribed time lag eliminates these effects (provided the time lag does not fluctuate unduly over time). We also demonstrate that when sampling at higher elevations, where low frequency turbulence dominates and covariance peaks are broader, both the probability and magnitude of bias are magnified. We show that the statistical significance of noisy flux data can be increased (limit of detection can be decreased) by appropriate averaging of individual fluxes, but only if systematic biases are avoided by using a prescribed time lag. Finally, we make recommendations for the analysis and reporting of data with low signal-to-noise and their associated errors.

Eddy-covariance data with low signal-to-noise ratio: time-lag determination, uncertainties and limit of detection

NASA Astrophysics Data System (ADS)

Langford, B.; Acton, W.; Ammann, C.; Valach, A.; Nemitz, E.

2015-03-01

All eddy-covariance flux measurements are associated with random uncertainties which are a combination of sampling error due to natural variability in turbulence and sensor noise. The former is the principal error for systems where the signal-to-noise ratio of the analyser is high, as is usually the case when measuring fluxes of heat, CO2 or H2O. Where signal is limited, which is often the case for measurements of other trace gases and aerosols, instrument uncertainties dominate. We are here applying a consistent approach based on auto- and cross-covariance functions to quantifying the total random flux error and the random error due to instrument noise separately. As with previous approaches, the random error quantification assumes that the time-lag between wind and concentration measurement is known. However, if combined with commonly used automated methods that identify the individual time-lag by looking for the maximum in the cross-covariance function of the two entities, analyser noise additionally leads to a systematic bias in the fluxes. Combining datasets from several analysers and using simulations we show that the method of time-lag determination becomes increasingly important as the magnitude of the instrument error approaches that of the sampling error. The flux bias can be particularly significant for disjunct data, whereas using a prescribed time-lag eliminates these effects (provided the time-lag does not fluctuate unduly over time). We also demonstrate that when sampling at higher elevations, where low frequency turbulence dominates and covariance peaks are broader, both the probability and magnitude of bias are magnified. We show that the statistical significance of noisy flux data can be increased (limit of detection can be decreased) by appropriate averaging of individual fluxes, but only if systematic biases are avoided by using a prescribed time-lag. Finally, we make recommendations for the analysis and reporting of data with low signal-to-noise and their associated errors.

Single-electron thermal noise

NASA Astrophysics Data System (ADS)

Nishiguchi, Katsuhiko; Ono, Yukinori; Fujiwara, Akira

2014-07-01

We report the observation of thermal noise in the motion of single electrons in an ultimately small dynamic random access memory (DRAM). The nanometer-scale transistors that compose the DRAM resolve the thermal noise in single-electron motion. A complete set of fundamental tests conducted on this single-electron thermal noise shows that the noise perfectly follows all the aspects predicted by statistical mechanics, which include the occupation probability, the law of equipartition, a detailed balance, and the law of kT/C. In addition, the counting statistics on the directional motion (i.e., the current) of the single-electron thermal noise indicate that the individual electron motion follows the Poisson process, as it does in shot noise.

Single-electron thermal noise.

PubMed

Nishiguchi, Katsuhiko; Ono, Yukinori; Fujiwara, Akira

2014-07-11

We report the observation of thermal noise in the motion of single electrons in an ultimately small dynamic random access memory (DRAM). The nanometer-scale transistors that compose the DRAM resolve the thermal noise in single-electron motion. A complete set of fundamental tests conducted on this single-electron thermal noise shows that the noise perfectly follows all the aspects predicted by statistical mechanics, which include the occupation probability, the law of equipartition, a detailed balance, and the law of kT/C. In addition, the counting statistics on the directional motion (i.e., the current) of the single-electron thermal noise indicate that the individual electron motion follows the Poisson process, as it does in shot noise.

Method and apparatus for determining position using global positioning satellites

NASA Technical Reports Server (NTRS)

Ward, John (Inventor); Ward, William S. (Inventor)

1998-01-01

A global positioning satellite receiver having an antenna for receiving a L1 signal from a satellite. The L1 signal is processed by a preamplifier stage including a band pass filter and a low noise amplifier and output as a radio frequency (RF) signal. A mixer receives and de-spreads the RF signal in response to a pseudo-random noise code, i.e., Gold code, generated by an internal pseudo-random noise code generator. A microprocessor enters a code tracking loop, such that during the code tracking loop, it addresses the pseudo-random code generator to cause the pseudo-random code generator to sequentially output pseudo-random codes corresponding to satellite codes used to spread the L1 signal, until correlation occurs. When an output of the mixer is indicative of the occurrence of correlation between the RF signal and the generated pseudo-random codes, the microprocessor enters an operational state which slows the receiver code sequence to stay locked with the satellite code sequence. The output of the mixer is provided to a detector which, in turn, controls certain routines of the microprocessor. The microprocessor will output pseudo range information according to an interrupt routine in response detection of correlation. The pseudo range information is to be telemetered to a ground station which determines the position of the global positioning satellite receiver.

Investigation of noise in gear transmissions by the method of mathematical smoothing of experiments

NASA Technical Reports Server (NTRS)

Sheftel, B. T.; Lipskiy, G. K.; Ananov, P. P.; Chernenko, I. K.

1973-01-01

A rotatable central component smoothing method is used to analyze rotating gear noise spectra. A matrix is formulated in which the randomized rows correspond to various tests and the columns to factor values. Canonical analysis of the obtained regression equation permits the calculation of optimal speed and load at a previous assigned noise level.

Boltzmann-distribution-equivalent for Lévy noise and how it leads to thermodynamically consistent epicatalysis

NASA Astrophysics Data System (ADS)

Bier, Martin

2018-02-01

Nonequilibrium systems commonly exhibit Lévy noise. This means that the distribution for the size of the Brownian fluctuations has a "fat" power-law tail. Large Brownian kicks are then more common as compared to the ordinary Gaussian distribution. We consider a two-state system, i.e., two wells and a barrier in between. The barrier is sufficiently high for a barrier crossing to be a rare event. When the noise is Lévy, we do not get a Boltzmann distribution between the two wells. Instead we get a situation where the distribution between the two wells also depends on the height of the barrier that is in between. Ordinarily, a catalyst, by lowering the barrier between two states, speeds up the relaxation to an equilibrium, but does not change the equilibrium distribution. In an environment with Lévy noise, on the other hand, we have the possibility of epicatalysis, i.e., a catalyst effectively altering the distribution between two states through the changing of the barrier height. After deriving formulas to quantitatively describe this effect, we discuss how this idea may apply in nuclear reactors and in the biochemistry of a living cell.

Lévy noise improves the electrical activity in a neuron under electromagnetic radiation.

PubMed

Wu, Juan; Xu, Yong; Ma, Jun

2017-01-01

As the fluctuations of the internal bioelectricity of nervous system is various and complex, the external electromagnetic radiation induced by magnet flux on membrane can be described by the non-Gaussian type distribution of Lévy noise. Thus, the electrical activities in an improved Hindmarsh-Rose model excited by the external electromagnetic radiation of Lévy noise are investigated and some interesting modes of the electrical activities are exhibited. The external electromagnetic radiation of Lévy noise leads to the mode transition of the electrical activities and spatial phase, such as from the rest state to the firing state, from the spiking state to the spiking state with more spikes, and from the spiking state to the bursting state. Then the time points of the firing state versus Lévy noise intensity are depicted. The increasing of Lévy noise intensity heightens the neuron firing. Also the stationary probability distribution functions of the membrane potential of the neuron induced by the external electromagnetic radiation of Lévy noise with different intensity, stability index and skewness papremeters are analyzed. Moreover, through the positive largest Lyapunov exponent, the parameter regions of chaotic electrical mode of the neuron induced by the external electromagnetic radiation of Lévy noise distribution are detected.

Lévy noise improves the electrical activity in a neuron under electromagnetic radiation

PubMed Central

Wu, Juan; Ma, Jun

2017-01-01

As the fluctuations of the internal bioelectricity of nervous system is various and complex, the external electromagnetic radiation induced by magnet flux on membrane can be described by the non-Gaussian type distribution of Lévy noise. Thus, the electrical activities in an improved Hindmarsh-Rose model excited by the external electromagnetic radiation of Lévy noise are investigated and some interesting modes of the electrical activities are exhibited. The external electromagnetic radiation of Lévy noise leads to the mode transition of the electrical activities and spatial phase, such as from the rest state to the firing state, from the spiking state to the spiking state with more spikes, and from the spiking state to the bursting state. Then the time points of the firing state versus Lévy noise intensity are depicted. The increasing of Lévy noise intensity heightens the neuron firing. Also the stationary probability distribution functions of the membrane potential of the neuron induced by the external electromagnetic radiation of Lévy noise with different intensity, stability index and skewness papremeters are analyzed. Moreover, through the positive largest Lyapunov exponent, the parameter regions of chaotic electrical mode of the neuron induced by the external electromagnetic radiation of Lévy noise distribution are detected. PMID:28358824

Properties of Noise Cross-Correlation Functions Obtained from a Distributed Acoustic Sensing Array at Garner Valley, California

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zeng, Xiangfang; Lancelle, Chelsea; Thurber, Clifford

A field test that was conducted at Garner Valley, California, on 11 and 12 September 2013 using distributed acoustic sensing (DAS) to sense ground vibrations provided a continuous overnight record of ambient noise. Furthermore, the energy of ambient noise was concentrated between 5 and 25 Hz, which falls into the typical traffic noise frequency band. A standard procedure (Bensen et al., 2007) was adopted to calculate noise cross-correlation functions (NCFs) for 1-min intervals. The 1-min-long NCFs were stacked using the time–frequency domain phase-weighted-stacking method, which significantly improves signal quality. The obtained NCFs were asymmetrical, which was a result of themore » nonuniform distributed noise sources. A precursor appeared on NCFs along one segment, which was traced to a strong localized noise source or a scatterer at a nearby road intersection. NCF for the radial component of two surface accelerometers along a DAS profile gave similar results to those from DAS channels. Here, we calculated the phase velocity dispersion from DAS NCFs using the multichannel analysis of surface waves technique, and the result agrees with active-source results. We then conclude that ambient noise sources and the high spatial sampling of DAS can provide the same subsurface information as traditional active-source methods.« less

Properties of Noise Cross-Correlation Functions Obtained from a Distributed Acoustic Sensing Array at Garner Valley, California

DOE PAGES

Zeng, Xiangfang; Lancelle, Chelsea; Thurber, Clifford; ...

2017-01-31

A field test that was conducted at Garner Valley, California, on 11 and 12 September 2013 using distributed acoustic sensing (DAS) to sense ground vibrations provided a continuous overnight record of ambient noise. Furthermore, the energy of ambient noise was concentrated between 5 and 25 Hz, which falls into the typical traffic noise frequency band. A standard procedure (Bensen et al., 2007) was adopted to calculate noise cross-correlation functions (NCFs) for 1-min intervals. The 1-min-long NCFs were stacked using the time–frequency domain phase-weighted-stacking method, which significantly improves signal quality. The obtained NCFs were asymmetrical, which was a result of themore » nonuniform distributed noise sources. A precursor appeared on NCFs along one segment, which was traced to a strong localized noise source or a scatterer at a nearby road intersection. NCF for the radial component of two surface accelerometers along a DAS profile gave similar results to those from DAS channels. Here, we calculated the phase velocity dispersion from DAS NCFs using the multichannel analysis of surface waves technique, and the result agrees with active-source results. We then conclude that ambient noise sources and the high spatial sampling of DAS can provide the same subsurface information as traditional active-source methods.« less

Visuo-manual tracking: does intermittent control with aperiodic sampling explain linear power and non-linear remnant without sensorimotor noise?

PubMed

Gollee, Henrik; Gawthrop, Peter J; Lakie, Martin; Loram, Ian D

2017-11-01

A human controlling an external system is described most easily and conventionally as linearly and continuously translating sensory input to motor output, with the inevitable output remnant, non-linearly related to the input, attributed to sensorimotor noise. Recent experiments show sustained manual tracking involves repeated refractoriness (insensitivity to sensory information for a certain duration), with the temporary 200-500 ms periods of irresponsiveness to sensory input making the control process intrinsically non-linear. This evidence calls for re-examination of the extent to which random sensorimotor noise is required to explain the non-linear remnant. This investigation of manual tracking shows how the full motor output (linear component and remnant) can be explained mechanistically by aperiodic sampling triggered by prediction error thresholds. Whereas broadband physiological noise is general to all processes, aperiodic sampling is associated with sensorimotor decision making within specific frontal, striatal and parietal networks; we conclude that manual tracking utilises such slow serial decision making pathways up to several times per second. The human operator is described adequately by linear translation of sensory input to motor output. Motor output also always includes a non-linear remnant resulting from random sensorimotor noise from multiple sources, and non-linear input transformations, for example thresholds or refractory periods. Recent evidence showed that manual tracking incurs substantial, serial, refractoriness (insensitivity to sensory information of 350 and 550 ms for 1st and 2nd order systems respectively). Our two questions are: (i) What are the comparative merits of explaining the non-linear remnant using noise or non-linear transformations? (ii) Can non-linear transformations represent serial motor decision making within the sensorimotor feedback loop intrinsic to tracking? Twelve participants (instructed to act in three prescribed ways) manually controlled two systems (1st and 2nd order) subject to a periodic multi-sine disturbance. Joystick power was analysed using three models, continuous-linear-control (CC), continuous-linear-control with calculated noise spectrum (CCN), and intermittent control with aperiodic sampling triggered by prediction error thresholds (IC). Unlike the linear mechanism, the intermittent control mechanism explained the majority of total power (linear and remnant) (77-87% vs. 8-48%, IC vs. CC). Between conditions, IC used thresholds and distributions of open loop intervals consistent with, respectively, instructions and previous measured, model independent values; whereas CCN required changes in noise spectrum deviating from broadband, signal dependent noise. We conclude that manual tracking uses open loop predictive control with aperiodic sampling. Because aperiodic sampling is inherent to serial decision making within previously identified, specific frontal, striatal and parietal networks we suggest that these structures are intimately involved in visuo-manual tracking. © 2017 The Authors. The Journal of Physiology published by John Wiley & Sons Ltd on behalf of The Physiological Society.

Social inequalities in residential exposure to road traffic noise: an environmental justice analysis based on the RECORD Cohort Study.

PubMed

Havard, Sabrina; Reich, Brian J; Bean, Kathy; Chaix, Basile

2011-05-01

To explore social inequalities in residential exposure to road traffic noise in an urban area. Environmental injustice in road traffic noise exposure was investigated in Paris, France, using the RECORD Cohort Study (n = 2130) and modelled noise data. Associations were assessed by estimating noise exposure within the local area around participants' residence, considering various socioeconomic variables defined at both individual and neighbourhood level, and comparing different regression models attempting or not to control for spatial autocorrelation in noise levels. After individual-level adjustment, participants' noise exposure increased with neighbourhood educational level and dwelling value but also with proportion of non-French citizens, suggesting seemingly contradictory findings. However, when country of citizenship was defined according to its human development level, noise exposure in fact increased and decreased with the proportions of citizens from advantaged and disadvantaged countries, respectively. These findings were consistent with those reported for the other socioeconomic characteristics, suggesting higher road traffic noise exposure in advantaged neighbourhoods. Substantial collinearity between neighbourhood explanatory variables and spatial random effects caused identifiability problems that prevented successful control for spatial autocorrelation. Contrary to previous literature, this study shows that people living in advantaged neighbourhoods were more exposed to road traffic noise in their residential environment than their deprived counterparts. This case study demonstrates the need to systematically perform sensitivity analyses with multiple socioeconomic characteristics to avoid incorrect inferences about an environmental injustice situation and the complexity of effectively controlling for spatial autocorrelation when fixed and random components of the model are correlated.

Quantifying Intrinsic and Extrinsic Variability in Stochastic Gene Expression Models

PubMed Central

Singh, Abhyudai; Soltani, Mohammad

2013-01-01

Genetically identical cell populations exhibit considerable intercellular variation in the level of a given protein or mRNA. Both intrinsic and extrinsic sources of noise drive this variability in gene expression. More specifically, extrinsic noise is the expression variability that arises from cell-to-cell differences in cell-specific factors such as enzyme levels, cell size and cell cycle stage. In contrast, intrinsic noise is the expression variability that is not accounted for by extrinsic noise, and typically arises from the inherent stochastic nature of biochemical processes. Two-color reporter experiments are employed to decompose expression variability into its intrinsic and extrinsic noise components. Analytical formulas for intrinsic and extrinsic noise are derived for a class of stochastic gene expression models, where variations in cell-specific factors cause fluctuations in model parameters, in particular, transcription and/or translation rate fluctuations. Assuming mRNA production occurs in random bursts, transcription rate is represented by either the burst frequency (how often the bursts occur) or the burst size (number of mRNAs produced in each burst). Our analysis shows that fluctuations in the transcription burst frequency enhance extrinsic noise but do not affect the intrinsic noise. On the contrary, fluctuations in the transcription burst size or mRNA translation rate dramatically increase both intrinsic and extrinsic noise components. Interestingly, simultaneous fluctuations in transcription and translation rates arising from randomness in ATP abundance can decrease intrinsic noise measured in a two-color reporter assay. Finally, we discuss how these formulas can be combined with single-cell gene expression data from two-color reporter experiments for estimating model parameters. PMID:24391934

Quantifying intrinsic and extrinsic variability in stochastic gene expression models.

PubMed

Singh, Abhyudai; Soltani, Mohammad

2013-01-01

Genetically identical cell populations exhibit considerable intercellular variation in the level of a given protein or mRNA. Both intrinsic and extrinsic sources of noise drive this variability in gene expression. More specifically, extrinsic noise is the expression variability that arises from cell-to-cell differences in cell-specific factors such as enzyme levels, cell size and cell cycle stage. In contrast, intrinsic noise is the expression variability that is not accounted for by extrinsic noise, and typically arises from the inherent stochastic nature of biochemical processes. Two-color reporter experiments are employed to decompose expression variability into its intrinsic and extrinsic noise components. Analytical formulas for intrinsic and extrinsic noise are derived for a class of stochastic gene expression models, where variations in cell-specific factors cause fluctuations in model parameters, in particular, transcription and/or translation rate fluctuations. Assuming mRNA production occurs in random bursts, transcription rate is represented by either the burst frequency (how often the bursts occur) or the burst size (number of mRNAs produced in each burst). Our analysis shows that fluctuations in the transcription burst frequency enhance extrinsic noise but do not affect the intrinsic noise. On the contrary, fluctuations in the transcription burst size or mRNA translation rate dramatically increase both intrinsic and extrinsic noise components. Interestingly, simultaneous fluctuations in transcription and translation rates arising from randomness in ATP abundance can decrease intrinsic noise measured in a two-color reporter assay. Finally, we discuss how these formulas can be combined with single-cell gene expression data from two-color reporter experiments for estimating model parameters.

Electronic noise in CT detectors: Impact on image noise and artifacts.

PubMed

Duan, Xinhui; Wang, Jia; Leng, Shuai; Schmidt, Bernhard; Allmendinger, Thomas; Grant, Katharine; Flohr, Thomas; McCollough, Cynthia H

2013-10-01

The objective of our study was to evaluate in phantoms the differences in CT image noise and artifact level between two types of commercial CT detectors: one with distributed electronics (conventional) and one with integrated electronics intended to decrease system electronic noise. Cylindric water phantoms of 20, 30, and 40 cm in diameter were scanned using two CT scanners, one equipped with integrated detector electronics and one with distributed detector electronics. All other scanning parameters were identical. Scans were acquired at four tube potentials and 10 tube currents. Semianthropomorphic phantoms were scanned to mimic the shoulder and abdominal regions. Images of two patients were also selected to show the clinical values of the integrated detector. Reduction of image noise with the integrated detector depended on phantom size, tube potential, and tube current. Scans that had low detected signal had the greatest reductions in noise, up to 40% for a 30-cm phantom scanned using 80 kV. This noise reduction translated into up to 50% in dose reduction to achieve equivalent image noise. Streak artifacts through regions of high attenuation were reduced by up to 45% on scans obtained using the integrated detector. Patient images also showed superior image quality for the integrated detector. For the same applied radiation level, the use of integrated electronics in a CT detector showed a substantially reduced level of electronic noise, resulting in reductions in image noise and artifacts, compared with detectors having distributed electronics.

Application of the LSQR algorithm in non-parametric estimation of aerosol size distribution

NASA Astrophysics Data System (ADS)

He, Zhenzong; Qi, Hong; Lew, Zhongyuan; Ruan, Liming; Tan, Heping; Luo, Kun

2016-05-01

Based on the Least Squares QR decomposition (LSQR) algorithm, the aerosol size distribution (ASD) is retrieved in non-parametric approach. The direct problem is solved by the Anomalous Diffraction Approximation (ADA) and the Lambert-Beer Law. An optimal wavelength selection method is developed to improve the retrieval accuracy of the ASD. The proposed optimal wavelength set is selected by the method which can make the measurement signals sensitive to wavelength and decrease the degree of the ill-condition of coefficient matrix of linear systems effectively to enhance the anti-interference ability of retrieval results. Two common kinds of monomodal and bimodal ASDs, log-normal (L-N) and Gamma distributions, are estimated, respectively. Numerical tests show that the LSQR algorithm can be successfully applied to retrieve the ASD with high stability in the presence of random noise and low susceptibility to the shape of distributions. Finally, the experimental measurement ASD over Harbin in China is recovered reasonably. All the results confirm that the LSQR algorithm combined with the optimal wavelength selection method is an effective and reliable technique in non-parametric estimation of ASD.

Noise distribution and denoising of current density images

PubMed Central

Beheshti, Mohammadali; Foomany, Farbod H.; Magtibay, Karl; Jaffray, David A.; Krishnan, Sridhar; Nanthakumar, Kumaraswamy; Umapathy, Karthikeyan

2015-01-01

Abstract. Current density imaging (CDI) is a magnetic resonance (MR) imaging technique that could be used to study current pathways inside the tissue. The current distribution is measured indirectly as phase changes. The inherent noise in the MR imaging technique degrades the accuracy of phase measurements leading to imprecise current variations. The outcome can be affected significantly, especially at a low signal-to-noise ratio (SNR). We have shown the residual noise distribution of the phase to be Gaussian-like and the noise in CDI images approximated as a Gaussian. This finding matches experimental results. We further investigated this finding by performing comparative analysis with denoising techniques, using two CDI datasets with two different currents (20 and 45 mA). We found that the block-matching and three-dimensional (BM3D) technique outperforms other techniques when applied on current density (J). The minimum gain in noise power by BM3D applied to J compared with the next best technique in the analysis was found to be around 2 dB per pixel. We characterize the noise profile in CDI images and provide insights on the performance of different denoising techniques when applied at two different stages of current density reconstruction. PMID:26158100

Noise-Enhanced Human Balance Control

NASA Astrophysics Data System (ADS)

Priplata, Attila; Niemi, James; Salen, Martin; Harry, Jason; Lipsitz, Lewis A.; Collins, J. J.

2002-11-01

Noise can enhance the detection and transmission of weak signals in certain nonlinear systems, via a mechanism known as stochastic resonance. Here we show that input noise can be used to improve motor control in humans. Specifically, we show that the postural sway of both young and elderly individuals during quiet standing can be significantly reduced by applying subsensory mechanical noise to the feet. We further demonstrate with input noise a trend towards the reduction of postural sway in elderly subjects to the level of young subjects. These results suggest that noise-based devices, such as randomly vibrating shoe inserts, may enable people to overcome functional difficulties due to age-related sensory loss.

Adaptive box filters for removal of random noise from digital images

USGS Publications Warehouse

Eliason, E.M.; McEwen, A.S.

1990-01-01

We have developed adaptive box-filtering algorithms to (1) remove random bit errors (pixel values with no relation to the image scene) and (2) smooth noisy data (pixels related to the image scene but with an additive or multiplicative component of noise). For both procedures, we use the standard deviation (??) of those pixels within a local box surrounding each pixel, hence they are adaptive filters. This technique effectively reduces speckle in radar images without eliminating fine details. -from Authors

Noise and Dissipation on Coadjoint Orbits

NASA Astrophysics Data System (ADS)

Arnaudon, Alexis; De Castro, Alex L.; Holm, Darryl D.

2018-02-01

We derive and study stochastic dissipative dynamics on coadjoint orbits by incorporating noise and dissipation into mechanical systems arising from the theory of reduction by symmetry, including a semidirect product extension. Random attractors are found for this general class of systems when the Lie algebra is semi-simple, provided the top Lyapunov exponent is positive. We study in details two canonical examples, the free rigid body and the heavy top, whose stochastic integrable reductions are found and numerical simulations of their random attractors are shown.

Effects of street traffic noise in the night

NASA Technical Reports Server (NTRS)

Wehrli, B.; Nemecek, J.; Turrian, V.; Hoffman, R.; Wanner, H.

1980-01-01

The relationship between automobile traffic noise and the degree of disturbance experience experienced at night was explored through a random sample survey of 1600 individuals in rural and urban areas. The data obtained were used to establish threshold values.

Self-Consistent Theory of Shot Noise Suppression in Ballistic Conductors

NASA Astrophysics Data System (ADS)

Bulashenko, O. M.; Rubí, J. M.; Kochelap, V. A.

Shot-noise measurements become a fundamental tool to probe carrier interactions in mesoscopic systems [1]. A matter of particular interest is the significance of Coulomb interaction which may keep nearby electrons more regularly spaced rather than strictly at random and lead to the noise reduction. That effect occurs in different physical situations. Among them are charge-limited ballistic transport, resonant tunneling, single-electron tunneling, etc. In this communication we address the problem of Coulomb correlations in ballistic conductors under the space-charge-limited transport conditions, and present for the first time a semiclassical self-consistent theory of shot noise in these conductors by solving analytically the kinetic equation coupled self-consistently with a Poisson equation. Basing upon this theory, exact results for current noise in a two-terminal ballistic conductor under the action of long-range Coulomb correlations has been derived. The noise reduction factor (in respect to the uncorrelated value) is obtained in a closed analytical form for a full range of biases ranging from thermal to shot-noise limits which describe perfectly the results of the Monte Carlo simulations for a nondegenerate electron gas [2]. The magnitude of the noise reduction exceeds 0.01, which is of interest from the point of view of possible applications. Using these analytical results one may estimate a relative contribution to the noise from different groups of carriers (in energy space and/or real space) and to investigate in great detail the correlations between different groups of carriers. This leads us to suggest an electron energy spectroscopy experiment to probe the Coulomb correlations in ballistic conductors. Indeed, while the injected carriers are uncorrelated, those in the volume of the conductor are strongly correlated, as follows from the derived formulas for the fluctuation of the distribution function. Those correlations may be observed experimentally by making use of a combination of two already realized techniques: a hot-electron spectrometer [3,4] which allows one to analyze different energy groups of electrons collected at the contact and shot-noise measurements [5,6]. Such "shot noise reduction spectroscopy" allows one to measure the novel phenomena. In particular, we predict the (anti)correlation of the "tangent" electrons having the energy close to the potential barrier height, to all other electron energy groups collected at the receiving contact.

Scattering and transport statistics at the metal-insulator transition: A numerical study of the power-law banded random-matrix model

NASA Astrophysics Data System (ADS)

Méndez-Bermúdez, J. A.; Gopar, Victor A.; Varga, Imre

2010-09-01

We study numerically scattering and transport statistical properties of the one-dimensional Anderson model at the metal-insulator transition described by the power-law banded random matrix (PBRM) model at criticality. Within a scattering approach to electronic transport, we concentrate on the case of a small number of single-channel attached leads. We observe a smooth crossover from localized to delocalized behavior in the average-scattering matrix elements, the conductance probability distribution, the variance of the conductance, and the shot noise power by varying b (the effective bandwidth of the PBRM model) from small (b≪1) to large (b>1) values. We contrast our results with analytic random matrix theory predictions which are expected to be recovered in the limit b→∞ . We also compare our results for the PBRM model with those for the three-dimensional (3D) Anderson model at criticality, finding that the PBRM model with bɛ[0.2,0.4] reproduces well the scattering and transport properties of the 3D Anderson model.

Capacity of PPM on Gaussian and Webb Channels

NASA Technical Reports Server (NTRS)

Divsalar, D.; Dolinar, S.; Pollara, F.; Hamkins, J.

2000-01-01

This paper computes and compares the capacities of M-ary PPM on various idealized channels that approximate the optical communication channel: (1) the standard additive white Gaussian noise (AWGN) channel;(2) a more general AWGN channel (AWGN2) allowing different variances in signal and noise slots;(3) a Webb-distributed channel (Webb2);(4) a Webb+Gaussian channel, modeling Gaussian thermal noise added to Webb-distributed channel outputs.

A Spanish matrix sentence test for assessing speech reception thresholds in noise.

PubMed

Hochmuth, Sabine; Brand, Thomas; Zokoll, Melanie A; Castro, Franz Zenker; Wardenga, Nina; Kollmeier, Birger

2012-07-01

To develop, optimize, and evaluate a new Spanish sentence test in noise. The test comprises a basic matrix of ten names, verbs, numerals, nouns, and adjectives. From this matrix, test lists of ten sentences with an equal syntactical structure can be formed at random, with each list containing the whole speech material. The speech material represents the phoneme distribution of the Spanish language. The test was optimized for measuring speech reception thresholds (SRTs) in noise by adjusting the presentation levels of the individual words. Subsequently, the test was evaluated by independent measurements investigating the training effects, the comparability of test lists, open-set vs. closed-set test format, and performance of listeners of different Spanish varieties. In total, 68 normal-hearing native Spanish-speaking listeners. SRTs measured using an adaptive procedure were 6.2 ± 0.8 dB SNR for the open-set and 7.2 ± 0.7 dB SNR for the closed-set test format. The residual training effect was less than 1 dB after using two double-lists before data collection. No significant differences were found for listeners of different Spanish varieties indicating that the test is applicable to Spanish as well as Latin American listeners. Test lists can be used interchangeably.

Dopamine sensing and measurement using threshold and spectral measurements in random lasers.

PubMed

Wan Ismail, Wan Zakiah; Liu, Guozhen; Zhang, Kai; Goldys, Ewa M; Dawes, Judith M

2016-01-25

We developed a novel dopamine sensing and measurement technique based on aggregation of gold nanoparticles in random lasers. Dopamine combined with copper ions triggers the aggregation of gold nanoparticles and thus affects the performance of random lasers. Dopamine sensing can be achieved using four parameters which are sensitive to the presence of dopamine, that is emission peak shift, emission linewidth, signal-to-noise ratio (peak emission intensity / noise) and random lasing threshold. The dopamine is most sensitively detected by a change in the emission linewidth with a limit of detection of 1 × 10(-7) M, as well as by an increase in the lasing threshold. The dopamine concentration from 1 × 10(-7) M to 1 × 10(-2) M can be determined by calibrating with the laser threshold.

Optical coherence tomography noise modeling and fundamental bounds on human retinal layer segmentation accuracy (Conference Presentation)

NASA Astrophysics Data System (ADS)

DuBose, Theodore B.; Milanfar, Peyman; Izatt, Joseph A.; Farsiu, Sina

2016-03-01

The human retina is composed of several layers, visible by in vivo optical coherence tomography (OCT) imaging. To enhance diagnostics of retinal diseases, several algorithms have been developed to automatically segment one or more of the boundaries of these layers. OCT images are corrupted by noise, which is frequently the result of the detector noise and speckle, a type of coherent noise resulting from the presence of several scatterers in each voxel. However, it is unknown what the empirical distribution of noise in each layer of the retina is, and how the magnitude and distribution of the noise affects the lower bounds of segmentation accuracy. Five healthy volunteers were imaged using a spectral domain OCT probe from Bioptigen, Inc, centered at 850nm with 4.6µm full width at half maximum axial resolution. Each volume was segmented by expert manual graders into nine layers. The histograms of intensities in each layer were then fit to seven possible noise distributions from the literature on speckle and image processing. Using these empirical noise distributions and empirical estimates of the intensity of each layer, the Cramer-Rao lower bound (CRLB), a measure of the variance of an estimator, was calculated for each boundary layer. Additionally, the optimum bias of a segmentation algorithm was calculated, and a corresponding biased CRLB was calculated, which represents the improved performance an algorithm can achieve by using prior knowledge, such as the smoothness and continuity of layer boundaries. Our general mathematical model can be easily adapted for virtually any OCT modality.

Noise effect in an improved conjugate gradient algorithm to invert particle size distribution and the algorithm amendment.

PubMed

Wei, Yongjie; Ge, Baozhen; Wei, Yaolin

2009-03-20

In general, model-independent algorithms are sensitive to noise during laser particle size measurement. An improved conjugate gradient algorithm (ICGA) that can be used to invert particle size distribution (PSD) from diffraction data is presented. By use of the ICGA to invert simulated data with multiplicative or additive noise, we determined that additive noise is the main factor that induces distorted results. Thus the ICGA is amended by introduction of an iteration step-adjusting parameter and is used experimentally on simulated data and some samples. The experimental results show that the sensitivity of the ICGA to noise is reduced and the inverted results are in accord with the real PSD.

Robustness analysis of superpixel algorithms to image blur, additive Gaussian noise, and impulse noise

NASA Astrophysics Data System (ADS)

Brekhna, Brekhna; Mahmood, Arif; Zhou, Yuanfeng; Zhang, Caiming

2017-11-01

Superpixels have gradually become popular in computer vision and image processing applications. However, no comprehensive study has been performed to evaluate the robustness of superpixel algorithms in regard to common forms of noise in natural images. We evaluated the robustness of 11 recently proposed algorithms to different types of noise. The images were corrupted with various degrees of Gaussian blur, additive white Gaussian noise, and impulse noise that either made the object boundaries weak or added extra information to it. We performed a robustness analysis of simple linear iterative clustering (SLIC), Voronoi Cells (VCells), flooding-based superpixel generation (FCCS), bilateral geodesic distance (Bilateral-G), superpixel via geodesic distance (SSS-G), manifold SLIC (M-SLIC), Turbopixels, superpixels extracted via energy-driven sampling (SEEDS), lazy random walk (LRW), real-time superpixel segmentation by DBSCAN clustering, and video supervoxels using partially absorbing random walks (PARW) algorithms. The evaluation process was carried out both qualitatively and quantitatively. For quantitative performance comparison, we used achievable segmentation accuracy (ASA), compactness, under-segmentation error (USE), and boundary recall (BR) on the Berkeley image database. The results demonstrated that all algorithms suffered performance degradation due to noise. For Gaussian blur, Bilateral-G exhibited optimal results for ASA and USE measures, SLIC yielded optimal compactness, whereas FCCS and DBSCAN remained optimal for BR. For the case of additive Gaussian and impulse noises, FCCS exhibited optimal results for ASA, USE, and BR, whereas Bilateral-G remained a close competitor in ASA and USE for Gaussian noise only. Additionally, Turbopixel demonstrated optimal performance for compactness for both types of noise. Thus, no single algorithm was able to yield optimal results for all three types of noise across all performance measures. Conclusively, to solve real-world problems effectively, more robust superpixel algorithms must be developed.

Development of Ultra-Low Noise, High Performance III-V Quantum Well Infrared Photodetectors (QWIPs) for Focal Plane Array Staring Image Sensor Systems

DTIC Science & Technology

1993-11-01

Development of Ultra-Low Noise , High Performance III-V Quantum Well Infrared Photodetectors ( QWIPs )I for Focal Plane Array Staring Image Sensor Systems...experimental studies of dark current, photocurrent, noise fig- ures optical absorption, spectral responsivity and detectivity for different types of QWIPs ...the Boltzmann constant, and T is the temperature. S The noise in the QWIPs is mainly due to the random fluctuations of thermally excited carriers. The

Summing up the noise in gene networks

NASA Astrophysics Data System (ADS)

Paulsson, Johan

2004-01-01

Random fluctuations in genetic networks are inevitable as chemical reactions are probabilistic and many genes, RNAs and proteins are present in low numbers per cell. Such `noise' affects all life processes and has recently been measured using green fluorescent protein (GFP). Two studies show that negative feedback suppresses noise, and three others identify the sources of noise in gene expression. Here I critically analyse these studies and present a simple equation that unifies and extends both the mathematical and biological perspectives.

Simple analytical model for low-frequency frequency-modulation noise of monolithic tunable lasers.

PubMed

Huynh, Tam N; Ó Dúill, Seán P; Nguyen, Lim; Rusch, Leslie A; Barry, Liam P

2014-02-10

We employ simple analytical models to construct the entire frequency-modulation (FM)-noise spectrum of tunable semiconductor lasers. Many contributions to the laser FM noise can be clearly identified from the FM-noise spectrum, such as standard Weiner FM noise incorporating laser relaxation oscillation, excess FM noise due to thermal fluctuations, and carrier-induced refractive index fluctuations from stochastic carrier generation in the passive tuning sections. The contribution of the latter effect is identified by noting a correlation between part of the FM-noise spectrum with the FM-modulation response of the passive sections. We pay particular attention to the case of widely tunable lasers with three independent tuning sections, mainly the sampled-grating distributed Bragg reflector laser, and compare with that of a distributed feedback laser. The theoretical model is confirmed with experimental measurements, with the calculations of the important phase-error variance demonstrating excellent agreement.

Chaotic sources of noise in machine acoustics

NASA Astrophysics Data System (ADS)

Moon, F. C., Prof.; Broschart, Dipl.-Ing. T.

1994-05-01

In this paper a model is posited for deterministic, random-like noise in machines with sliding rigid parts impacting linear continuous machine structures. Such problems occur in gear transmission systems. A mathematical model is proposed to explain the random-like structure-borne and air-borne noise from such systems when the input is a periodic deterministic excitation of the quasi-rigid impacting parts. An experimental study is presented which supports the model. A thin circular plate is impacted by a chaotically vibrating mass excited by a sinusoidal moving base. The results suggest that the plate vibrations might be predicted by replacing the chaotic vibrating mass with a probabilistic forcing function. Prechaotic vibrations of the impacting mass show classical period doubling phenomena.

Punishment-induced fear modifies the daily course of yawning in rats.

PubMed

Moyaho, Alejandro; Valencia, Jaime

2010-01-01

A challenge in the study of yawning behavior is understanding the way external factors may modify it. This study investigated whether response-dependent punishment or random punishment decreased yawning by the application of buzzer noise paired with electric shocks in a high-yawning strain of Sprague-Dawley male rats. Yawn rate increased daily in response to the experimental cage, and also to the buzzer noise. Two alternate periods of no punishment and punishment were followed by a final period of buzzer noise occurring alone. Punishment did not diminish yawning significantly in either condition although the yawn rate increased in the following period of no punishment and in the buzzer-noise period, relative to the period of yawn-dependent punishment. Yawn rate increased in the buzzer-noise period relative to the first period of no punishment and first period of random punishment. These findings indicate that there are constraints that impede the suppression of yawning using punishment, and that yawning is a delayed response to fear produced by response-dependent punishment. Copyright 2010 S. Karger AG, Basel.

Analysis of Digital Communication Signals and Extraction of Parameters.

DTIC Science & Technology

1994-12-01

Fast Fourier Transform (FFT). The correlation methods utilize modified time-frequency distributions , where one of these is based on the Wigner - Ville ... Distribution ( WVD ). Gaussian white noise is added to the signal to simulate various signal-to-noise ratios (SNRs).

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.

PubMed

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.