Linear approximations of global behaviors in nonlinear systems with moderate or strong noise
NASA Astrophysics Data System (ADS)
Liang, Junhao; Din, Anwarud; Zhou, Tianshou
2018-03-01
While many physical or chemical systems can be modeled by nonlinear Langevin equations (LEs), dynamical analysis of these systems is challenging in the cases of moderate and strong noise. Here we develop a linear approximation scheme, which can transform an often intractable LE into a linear set of binomial moment equations (BMEs). This scheme provides a feasible way to capture nonlinear behaviors in the sense of probability distribution and is effective even when the noise is moderate or big. Based on BMEs, we further develop a noise reduction technique, which can effectively handle tough cases where traditional small-noise theories are inapplicable. The overall method not only provides an approximation-based paradigm to analysis of the local and global behaviors of nonlinear noisy systems but also has a wide range of applications.
Signatures of nonlinearity in single cell noise-induced oscillations.
Thomas, Philipp; Straube, Arthur V; Timmer, Jens; Fleck, Christian; Grima, Ramon
2013-10-21
A class of theoretical models seeks to explain rhythmic single cell data by postulating that they are generated by intrinsic noise in biochemical systems whose deterministic models exhibit only damped oscillations. The main features of such noise-induced oscillations are quantified by the power spectrum which measures the dependence of the oscillatory signal's power with frequency. In this paper we derive an approximate closed-form expression for the power spectrum of any monostable biochemical system close to a Hopf bifurcation, where noise-induced oscillations are most pronounced. Unlike the commonly used linear noise approximation which is valid in the macroscopic limit of large volumes, our theory is valid over a wide range of volumes and hence affords a more suitable description of single cell noise-induced oscillations. Our theory predicts that the spectra have three universal features: (i) a dominant peak at some frequency, (ii) a smaller peak at twice the frequency of the dominant peak and (iii) a peak at zero frequency. Of these, the linear noise approximation predicts only the first feature while the remaining two stem from the combination of intrinsic noise and nonlinearity in the law of mass action. The theoretical expressions are shown to accurately match the power spectra determined from stochastic simulations of mitotic and circadian oscillators. Furthermore it is shown how recently acquired single cell rhythmic fibroblast data displays all the features predicted by our theory and that the experimental spectrum is well described by our theory but not by the conventional linear noise approximation. © 2013 Elsevier Ltd. All rights reserved.
Stochastic Swift-Hohenberg Equation with Degenerate Linear Multiplicative Noise
NASA Astrophysics Data System (ADS)
Hernández, Marco; Ong, Kiah Wah
2018-03-01
We study the dynamic transition of the Swift-Hohenberg equation (SHE) when linear multiplicative noise acting on a finite set of modes of the dominant linear flow is introduced. Existence of a stochastic flow and a local stochastic invariant manifold for this stochastic form of SHE are both addressed in this work. We show that the approximate reduced system corresponding to the invariant manifold undergoes a stochastic pitchfork bifurcation, and obtain numerical evidence suggesting that this picture is a good approximation for the full system as well.
Intrinsic noise analysis and stochastic simulation on transforming growth factor beta signal pathway
NASA Astrophysics Data System (ADS)
Wang, Lu; Ouyang, Qi
2010-10-01
A typical biological cell lives in a small volume at room temperature; the noise effect on the cell signal transduction pathway may play an important role in its dynamics. Here, using the transforming growth factor-β signal transduction pathway as an example, we report our stochastic simulations of the dynamics of the pathway and introduce a linear noise approximation method to calculate the transient intrinsic noise of pathway components. We compare the numerical solutions of the linear noise approximation with the statistic results of chemical Langevin equations, and find that they are quantitatively in agreement with the other. When transforming growth factor-β dose decreases to a low level, the time evolution of noise fluctuation of nuclear Smad2—Smad4 complex indicates the abnormal enhancement in the transient signal activation process.
Stochastic resonance-enhanced laser-based particle detector.
Dutta, A; Werner, C
2009-01-01
This paper presents a Laser-based particle detector whose response was enhanced by modulating the Laser diode with a white-noise generator. A Laser sheet was generated to cast a shadow of the object on a 200 dots per inch, 512 x 1 pixels linear sensor array. The Laser diode was modulated with a white-noise generator to achieve stochastic resonance. The white-noise generator essentially amplified the wide-bandwidth (several hundred MHz) noise produced by a reverse-biased zener diode operating in junction-breakdown mode. The gain in the amplifier in the white-noise generator was set such that the Receiver Operating Characteristics plot provided the best discriminability. A monofiber 40 AWG (approximately 80 microm) wire was detected with approximately 88% True Positive rate and approximately 19% False Positive rate in presence of white-noise modulation and with approximately 71% True Positive rate and approximately 15% False Positive rate in absence of white-noise modulation.
Energy diffusion controlled reaction rate of reacting particle driven by broad-band noise
NASA Astrophysics Data System (ADS)
Deng, M. L.; Zhu, W. Q.
2007-10-01
The energy diffusion controlled reaction rate of a reacting particle with linear weak damping and broad-band noise excitation is studied by using the stochastic averaging method. First, the stochastic averaging method for strongly nonlinear oscillators under broad-band noise excitation using generalized harmonic functions is briefly introduced. Then, the reaction rate of the classical Kramers' reacting model with linear weak damping and broad-band noise excitation is investigated by using the stochastic averaging method. The averaged Itô stochastic differential equation describing the energy diffusion and the Pontryagin equation governing the mean first-passage time (MFPT) are established. The energy diffusion controlled reaction rate is obtained as the inverse of the MFPT by solving the Pontryagin equation. The results of two special cases of broad-band noises, i.e. the harmonic noise and the exponentially corrected noise, are discussed in details. It is demonstrated that the general expression of reaction rate derived by the authors can be reduced to the classical ones via linear approximation and high potential barrier approximation. The good agreement with the results of the Monte Carlo simulation verifies that the reaction rate can be well predicted using the stochastic averaging method.
Evaluation of alternatives to sound barrier walls.
DOT National Transportation Integrated Search
2013-06-01
The existing INDOTs noise wall specification was developed primarily on the basis of knowledge of the conventional precast concrete : panel systems. Currently, the constructed cost of conventional noise walls is approximately $2 million per linear...
Feature Visibility Limits in the Non-Linear Enhancement of Turbid Images
NASA Technical Reports Server (NTRS)
Jobson, Daniel J.; Rahman, Zia-ur; Woodell, Glenn A.
2003-01-01
The advancement of non-linear processing methods for generic automatic clarification of turbid imagery has led us from extensions of entirely passive multiscale Retinex processing to a new framework of active measurement and control of the enhancement process called the Visual Servo. In the process of testing this new non-linear computational scheme, we have identified that feature visibility limits in the post-enhancement image now simplify to a single signal-to-noise figure of merit: a feature is visible if the feature-background signal difference is greater than the RMS noise level. In other words, a signal-to-noise limit of approximately unity constitutes a lower limit on feature visibility.
The Prediction of Scattered Broadband Shock-Associated Noise
NASA Technical Reports Server (NTRS)
Miller, Steven A. E.
2015-01-01
A mathematical model is developed for the prediction of scattered broadband shock-associated noise. Model arguments are dependent on the vector Green's function of the linearized Euler equations, steady Reynolds-averaged Navier-Stokes solutions, and the two-point cross-correlation of the equivalent source. The equivalent source is dependent on steady Reynolds-averaged Navier-Stokes solutions of the jet flow, that capture the nozzle geometry and airframe surface. Contours of the time-averaged streamwise velocity component and turbulent kinetic energy are examined with varying airframe position relative to the nozzle exit. Propagation effects are incorporated by approximating the vector Green's function of the linearized Euler equations. This approximation involves the use of ray theory and an assumption that broadband shock-associated noise is relatively unaffected by the refraction of the jet shear layer. A non-dimensional parameter is proposed that quantifies the changes of the broadband shock-associated noise source with varying jet operating condition and airframe position. Scattered broadband shock-associated noise possesses a second set of broadband lobes that are due to the effect of scattering. Presented predictions demonstrate relatively good agreement compared to a wide variety of measurements.
Noise in solid-state nanopores.
Smeets, R M M; Keyser, U F; Dekker, N H; Dekker, C
2008-01-15
We study ionic current fluctuations in solid-state nanopores over a wide frequency range and present a complete description of the noise characteristics. At low frequencies (f approximately < 100 Hz) we observe 1/f-type of noise. We analyze this low-frequency noise at different salt concentrations and find that the noise power remarkably scales linearly with the inverse number of charge carriers, in agreement with Hooge's relation. We find a Hooge parameter alpha = (1.1 +/- 0.1) x 10(-4). In the high-frequency regime (f approximately > 1 kHz), we can model the increase in current power spectral density with frequency through a calculation of the Johnson noise. Finally, we use these results to compute the signal-to-noise ratio for DNA translocation for different salt concentrations and nanopore diameters, yielding the parameters for optimal detection efficiency.
Linear-time general decoding algorithm for the surface code
NASA Astrophysics Data System (ADS)
Darmawan, Andrew S.; Poulin, David
2018-05-01
A quantum error correcting protocol can be substantially improved by taking into account features of the physical noise process. We present an efficient decoder for the surface code which can account for general noise features, including coherences and correlations. We demonstrate that the decoder significantly outperforms the conventional matching algorithm on a variety of noise models, including non-Pauli noise and spatially correlated noise. The algorithm is based on an approximate calculation of the logical channel using a tensor-network description of the noisy state.
Wang, Jun-Sheng; Yang, Guang-Hong
2017-07-25
This paper studies the optimal output-feedback control problem for unknown linear discrete-time systems with stochastic measurement and process noise. A dithered Bellman equation with the innovation covariance matrix is constructed via the expectation operator given in the form of a finite summation. On this basis, an output-feedback-based approximate dynamic programming method is developed, where the terms depending on the innovation covariance matrix are available with the aid of the innovation covariance matrix identified beforehand. Therefore, by iterating the Bellman equation, the resulting value function can converge to the optimal one in the presence of the aforementioned noise, and the nearly optimal control laws are delivered. To show the effectiveness and the advantages of the proposed approach, a simulation example and a velocity control experiment on a dc machine are employed.
Sanz, Luis; Alonso, Juan Antonio
2017-12-01
In this work we develop approximate aggregation techniques in the context of slow-fast linear population models governed by stochastic differential equations and apply the results to the treatment of populations with spatial heterogeneity. Approximate aggregation techniques allow one to transform a complex system involving many coupled variables and in which there are processes with different time scales, by a simpler reduced model with a fewer number of 'global' variables, in such a way that the dynamics of the former can be approximated by that of the latter. In our model we contemplate a linear fast deterministic process together with a linear slow process in which the parameters are affected by additive noise, and give conditions for the solutions corresponding to positive initial conditions to remain positive for all times. By letting the fast process reach equilibrium we build a reduced system with a lesser number of variables, and provide results relating the asymptotic behaviour of the first- and second-order moments of the population vector for the original and the reduced system. The general technique is illustrated by analysing a multiregional stochastic system in which dispersal is deterministic and the rate growth of the populations in each patch is affected by additive noise.
ORACLS: A system for linear-quadratic-Gaussian control law design
NASA Technical Reports Server (NTRS)
Armstrong, E. S.
1978-01-01
A modern control theory design package (ORACLS) for constructing controllers and optimal filters for systems modeled by linear time-invariant differential or difference equations is described. Numerical linear-algebra procedures are used to implement the linear-quadratic-Gaussian (LQG) methodology of modern control theory. Algorithms are included for computing eigensystems of real matrices, the relative stability of a matrix, factored forms for nonnegative definite matrices, the solutions and least squares approximations to the solutions of certain linear matrix algebraic equations, the controllability properties of a linear time-invariant system, and the steady state covariance matrix of an open-loop stable system forced by white noise. Subroutines are provided for solving both the continuous and discrete optimal linear regulator problems with noise free measurements and the sampled-data optimal linear regulator problem. For measurement noise, duality theory and the optimal regulator algorithms are used to solve the continuous and discrete Kalman-Bucy filter problems. Subroutines are also included which give control laws causing the output of a system to track the output of a prescribed model.
Analysis of separation test for automatic brake adjuster based on linear radon transformation
NASA Astrophysics Data System (ADS)
Luo, Zai; Jiang, Wensong; Guo, Bin; Fan, Weijun; Lu, Yi
2015-01-01
The linear Radon transformation is applied to extract inflection points for online test system under the noise conditions. The linear Radon transformation has a strong ability of anti-noise and anti-interference by fitting the online test curve in several parts, which makes it easy to handle consecutive inflection points. We applied the linear Radon transformation to the separation test system to solve the separating clearance of automatic brake adjuster. The experimental results show that the feature point extraction error of the gradient maximum optimal method is approximately equal to ±0.100, while the feature point extraction error of linear Radon transformation method can reach to ±0.010, which has a lower error than the former one. In addition, the linear Radon transformation is robust.
Optimal entrainment of circadian clocks in the presence of noise
NASA Astrophysics Data System (ADS)
Monti, Michele; Lubensky, David K.; ten Wolde, Pieter Rein
2018-03-01
Circadian clocks are biochemical oscillators that allow organisms to estimate the time of the day. These oscillators are inherently noisy due to the discrete nature of the reactants and the stochastic character of their interactions. To keep these oscillators in sync with the daily day-night rhythm in the presence of noise, circadian clocks must be coupled to the dark-light cycle. In this paper, we study the entrainment of phase oscillators as a function of the intrinsic noise in the system. Using stochastic simulations, we compute the optimal coupling strength, intrinsic frequency, and shape of the phase-response curve, that maximize the mutual information between the phase of the clock and time. We show that the optimal coupling strength and intrinsic frequency increase with the noise, but that the shape of the phase-response curve varies nonmonotonically with the noise: in the low-noise regime, it features a dead zone that increases in width as the noise increases, while in the high-noise regime, the width decreases with the noise. These results arise from a tradeoff between maximizing stability—noise suppression—and maximizing linearity of the input-output, i.e., time-phase, relation. We also show that three analytic approximations—the linear-noise approximation, the phase-averaging method, and linear-response theory—accurately describe different regimes of the coupling strength and the noise.
Study of the intensity noise and intensity modulation in a of hybrid soliton pulsed source
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dogru, Nuran; Oziazisi, M Sadetin
2005-10-31
The relative intensity noise (RIN) and small-signal intensity modulation (IM) of a hybrid soliton pulsed source (HSPS) with a linearly chirped Gaussian apodised fibre Bragg grating (FBG) are considered in the electric-field approximation. The HSPS is described by solving the dynamic coupled-mode equations. It is shown that consideration of the carrier density noise in the HSPS in addition to the spontaneous noise is necessary to analyse accurately noise in the mode-locked HSPS. It is also shown that the resonance peak spectral splitting (RPSS) of the IM near the frequency inverse to the round-trip time of light in the external cavitymore » can be eliminated by selecting an appropriate linear chirp rate in the Gaussian apodised FBG. (laser applications and other topics in quantum electronics)« less
NASA Astrophysics Data System (ADS)
Herath, Narmada; Del Vecchio, Domitilla
2018-03-01
Biochemical reaction networks often involve reactions that take place on different time scales, giving rise to "slow" and "fast" system variables. This property is widely used in the analysis of systems to obtain dynamical models with reduced dimensions. In this paper, we consider stochastic dynamics of biochemical reaction networks modeled using the Linear Noise Approximation (LNA). Under time-scale separation conditions, we obtain a reduced-order LNA that approximates both the slow and fast variables in the system. We mathematically prove that the first and second moments of this reduced-order model converge to those of the full system as the time-scale separation becomes large. These mathematical results, in particular, provide a rigorous justification to the accuracy of LNA models derived using the stochastic total quasi-steady state approximation (tQSSA). Since, in contrast to the stochastic tQSSA, our reduced-order model also provides approximations for the fast variable stochastic properties, we term our method the "stochastic tQSSA+". Finally, we demonstrate the application of our approach on two biochemical network motifs found in gene-regulatory and signal transduction networks.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Yongge; Xu, Wei, E-mail: weixu@nwpu.edu.cn; Yang, Guidong
The Poisson white noise, as a typical non-Gaussian excitation, has attracted much attention recently. However, little work was referred to the study of stochastic systems with fractional derivative under Poisson white noise excitation. This paper investigates the stationary response of a class of quasi-linear systems with fractional derivative excited by Poisson white noise. The equivalent stochastic system of the original stochastic system is obtained. Then, approximate stationary solutions are obtained with the help of the perturbation method. Finally, two typical examples are discussed in detail to demonstrate the effectiveness of the proposed method. The analysis also shows that the fractionalmore » order and the fractional coefficient significantly affect the responses of the stochastic systems with fractional derivative.« less
Yan, Hao; Duan, Hui-Zong; Li, Lin-Tao; Liang, Yu-Rong; Luo, Jun; Yeh, Hsien-Chi
2015-12-01
Picometer laser interferometry is an essential tool for ultra-precision measurements in frontier scientific research and advanced manufacturing. In this paper, we present a dual-heterodyne laser interferometer for simultaneously measuring linear and angular displacements with resolutions of picometer and nanoradian, respectively. The phase measurement method is based on cross-correlation analysis and realized by a PXI-bus data acquisition system. By implementing a dual-heterodyne interferometer with a highly symmetric optical configuration, low frequency noises caused by the environmental fluctuations can be suppressed to very low levels via common-mode noise rejection. Experimental results for the dual-heterodyne interferometer configuration presented demonstrate that the noise levels of the linear and angular displacement measurements are approximately 1 pm/Hz(1/2) and 0.5 nrad/Hz(1/2) at 1 Hz.
Predicting the performance of linear optical detectors in free space laser communication links
NASA Astrophysics Data System (ADS)
Farrell, Thomas C.
2018-05-01
While the fundamental performance limit for optical communications is set by the quantum nature of light, in practical systems background light, dark current, and thermal noise of the electronics also degrade performance. In this paper, we derive a set of equations predicting the performance of PIN diodes and linear mode avalanche photo diodes (APDs) in the presence of such noise sources. Electrons generated by signal, background, and dark current shot noise are well modeled in PIN diodes as Poissonian statistical processes. In APDs, on the other hand, the amplifying effects of the device result in statistics that are distinctly non-Poissonian. Thermal noise is well modeled as Gaussian. In this paper, we appeal to the central limit theorem and treat both the variability of the signal and the sum of noise sources as Gaussian. Comparison against Monte-Carlo simulation of PIN diode performance (where we do model shot noise with draws from a Poissonian distribution) validates the legitimacy of this approximation. On-off keying, M-ary pulse position, and binary differential phase shift keying modulation are modeled. We conclude with examples showing how the equations may be used in a link budget to estimate the performance of optical links using linear receivers.
Adaptive Filtering Using Recurrent Neural Networks
NASA Technical Reports Server (NTRS)
Parlos, Alexander G.; Menon, Sunil K.; Atiya, Amir F.
2005-01-01
A method for adaptive (or, optionally, nonadaptive) filtering has been developed for estimating the states of complex process systems (e.g., chemical plants, factories, or manufacturing processes at some level of abstraction) from time series of measurements of system inputs and outputs. The method is based partly on the fundamental principles of the Kalman filter and partly on the use of recurrent neural networks. The standard Kalman filter involves an assumption of linearity of the mathematical model used to describe a process system. The extended Kalman filter accommodates a nonlinear process model but still requires linearization about the state estimate. Both the standard and extended Kalman filters involve the often unrealistic assumption that process and measurement noise are zero-mean, Gaussian, and white. In contrast, the present method does not involve any assumptions of linearity of process models or of the nature of process noise; on the contrary, few (if any) assumptions are made about process models, noise models, or the parameters of such models. In this regard, the method can be characterized as one of nonlinear, nonparametric filtering. The method exploits the unique ability of neural networks to approximate nonlinear functions. In a given case, the process model is limited mainly by limitations of the approximation ability of the neural networks chosen for that case. Moreover, despite the lack of assumptions regarding process noise, the method yields minimum- variance filters. In that they do not require statistical models of noise, the neural- network-based state filters of this method are comparable to conventional nonlinear least-squares estimators.
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.
2012-01-01
Background It is well known that the deterministic dynamics of biochemical reaction networks can be more easily studied if timescale separation conditions are invoked (the quasi-steady-state assumption). In this case the deterministic dynamics of a large network of elementary reactions are well described by the dynamics of a smaller network of effective reactions. Each of the latter represents a group of elementary reactions in the large network and has associated with it an effective macroscopic rate law. A popular method to achieve model reduction in the presence of intrinsic noise consists of using the effective macroscopic rate laws to heuristically deduce effective probabilities for the effective reactions which then enables simulation via the stochastic simulation algorithm (SSA). The validity of this heuristic SSA method is a priori doubtful because the reaction probabilities for the SSA have only been rigorously derived from microscopic physics arguments for elementary reactions. Results We here obtain, by rigorous means and in closed-form, a reduced linear Langevin equation description of the stochastic dynamics of monostable biochemical networks in conditions characterized by small intrinsic noise and timescale separation. The slow-scale linear noise approximation (ssLNA), as the new method is called, is used to calculate the intrinsic noise statistics of enzyme and gene networks. The results agree very well with SSA simulations of the non-reduced network of elementary reactions. In contrast the conventional heuristic SSA is shown to overestimate the size of noise for Michaelis-Menten kinetics, considerably under-estimate the size of noise for Hill-type kinetics and in some cases even miss the prediction of noise-induced oscillations. Conclusions A new general method, the ssLNA, is derived and shown to correctly describe the statistics of intrinsic noise about the macroscopic concentrations under timescale separation conditions. The ssLNA provides a simple and accurate means of performing stochastic model reduction and hence it is expected to be of widespread utility in studying the dynamics of large noisy reaction networks, as is common in computational and systems biology. PMID:22583770
Time-lapse joint AVO inversion using generalized linear method based on exact Zoeppritz equations
NASA Astrophysics Data System (ADS)
Zhi, L.; Gu, H.
2017-12-01
The conventional method of time-lapse AVO (Amplitude Versus Offset) inversion is mainly based on the approximate expression of Zoeppritz equations. Though the approximate expression is concise and convenient to use, it has certain limitations. For example, its application condition is that the difference of elastic parameters between the upper medium and lower medium is little and the incident angle is small. In addition, the inversion of density is not stable. Therefore, we develop the method of time-lapse joint AVO inversion based on exact Zoeppritz equations. In this method, we apply exact Zoeppritz equations to calculate the reflection coefficient of PP wave. And in the construction of objective function for inversion, we use Taylor expansion to linearize the inversion problem. Through the joint AVO inversion of seismic data in baseline survey and monitor survey, we can obtain P-wave velocity, S-wave velocity, density in baseline survey and their time-lapse changes simultaneously. We can also estimate the oil saturation change according to inversion results. Compared with the time-lapse difference inversion, the joint inversion has a better applicability. It doesn't need some assumptions and can estimate more parameters simultaneously. Meanwhile, by using the generalized linear method, the inversion is easily realized and its calculation amount is small. We use the Marmousi model to generate synthetic seismic records to test and analyze the influence of random noise. Without noise, all estimation results are relatively accurate. With the increase of noise, P-wave velocity change and oil saturation change are stable and less affected by noise. S-wave velocity change is most affected by noise. Finally we use the actual field data of time-lapse seismic prospecting to process and the results can prove the availability and feasibility of our method in actual situation.
Phase unwrapping algorithm using polynomial phase approximation and linear Kalman filter.
Kulkarni, Rishikesh; Rastogi, Pramod
2018-02-01
A noise-robust phase unwrapping algorithm is proposed based on state space analysis and polynomial phase approximation using wrapped phase measurement. The true phase is approximated as a two-dimensional first order polynomial function within a small sized window around each pixel. The estimates of polynomial coefficients provide the measurement of phase and local fringe frequencies. A state space representation of spatial phase evolution and the wrapped phase measurement is considered with the state vector consisting of polynomial coefficients as its elements. Instead of using the traditional nonlinear Kalman filter for the purpose of state estimation, we propose to use the linear Kalman filter operating directly with the wrapped phase measurement. The adaptive window width is selected at each pixel based on the local fringe density to strike a balance between the computation time and the noise robustness. In order to retrieve the unwrapped phase, either a line-scanning approach or a quality guided strategy of pixel selection is used depending on the underlying continuous or discontinuous phase distribution, respectively. Simulation and experimental results are provided to demonstrate the applicability of the proposed method.
Kernel Wiener filter and its application to pattern recognition.
Yoshino, Hirokazu; Dong, Chen; Washizawa, Yoshikazu; Yamashita, Yukihiko
2010-11-01
The Wiener filter (WF) is widely used for inverse problems. From an observed signal, it provides the best estimated signal with respect to the squared error averaged over the original and the observed signals among linear operators. The kernel WF (KWF), extended directly from WF, has a problem that an additive noise has to be handled by samples. Since the computational complexity of kernel methods depends on the number of samples, a huge computational cost is necessary for the case. By using the first-order approximation of kernel functions, we realize KWF that can handle such a noise not by samples but as a random variable. We also propose the error estimation method for kernel filters by using the approximations. In order to show the advantages of the proposed methods, we conducted the experiments to denoise images and estimate errors. We also apply KWF to classification since KWF can provide an approximated result of the maximum a posteriori classifier that provides the best recognition accuracy. The noise term in the criterion can be used for the classification in the presence of noise or a new regularization to suppress changes in the input space, whereas the ordinary regularization for the kernel method suppresses changes in the feature space. In order to show the advantages of the proposed methods, we conducted experiments of binary and multiclass classifications and classification in the presence of noise.
Uniform apparent contrast noise: A picture of the noise of the visual contrast detection system
NASA Technical Reports Server (NTRS)
Ahumada, A. J., Jr.; Watson, A. B.
1984-01-01
A picture which is a sample of random contrast noise is generated. The noise amplitude spectrum in each region of the picture is inversely proportional to spatial frequency contrast sensitivity for that region, assuming the observer fixates the center of the picture and is the appropriate distance from it. In this case, the picture appears to have approximately the same contrast everywhere. To the extent that contrast detection thresholds are determined by visual system noise, this picture can be regarded as a picture of the noise of that system. There is evidence that, at different eccentricities, contrast sensitivity functions differ only by a magnification factor. The picture was generated by filtering a sample of white noise with a filter whose frequency response is inversely proportional to foveal contrast sensitivity. It was then stretched by a space-varying magnification function. The picture summmarizes a noise linear model of detection and discrimination of contrast signals by referring the model noise to the input picture domain.
On a stochastic control method for weakly coupled linear systems. M.S. Thesis
NASA Technical Reports Server (NTRS)
Kwong, R. H.
1972-01-01
The stochastic control of two weakly coupled linear systems with different controllers is considered. Each controller only makes measurements about his own system; no information about the other system is assumed to be available. Based on the noisy measurements, the controllers are to generate independently suitable control policies which minimize a quadratic cost functional. To account for the effects of weak coupling directly, an approximate model, which involves replacing the influence of one system on the other by a white noise process is proposed. Simple suboptimal control problem for calculating the covariances of these noises is solved using the matrix minimum principle. The overall system performance based on this scheme is analyzed as a function of the degree of intersystem coupling.
Single photon counting linear mode avalanche photodiode technologies
NASA Astrophysics Data System (ADS)
Williams, George M.; Huntington, Andrew S.
2011-10-01
The false count rate of a single-photon-sensitive photoreceiver consisting of a high-gain, low-excess-noise linear-mode InGaAs avalanche photodiode (APD) and a high-bandwidth transimpedance amplifier (TIA) is fit to a statistical model. The peak height distribution of the APD's multiplied dark current is approximated by the weighted sum of McIntyre distributions, each characterizing dark current generated at a different location within the APD's junction. The peak height distribution approximated in this way is convolved with a Gaussian distribution representing the input-referred noise of the TIA to generate the statistical distribution of the uncorrelated sum. The cumulative distribution function (CDF) representing count probability as a function of detection threshold is computed, and the CDF model fit to empirical false count data. It is found that only k=0 McIntyre distributions fit the empirically measured CDF at high detection threshold, and that false count rate drops faster than photon count rate as detection threshold is raised. Once fit to empirical false count data, the model predicts the improvement of the false count rate to be expected from reductions in TIA noise and APD dark current. Improvement by at least three orders of magnitude is thought feasible with further manufacturing development and a capacitive-feedback TIA (CTIA).
Mass flow meter using the triboelectric effect for measurement in cryogenics
NASA Technical Reports Server (NTRS)
Bernatowicz, Henry; Cunningham, Jock; Wolff, Steve
1987-01-01
The use of triboelectric charge to measure the mass flow rate of cryogens for the Space Shuttle Main Engine was investigated. Cross correlation of the triboelectric charge signals was used to determine the transit time of the cryogen between two sensor locations in a .75-in tube. The ring electrode sensors were mounted in a removable spool piece. Three spool pieces were constructed for delivery, each with a different design. One set of electronics for implementation of the cross correlation and flow calculation was constructed for delivery. Tests were made using a laboratory flow loop using liquid freon and transformer oil. The measured flow precision was 1 percent and the response was linear. The natural frequency distribution of the triboelectric signal was approximately 1/f. The sensor electrodes should have an axial length less than approximately one/tenth pipe diameter. The electrode spacing should be less than approximately one pipe diameter. Tests using liquid nitrogen demonstrated poor tribo-signal to noise ratio. Most of the noise was microphonic and common to both electrode systems. The common noise rejection facility of the correlator was successful in compensating for this noise but the signal was too small to enable reliable demonstration of the technique in liquid nitrogen.
Jafari, Masoumeh; Salimifard, Maryam; Dehghani, Maryam
2014-07-01
This paper presents an efficient method for identification of nonlinear Multi-Input Multi-Output (MIMO) systems in the presence of colored noises. The method studies the multivariable nonlinear Hammerstein and Wiener models, in which, the nonlinear memory-less block is approximated based on arbitrary vector-based basis functions. The linear time-invariant (LTI) block is modeled by an autoregressive moving average with exogenous (ARMAX) model which can effectively describe the moving average noises as well as the autoregressive and the exogenous dynamics. According to the multivariable nature of the system, a pseudo-linear-in-the-parameter model is obtained which includes two different kinds of unknown parameters, a vector and a matrix. Therefore, the standard least squares algorithm cannot be applied directly. To overcome this problem, a Hierarchical Least Squares Iterative (HLSI) algorithm is used to simultaneously estimate the vector and the matrix of unknown parameters as well as the noises. The efficiency of the proposed identification approaches are investigated through three nonlinear MIMO case studies. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Recent Results on "Approximations to Optimal Alarm Systems for Anomaly Detection"
NASA Technical Reports Server (NTRS)
Martin, Rodney Alexander
2009-01-01
An optimal alarm system and its approximations may use Kalman filtering for univariate linear dynamic systems driven by Gaussian noise to provide a layer of predictive capability. Predicted Kalman filter future process values and a fixed critical threshold can be used to construct a candidate level-crossing event over a predetermined prediction window. An optimal alarm system can be designed to elicit the fewest false alarms for a fixed detection probability in this particular scenario.
Trellis Coding of Non-coherent Multiple Symbol Full Response M-ary CPFSK with Modulation Index 1/M
NASA Technical Reports Server (NTRS)
Lee, H.; Divsalar, D.; Weber, C.
1994-01-01
This paper introduces a trellis coded modulation (TCM) scheme for non-coherent multiple full response M-ary CPFSK with modulation index 1/M. A proper branch metric for the trellis decoder is obtained by employing a simple approximation of the modified Bessel function for large signal to noise ratio (SNR). Pairwise error probability of coded sequences is evaluated by applying a linear approximation to the Rician random variable.
How reliable is the linear noise approximation of gene regulatory networks?
2013-01-01
Background The linear noise approximation (LNA) is commonly used to predict how noise is regulated and exploited at the cellular level. These predictions are exact for reaction networks composed exclusively of first order reactions or for networks involving bimolecular reactions and large numbers of molecules. It is however well known that gene regulation involves bimolecular interactions with molecule numbers as small as a single copy of a particular gene. It is therefore questionable how reliable are the LNA predictions for these systems. Results We implement in the software package intrinsic Noise Analyzer (iNA), a system size expansion based method which calculates the mean concentrations and the variances of the fluctuations to an order of accuracy higher than the LNA. We then use iNA to explore the parametric dependence of the Fano factors and of the coefficients of variation of the mRNA and protein fluctuations in models of genetic networks involving nonlinear protein degradation, post-transcriptional, post-translational and negative feedback regulation. We find that the LNA can significantly underestimate the amplitude and period of noise-induced oscillations in genetic oscillators. We also identify cases where the LNA predicts that noise levels can be optimized by tuning a bimolecular rate constant whereas our method shows that no such regulation is possible. All our results are confirmed by stochastic simulations. Conclusion The software iNA allows the investigation of parameter regimes where the LNA fares well and where it does not. We have shown that the parametric dependence of the coefficients of variation and Fano factors for common gene regulatory networks is better described by including terms of higher order than LNA in the system size expansion. This analysis is considerably faster than stochastic simulations due to the extensive ensemble averaging needed to obtain statistically meaningful results. Hence iNA is well suited for performing computationally efficient and quantitative studies of intrinsic noise in gene regulatory networks. PMID:24266939
Probabilistic density function method for nonlinear dynamical systems driven by colored noise.
Barajas-Solano, David A; Tartakovsky, Alexandre M
2016-05-01
We present a probability density function (PDF) method for a system of nonlinear stochastic ordinary differential equations driven by colored noise. The method provides an integrodifferential equation for the temporal evolution of the joint PDF of the system's state, which we close by means of a modified large-eddy-diffusivity (LED) closure. In contrast to the classical LED closure, the proposed closure accounts for advective transport of the PDF in the approximate temporal deconvolution of the integrodifferential equation. In addition, we introduce the generalized local linearization approximation for deriving a computable PDF equation in the form of a second-order partial differential equation. We demonstrate that the proposed closure and localization accurately describe the dynamics of the PDF in phase space for systems driven by noise with arbitrary autocorrelation time. We apply the proposed PDF method to analyze a set of Kramers equations driven by exponentially autocorrelated Gaussian colored noise to study nonlinear oscillators and the dynamics and stability of a power grid. Numerical experiments show the PDF method is accurate when the noise autocorrelation time is either much shorter or longer than the system's relaxation time, while the accuracy decreases as the ratio of the two timescales approaches unity. Similarly, the PDF method accuracy decreases with increasing standard deviation of the noise.
Kim, SangYun; Samadpoor Rikan, Behnam; Pu, YoungGun; Yoo, Sang-Sun; Lee, Minjae; Yang, Youngoo; Lee, Kang-Yoon
2018-01-01
In this paper, a high noise immunity, 28 × 16-channel finger touch sensing IC for an orthogonal frequency division multiplexing (OFDM) touch sensing scheme is presented. In order to increase the signal-to-noise ratio (SNR), the OFDM sensing scheme is proposed. The transmitter (TX) transmits the orthogonal signal to each channels of the panel. The receiver (RX) detects the magnitude of the orthogonal frequency to be transmitted from the TX. Due to the orthogonal characteristics, it is robust to narrowband interference and noise. Therefore, the SNR can be improved. In order to reduce the noise effect of low frequencies, a mixer and high-pass filter are proposed as well. After the noise is filtered, the touch SNR attained is 60 dB, from 20 dB before the noise is filtered. The advantage of the proposed OFDM sensing scheme is its ability to detect channels of the panel simultaneously with the use of multiple carriers. To satisfy the linearity of the signal in the OFDM system, a high-linearity mixer and a rail-to-rail amplifier in the TX driver are designed. The proposed design is implemented in 90 nm CMOS process. The SNR is approximately 60 dB. The area is 13.6 mm2, and the power consumption is 62.4 mW. PMID:29883435
Longitudinal Relaxation of Ferromagnetic Grains
NASA Astrophysics Data System (ADS)
Würger, Alois
1998-07-01
We study the activated longitudinal dynamics of a small single-domain magnet with uniaxial anisotropy, coupled to quantum noise. The smallest finite eigenvalue λ1 = γ0e-EB/kBT of the relaxation matrix is evaluated in a controlled approximation. For white noise we find γ0~T-1 at moderate temperatures and γ0 = const at very low T. Coupling to elastic waves leads to a prefactor that is linear in T or constant, depending on temperature. At very low T, the discreteness of the energy spectrum is crucial.
Investigating the two-moment characterisation of subcellular biochemical networks.
Ullah, Mukhtar; Wolkenhauer, Olaf
2009-10-07
While ordinary differential equations (ODEs) form the conceptual framework for modelling many cellular processes, specific situations demand stochastic models to capture the influence of noise. The most common formulation of stochastic models for biochemical networks is the chemical master equation (CME). While stochastic simulations are a practical way to realise the CME, analytical approximations offer more insight into the influence of noise. Towards that end, the two-moment approximation (2MA) is a promising addition to the established analytical approaches including the chemical Langevin equation (CLE) and the related linear noise approximation (LNA). The 2MA approach directly tracks the mean and (co)variance which are coupled in general. This coupling is not obvious in CME and CLE and ignored by LNA and conventional ODE models. We extend previous derivations of 2MA by allowing (a) non-elementary reactions and (b) relative concentrations. Often, several elementary reactions are approximated by a single step. Furthermore, practical situations often require the use of relative concentrations. We investigate the applicability of the 2MA approach to the well-established fission yeast cell cycle model. Our analytical model reproduces the clustering of cycle times observed in experiments. This is explained through multiple resettings of M-phase promoting factor (MPF), caused by the coupling between mean and (co)variance, near the G2/M transition.
No-reference multiscale blur detection tool for content based image retrieval
NASA Astrophysics Data System (ADS)
Ezekiel, Soundararajan; Stocker, Russell; Harrity, Kyle; Alford, Mark; Ferris, David; Blasch, Erik; Gorniak, Mark
2014-06-01
In recent years, digital cameras have been widely used for image capturing. These devices are equipped in cell phones, laptops, tablets, webcams, etc. Image quality is an important component of digital image analysis. To assess image quality for these mobile products, a standard image is required as a reference image. In this case, Root Mean Square Error and Peak Signal to Noise Ratio can be used to measure the quality of the images. However, these methods are not possible if there is no reference image. In our approach, a discrete-wavelet transformation is applied to the blurred image, which decomposes into the approximate image and three detail sub-images, namely horizontal, vertical, and diagonal images. We then focus on noise-measuring the detail images and blur-measuring the approximate image to assess the image quality. We then compute noise mean and noise ratio from the detail images, and blur mean and blur ratio from the approximate image. The Multi-scale Blur Detection (MBD) metric provides both an assessment of the noise and blur content. These values are weighted based on a linear regression against full-reference y values. From these statistics, we can compare to normal useful image statistics for image quality without needing a reference image. We then test the validity of our obtained weights by R2 analysis as well as using them to estimate image quality of an image with a known quality measure. The result shows that our method provides acceptable results for images containing low to mid noise levels and blur content.
Li, Yongkai; Yi, Ming; Zou, Xiufen
2014-01-01
To gain insights into the mechanisms of cell fate decision in a noisy environment, the effects of intrinsic and extrinsic noises on cell fate are explored at the single cell level. Specifically, we theoretically define the impulse of Cln1/2 as an indication of cell fates. The strong dependence between the impulse of Cln1/2 and cell fates is exhibited. Based on the simulation results, we illustrate that increasing intrinsic fluctuations causes the parallel shift of the separation ratio of Whi5P but that increasing extrinsic fluctuations leads to the mixture of different cell fates. Our quantitative study also suggests that the strengths of intrinsic and extrinsic noises around an approximate linear model can ensure a high accuracy of cell fate selection. Furthermore, this study demonstrates that the selection of cell fates is an entropy-decreasing process. In addition, we reveal that cell fates are significantly correlated with the range of entropy decreases. PMID:25042292
Laboratory studies of scales for measuring helicopter noise
NASA Technical Reports Server (NTRS)
Ollerhead, J. B.
1982-01-01
The adequacy of the effective perceived noise level (EPNL) procedure for rating helicopter noise annoyance was investigated. Recordings of 89 helicopters and 30 fixed wing aircraft (CTOL) flyover sounds were rated with respect to annoyance by groups of approximately 40 subjects. The average annoyance scores were transformed to annoyance levels defined as the equally annoying sound levels of a fixed reference sound. The sound levels of the test sounds were measured on various scales, with and without corrections for duration, tones, and impulsiveness. On average, the helicopter sounds were judged equally annoying to CTOL sounds when their duration corrected levels are approximately 2 dB higher. Multiple regression analysis indicated that, provided the helicopter/CTOL difference of about 2 dB is taken into account, the particular linear combination of level, duration, and tone corrections inherent in EPNL is close to optimum. The results reveal no general requirement for special EPNL correction terms to penalize helicopter sounds which are particularly impulsive; impulsiveness causes spectral and temporal changes which themselves adequately amplify conventionally measured sound levels.
Akan, Zafer; Körpinar, Mehmet Ali; Tulgar, Metin
2011-06-01
Noise pollution is a common health problem for developing countries. Especially highways and airports lead to noise pollution in different levels and in many frequencies. In this study, we focused on the effect of noise pollution in airports. This work aimed measurements of noise pollution levels in Van Ferit Melen (VFM) airport and effect of noise pollution over the immunoglobulin A, G, and M changes among VFM airport workers in Turkey. It was seen that apron and terminal workers were exposed to high noise (>80 dB(A)) without any protective precautions. Noise-induced temporary threshold shifts and noise-induced permanent threshold shifts were detected between the apron workers (p < 0.001) and terminal workers (p < 0.005). IgA values of apron terminal and control group workers were approximately the same in the morning and increased in a linear manner during the day. This increase was statistically significant (p < 0.001). IgG and IgM values of apron, terminal, and control group workers were approximately same in the morning. Apron and terminal workers IgG and IgM levels were increased until noon and then decreased until evening as compare to control group, but these changes were not statically significant (p > 0.05). These findings suggested that the noise pollution in the VFM airport could lead to hearing loss and changes in blood serum immunoglobulin levels of airport workers. Blood serum immunoglobulin changes might be due to vibrational effects of noise pollution. Airport workers should apply protective precautions against effect of noise pollution in the VFM airport.
NASA Astrophysics Data System (ADS)
Louarroudi, E.; Pintelon, R.; Lataire, J.
2014-10-01
Time-periodic (TP) phenomena occurring, for instance, in wind turbines, helicopters, anisotropic shaft-bearing systems, and cardiovascular/respiratory systems, are often not addressed when classical frequency response function (FRF) measurements are performed. As the traditional FRF concept is based on the linear time-invariant (LTI) system theory, it is only approximately valid for systems with varying dynamics. Accordingly, the quantification of any deviation from this ideal LTI framework is more than welcome. The “measure of deviation” allows us to define the notion of the best LTI (BLTI) approximation, which yields the best - in mean square sense - LTI description of a linear time-periodic LTP system. By taking into consideration the TP effects, it is shown in this paper that the variability of the BLTI measurement can be reduced significantly compared with that of classical FRF estimators. From a single experiment, the proposed identification methods can handle (non-)linear time-periodic [(N)LTP] systems in open-loop with a quantification of (i) the noise and/or the NL distortions, (ii) the TP distortions and (iii) the transient (leakage) errors. Besides, a geometrical interpretation of the BLTI approximation is provided, leading to a framework called vector FRF analysis. The theory presented is supported by numerical simulations as well as real measurements mimicking the well-known mechanical Mathieu oscillator.
NASA Astrophysics Data System (ADS)
Waubke, Holger; Kasess, Christian H.
2016-11-01
Devices that emit structure-borne sound are commonly decoupled by elastic components to shield the environment from acoustical noise and vibrations. The elastic elements often have a hysteretic behavior that is typically neglected. In order to take hysteretic behavior into account, Bouc developed a differential equation for such materials, especially joints made of rubber or equipped with dampers. In this work, the Bouc model is solved by means of the Gaussian closure technique based on the Kolmogorov equation. Kolmogorov developed a method to derive probability density functions for arbitrary explicit first-order vector differential equations under white noise excitation using a partial differential equation of a multivariate conditional probability distribution. Up to now no analytical solution of the Kolmogorov equation in conjunction with the Bouc model exists. Therefore a wide range of approximate solutions, especially the statistical linearization, were developed. Using the Gaussian closure technique that is an approximation to the Kolmogorov equation assuming a multivariate Gaussian distribution an analytic solution is derived in this paper for the Bouc model. For the stationary case the two methods yield equivalent results, however, in contrast to statistical linearization the presented solution allows to calculate the transient behavior explicitly. Further, stationary case leads to an implicit set of equations that can be solved iteratively with a small number of iterations and without instabilities for specific parameter sets.
González-López, Antonio; Vera-Sánchez, Juan Antonio; Ruiz-Morales, Carmen
2016-05-01
This note studies the statistical relationships between color channels in radiochromic film readings with flatbed scanners. The same relationships are studied for noise. Finally, their implications for multichannel film dosimetry are discussed. Radiochromic films exposed to wedged fields of 6 MV energy were read in a flatbed scanner. The joint histograms of pairs of color channels were used to obtain the joint and conditional probability density functions between channels. Then, the conditional expectations and variances of one channel given another channel were obtained. Noise was extracted from film readings by means of a multiresolution analysis. Two different dose ranges were analyzed, the first one ranging from 112 to 473 cGy and the second one from 52 to 1290 cGy. For the smallest dose range, the conditional expectations of one channel given another channel can be approximated by linear functions, while the conditional variances are fairly constant. The slopes of the linear relationships between channels can be used to simplify the expression that estimates the dose by means of the multichannel method. The slopes of the linear relationships between each channel and the red one can also be interpreted as weights in the final contribution to dose estimation. However, for the largest dose range, the conditional expectations of one channel given another channel are no longer linear functions. Finally, noises in different channels were found to correlate weakly. Signals present in different channels of radiochromic film readings show a strong statistical dependence. By contrast, noise correlates weakly between channels. For the smallest dose range analyzed, the linear behavior between the conditional expectation of one channel given another channel can be used to simplify calculations in multichannel film dosimetry.
Ramaswamy, Rajesh; Sbalzarini, Ivo F; González-Segredo, Nélido
2011-01-28
Stochastic effects from correlated noise non-trivially modulate the kinetics of non-linear chemical reaction networks. This is especially important in systems where reactions are confined to small volumes and reactants are delivered in bursts. We characterise how the two noise sources confinement and burst modulate the relaxation kinetics of a non-linear reaction network around a non-equilibrium steady state. We find that the lifetimes of species change with burst input and confinement. Confinement increases the lifetimes of all species that are involved in any non-linear reaction as a reactant. Burst monotonically increases or decreases lifetimes. Competition between burst-induced and confinement-induced modulation may hence lead to a non-monotonic modulation. We quantify lifetime as the integral of the time autocorrelation function (ACF) of concentration fluctuations around a non-equilibrium steady state of the reaction network. Furthermore, we look at the first and second derivatives of the ACF, each of which is affected in opposite ways by burst and confinement. This allows discriminating between these two noise sources. We analytically derive the ACF from the linear Fokker-Planck approximation of the chemical master equation in order to establish a baseline for the burst-induced modulation at low confinement. Effects of higher confinement are then studied using a partial-propensity stochastic simulation algorithm. The results presented here may help understand the mechanisms that deviate stochastic kinetics from its deterministic counterpart. In addition, they may be instrumental when using fluorescence-lifetime imaging microscopy (FLIM) or fluorescence-correlation spectroscopy (FCS) to measure confinement and burst in systems with known reaction rates, or, alternatively, to correct for the effects of confinement and burst when experimentally measuring reaction rates.
DOE Office of Scientific and Technical Information (OSTI.GOV)
González-López, Antonio, E-mail: antonio.gonzalez7@carm.es; Vera-Sánchez, Juan Antonio; Ruiz-Morales, Carmen
Purpose: This note studies the statistical relationships between color channels in radiochromic film readings with flatbed scanners. The same relationships are studied for noise. Finally, their implications for multichannel film dosimetry are discussed. Methods: Radiochromic films exposed to wedged fields of 6 MV energy were read in a flatbed scanner. The joint histograms of pairs of color channels were used to obtain the joint and conditional probability density functions between channels. Then, the conditional expectations and variances of one channel given another channel were obtained. Noise was extracted from film readings by means of a multiresolution analysis. Two different dosemore » ranges were analyzed, the first one ranging from 112 to 473 cGy and the second one from 52 to 1290 cGy. Results: For the smallest dose range, the conditional expectations of one channel given another channel can be approximated by linear functions, while the conditional variances are fairly constant. The slopes of the linear relationships between channels can be used to simplify the expression that estimates the dose by means of the multichannel method. The slopes of the linear relationships between each channel and the red one can also be interpreted as weights in the final contribution to dose estimation. However, for the largest dose range, the conditional expectations of one channel given another channel are no longer linear functions. Finally, noises in different channels were found to correlate weakly. Conclusions: Signals present in different channels of radiochromic film readings show a strong statistical dependence. By contrast, noise correlates weakly between channels. For the smallest dose range analyzed, the linear behavior between the conditional expectation of one channel given another channel can be used to simplify calculations in multichannel film dosimetry.« less
NASA Technical Reports Server (NTRS)
Banks, H. T.; Silcox, R. J.; Keeling, S. L.; Wang, C.
1989-01-01
A unified treatment of the linear quadratic tracking (LQT) problem, in which a control system's dynamics are modeled by a linear evolution equation with a nonhomogeneous component that is linearly dependent on the control function u, is presented; the treatment proceeds from the theoretical formulation to a numerical approximation framework. Attention is given to two categories of LQT problems in an infinite time interval: the finite energy and the finite average energy. The behavior of the optimal solution for finite time-interval problems as the length of the interval tends to infinity is discussed. Also presented are the formulations and properties of LQT problems in a finite time interval.
NASA Astrophysics Data System (ADS)
Krysko, V. A.; Awrejcewicz, J.; Krylova, E. Yu; Papkova, I. V.; Krysko, A. V.
2018-06-01
Parametric non-linear vibrations of flexible cylindrical panels subjected to additive white noise are studied. The governing Marguerre equations are investigated using the finite difference method (FDM) of the second-order accuracy and the Runge-Kutta method. The considered mechanical structural member is treated as a system of many/infinite number of degrees of freedom (DoF). The dependence of chaotic vibrations on the number of DoFs is investigated. Reliability of results is guaranteed by comparing the results obtained using two qualitatively different methods to reduce the problem of PDEs (partial differential equations) to ODEs (ordinary differential equations), i.e. the Faedo-Galerkin method in higher approximations and the 4th and 6th order FDM. The Cauchy problem obtained by the FDM is eventually solved using the 4th-order Runge-Kutta methods. The numerical experiment yielded, for a certain set of parameters, the non-symmetric vibration modes/forms with and without white noise. In particular, it has been illustrated and discussed that action of white noise on chaotic vibrations implies quasi-periodicity, whereas the previously non-symmetric vibration modes are closer to symmetric ones.
Approximation methods for control of structural acoustics models with piezoceramic actuators
NASA Astrophysics Data System (ADS)
Banks, H. T.; Fang, W.; Silcox, R. J.; Smith, R. C.
1993-01-01
The active control of acoustic pressure in a 2-D cavity with a flexible boundary (a beam) is considered. Specifically, this control is implemented via piezoceramic patches on the beam which produces pure bending moments. The incorporation of the feedback control in this manner leads to a system with an unbounded input term. Approximation methods in this manner leads to a system with an unbounded input term. Approximation methods in this manner leads to a system with an unbounded input team. Approximation methods in the context of linear quadratic regulator (LQR) state space control formulation are discussed and numerical results demonstrating the effectiveness of this approach in computing feedback controls for noise reduction are presented.
Dynamic properties of micro-magnetic noise in soft ferromagnetic materials
NASA Astrophysics Data System (ADS)
Stupakov, A.; Perevertov, A.
2018-06-01
Dynamic response of magnetic hysteresis, magnetic Barkhausen noise and magneto-acoustic emission in a soft ribbon and electrical steels was studied comprehensively. The measurements were performed under controllable magnetization conditions: sinusoidal/triangular waveforms of the magnetic induction and a triangular waveform of the magnetic field. Magnetizing frequency was varied in a wide range: fmag = 0.5 - 500 and 0.5-100 Hz for the ribbon and the electrical steels, respectively. Magnetization amplitude was fixed on a near-saturation level Hmax ≃ 100 A/m. Barkhausen noise signal was detected by a sample-wrapping/surface-mounted coil and differently filtered. It was found that intensity of the Barkhausen noise rises approximately as a square root function of the magnetizing frequency. Whereas, level of the magneto-acoustic emission follows the hysteresis loss trend with an additional linear term (classical loss component).
NASA Technical Reports Server (NTRS)
Hanson, D. B.
1991-01-01
A unified theory for the aerodynamics and noise of advanced turboprops are presented. Aerodynamic topics include calculation of performance, blade load distribution, and non-uniform wake flow fields. Blade loading can be steady or unsteady due to fixed distortion, counter-rotating wakes, or blade vibration. The aerodynamic theory is based on the pressure potential method and is therefore basically linear. However, nonlinear effects associated with finite axial induction and blade vortex flow are included via approximate methods. Acoustic topics include radiation of noise caused by blade thickness, steady loading (including vortex lift), and unsteady loading. Shielding of the fuselage by its boundary layer and the wing are treated in separate analyses that are compatible but not integrated with the aeroacoustic theory for rotating blades.
Marques do Carmo, Diego; Costa, Márcio Holsbach
2018-04-01
This work presents an online approximation method for the multichannel Wiener filter (MWF) noise reduction technique with preservation of the noise interaural level difference (ILD) for binaural hearing-aids. The steepest descent method is applied to a previously proposed MWF-ILD cost function to both approximate the optimal linear estimator of the desired speech and keep the subjective perception of the original acoustic scenario. The computational cost of the resulting algorithm is estimated in terms of multiply and accumulate operations, whose number can be controlled by setting the number of iterations at each time frame. Simulation results for the particular case of one speech and one-directional noise source show that the proposed method increases the signal-to-noise ratio SNR of the originally acquired speech by up to 16.9 dB in the assessed scenarios. As compared to the online implementation of the conventional MWF technique, the proposed technique provides a reduction of up to 7 dB in the noise ILD error at the price of a reduction of up 3 dB in the output SNR. Subjective experiments with volunteers complement these objective measures with psychoacoustic results, which corroborate the expected spatial preservation of the original acoustic scenario. The proposed method allows practical online implementation of the MWF-ILD noise reduction technique under constrained computational resources. Predicted SNR improvements from 12 dB to 16.9 dB can be obtained in application-specific integrated circuits for hearing-aids and state-of-the-art digital signal processors. Copyright © 2018 Elsevier Ltd. All rights reserved.
Synchronization of mobile chaotic oscillator networks
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fujiwara, Naoya, E-mail: fujiwara@csis.u-tokyo.ac.jp; Kurths, Jürgen; Díaz-Guilera, Albert
We study synchronization of systems in which agents holding chaotic oscillators move in a two-dimensional plane and interact with nearby ones forming a time dependent network. Due to the uncertainty in observing other agents' states, we assume that the interaction contains a certain amount of noise that turns out to be relevant for chaotic dynamics. We find that a synchronization transition takes place by changing a control parameter. But this transition depends on the relative dynamic scale of motion and interaction. When the topology change is slow, we observe an intermittent switching between laminar and burst states close to themore » transition due to small noise. This novel type of synchronization transition and intermittency can happen even when complete synchronization is linearly stable in the absence of noise. We show that the linear stability of the synchronized state is not a sufficient condition for its stability due to strong fluctuations of the transverse Lyapunov exponent associated with a slow network topology change. Since this effect can be observed within the linearized dynamics, we can expect such an effect in the temporal networks with noisy chaotic oscillators, irrespective of the details of the oscillator dynamics. When the topology change is fast, a linearized approximation describes well the dynamics towards synchrony. These results imply that the fluctuations of the finite-time transverse Lyapunov exponent should also be taken into account to estimate synchronization of the mobile contact networks.« less
NASA Astrophysics Data System (ADS)
Belinskiĭ, A. V.
1992-09-01
An investigation is made of the evolution of quantum fluctuations of a fundamental soliton in the course of its propagation in a nonlinear fiber waveguide characterized by losses and compensated by amplification. Simple relationships are obtained for the amplitude and phase noise, quantum uncertainty of the position and momentum, and also fluctuations of the quadrature components of the radiation field. Numerical estimates are obtained. It is shown that loss-compensating amplification is unnecessary for efficient formation of squeezed states of a soliton.
Sinc-Galerkin estimation of diffusivity in parabolic problems
NASA Technical Reports Server (NTRS)
Smith, Ralph C.; Bowers, Kenneth L.
1991-01-01
A fully Sinc-Galerkin method for the numerical recovery of spatially varying diffusion coefficients in linear partial differential equations is presented. Because the parameter recovery problems are inherently ill-posed, an output error criterion in conjunction with Tikhonov regularization is used to formulate them as infinite-dimensional minimization problems. The forward problems are discretized with a sinc basis in both the spatial and temporal domains thus yielding an approximate solution which displays an exponential convergence rate and is valid on the infinite time interval. The minimization problems are then solved via a quasi-Newton/trust region algorithm. The L-curve technique for determining an approximate value of the regularization parameter is briefly discussed, and numerical examples are given which show the applicability of the method both for problems with noise-free data as well as for those whose data contains white noise.
Linearizing an intermodulation radar transmitter by filtering switched tones
NASA Astrophysics Data System (ADS)
Mazzaro, Gregory J.; Sherbondy, Andrew J.; Ranney, Kenneth I.; Sherbondy, Kelly D.; Martone, Anthony F.
2017-05-01
For nonlinear radar, the transmit power required to measure a detectable response from a target is relatively high, and generating that high power is achieved at the cost of linearity. This paper applies the distortion mitigation technique Linearization by Time-Multiplexed Spectrum (LITMUS) to intermodulation radar, a type of nonlinear radar which receives spectral content produced by the mixing of multiple frequencies at a nonlinear target. By implementing LITMUS, an experimental detection system for an intermodulation radar achieves a signal-to-noise ratio up to 20 dB for a total transmit power of approximately 80 mW and nonlinear targets placed at a standoff distance of 2 meters.
Estimation for the Linear Model With Uncertain Covariance Matrices
NASA Astrophysics Data System (ADS)
Zachariah, Dave; Shariati, Nafiseh; Bengtsson, Mats; Jansson, Magnus; Chatterjee, Saikat
2014-03-01
We derive a maximum a posteriori estimator for the linear observation model, where the signal and noise covariance matrices are both uncertain. The uncertainties are treated probabilistically by modeling the covariance matrices with prior inverse-Wishart distributions. The nonconvex problem of jointly estimating the signal of interest and the covariance matrices is tackled by a computationally efficient fixed-point iteration as well as an approximate variational Bayes solution. The statistical performance of estimators is compared numerically to state-of-the-art estimators from the literature and shown to perform favorably.
Approximation methods for control of acoustic/structure models with piezoceramic actuators
NASA Technical Reports Server (NTRS)
Banks, H. T.; Fang, W.; Silcox, R. J.; Smith, R. C.
1991-01-01
The active control of acoustic pressure in a 2-D cavity with a flexible boundary (a beam) is considered. Specifically, this control is implemented via piezoceramic patches on the beam which produces pure bending moments. The incorporation of the feedback control in this manner leads to a system with an unbounded input term. Approximation methods in this manner leads to a system with an unbounded input term. Approximation methods in the context of linear quadratic regulator (LQR) state space control formulation are discussed and numerical results demonstrating the effectiveness of this approach in computing feedback controls for noise reduction are presented.
Detection of Natural Fractures from Observed Surface Seismic Data Based on a Linear-Slip Model
NASA Astrophysics Data System (ADS)
Chen, Huaizhen; Zhang, Guangzhi
2018-03-01
Natural fractures play an important role in migration of hydrocarbon fluids. Based on a rock physics effective model, the linear-slip model, which defines fracture parameters (fracture compliances) for quantitatively characterizing the effects of fractures on rock total compliance, we propose a method to detect natural fractures from observed seismic data via inversion for the fracture compliances. We first derive an approximate PP-wave reflection coefficient in terms of fracture compliances. Using the approximate reflection coefficient, we derive azimuthal elastic impedance as a function of fracture compliances. An inversion method to estimate fracture compliances from seismic data is presented based on a Bayesian framework and azimuthal elastic impedance, which is implemented in a two-step procedure: a least-squares inversion for azimuthal elastic impedance and an iterative inversion for fracture compliances. We apply the inversion method to synthetic and real data to verify its stability and reasonability. Synthetic tests confirm that the method can make a stable estimation of fracture compliances in the case of seismic data containing a moderate signal-to-noise ratio for Gaussian noise, and the test on real data reveals that reasonable fracture compliances are obtained using the proposed method.
NASA Astrophysics Data System (ADS)
Casado-Pascual, Jesús; Denk, Claus; Gómez-Ordóñez, José; Morillo, Manuel; Hänggi, Peter
2003-03-01
In the context of the phenomenon of stochastic resonance (SR), we study the correlation function, the signal-to-noise ratio (SNR), and the ratio of output over input SNR, i.e., the gain, which is associated to the nonlinear response of a bistable system driven by time-periodic forces and white Gaussian noise. These quantifiers for SR are evaluated using the techniques of linear response theory (LRT) beyond the usually employed two-mode approximation scheme. We analytically demonstrate within such an extended LRT description that the gain can indeed not exceed unity. We implement an efficient algorithm, based on work by Greenside and Helfand (detailed in the Appendix), to integrate the driven Langevin equation over a wide range of parameter values. The predictions of LRT are carefully tested against the results obtained from numerical solutions of the corresponding Langevin equation over a wide range of parameter values. We further present an accurate procedure to evaluate the distinct contributions of the coherent and incoherent parts of the correlation function to the SNR and the gain. As a main result we show for subthreshold driving that both the correlation function and the SNR can deviate substantially from the predictions of LRT and yet the gain can be either larger or smaller than unity. In particular, we find that the gain can exceed unity in the strongly nonlinear regime which is characterized by weak noise and very slow multifrequency subthreshold input signals with a small duty cycle. This latter result is in agreement with recent analog simulation results by Gingl et al. [ICNF 2001, edited by G. Bosman (World Scientific, Singapore, 2002), pp. 545 548; Fluct. Noise Lett. 1, L181 (2001)].
Active control of acoustic pressure fields using smart material technologies
NASA Technical Reports Server (NTRS)
Banks, H. T.; Smith, R. C.
1993-01-01
An overview describing the use of piezoceramic patches in reducing noise in a structural acoustics setting is presented. The passive and active contributions due to patches which are bonded to an Euler-Bernoulli beam or thin shell are briefly discussed and the results are incorporated into a 2-D structural acoustics model. In this model, an exterior noise source causes structural vibrations which in turn lead to interior noise as a result of nonlinear fluid/structure coupling mechanism. Interior sound pressure levels are reduced via patches bonded to the flexible boundary (a beam in this case) which generate pure bending moments when an out-of-phase voltage is applied. Well-posedness results for the infinite dimensional system are discussed and a Galerkin scheme for approximating the system dynamics is outlined. Control is implemented by using linear quadratic regulator (LQR) optimal control theory to calculate gains for the linearized system and then feeding these gains back into the nonlinear system of interest. The effectiveness of this strategy for this problem is illustrated in an example.
Probabilistic density function method for nonlinear dynamical systems driven by colored noise
DOE Office of Scientific and Technical Information (OSTI.GOV)
Barajas-Solano, David A.; Tartakovsky, Alexandre M.
2016-05-01
We present a probability density function (PDF) method for a system of nonlinear stochastic ordinary differential equations driven by colored noise. The method provides an integro-differential equation for the temporal evolution of the joint PDF of the system's state, which we close by means of a modified Large-Eddy-Diffusivity-type closure. Additionally, we introduce the generalized local linearization (LL) approximation for deriving a computable PDF equation in the form of the second-order partial differential equation (PDE). We demonstrate the proposed closure and localization accurately describe the dynamics of the PDF in phase space for systems driven by noise with arbitrary auto-correlation time.more » We apply the proposed PDF method to the analysis of a set of Kramers equations driven by exponentially auto-correlated Gaussian colored noise to study the dynamics and stability of a power grid.« less
Analytical approximations to the Hotelling trace for digital x-ray detectors
NASA Astrophysics Data System (ADS)
Clarkson, Eric; Pineda, Angel R.; Barrett, Harrison H.
2001-06-01
The Hotelling trace is the signal-to-noise ratio for the ideal linear observer in a detection task. We provide an analytical approximation for this figure of merit when the signal is known exactly and the background is generated by a stationary random process, and the imaging system is an ideal digital x-ray detector. This approximation is based on assuming that the detector is infinite in extent. We test this approximation for finite-size detectors by comparing it to exact calculations using matrix inversion of the data covariance matrix. After verifying the validity of the approximation under a variety of circumstances, we use it to generate plots of the Hotelling trace as a function of pairs of parameters of the system, the signal and the background.
Di, Guo-Qing; Lin, Qi-Li; Li, Zheng-Guang; Kang, Jian
2014-03-07
High-speed railway (HR, Electrified railway with service speed above 200 km/h.) noise and conventional railway (CR, Electrified railway with service speed under 200 km/h.) noise are different in both time and frequency domain. There is an urgent need to study the influence of HR noise and consequently, develop appropriate noise evaluation index and limits for the total railway noise including HR and CR noise. Based on binaural recording of HR and CR noises in a approximate semi-free field, noise annoyance and activity disturbance induced by maximal train pass-by events in China were investigated through laboratory subjective evaluation. 80 students within recruited 102 students, 40 males and 40 females, 23.9 ± 2.1 years old, were finally selected as the subjects. After receiving noise stimulus via headphone of a binaural audio playback system, subjects were asked to express the annoyance or activity disturbance due to railway noise at a 0-100 numerical scale. The results show that with the same annoyance rating (A) or activity disturbance rating (D), the A-weighted equivalent sound pressure level (LAeq) of CR noise is approximately 7 dB higher than that of HR noise. Linear regression analysis between some acoustical parameters and A (or D) suggests that the coefficient of determination (R2) is higher with the instantaneous fast A-weighted sound pressure level (LAFmax) than that with LAeq. A combined acoustical parameter, LHC = 1.74LAFmax + 0.008LAFmax(Lp-LAeq), where Lp is the sound pressure level, was derived consequently, which could better evaluate the total railway noise, including HR and CR noise. More importantly, with a given LHC, the noise annoyance of HR and CR noise is the same. Among various acoustical parameters including LHC and LAeq, A and D have the highest correlation with LHC. LHC has been proved to be an appropriate index to evaluate the total railway noise, including both HR and CR. However, it should be pointed out that this study provides suggestive evidence, rather than a final proof. Further study is expected to elucidate conclusions above by additional measurements.
Kargar, Soudabeh; Borisch, Eric A; Froemming, Adam T; Kawashima, Akira; Mynderse, Lance A; Stinson, Eric G; Trzasko, Joshua D; Riederer, Stephen J
2018-05-01
To describe an efficient numerical optimization technique using non-linear least squares to estimate perfusion parameters for the Tofts and extended Tofts models from dynamic contrast enhanced (DCE) MRI data and apply the technique to prostate cancer. Parameters were estimated by fitting the two Tofts-based perfusion models to the acquired data via non-linear least squares. We apply Variable Projection (VP) to convert the fitting problem from a multi-dimensional to a one-dimensional line search to improve computational efficiency and robustness. Using simulation and DCE-MRI studies in twenty patients with suspected prostate cancer, the VP-based solver was compared against the traditional Levenberg-Marquardt (LM) strategy for accuracy, noise amplification, robustness to converge, and computation time. The simulation demonstrated that VP and LM were both accurate in that the medians closely matched assumed values across typical signal to noise ratio (SNR) levels for both Tofts models. VP and LM showed similar noise sensitivity. Studies using the patient data showed that the VP method reliably converged and matched results from LM with approximate 3× and 2× reductions in computation time for the standard (two-parameter) and extended (three-parameter) Tofts models. While LM failed to converge in 14% of the patient data, VP converged in the ideal 100%. The VP-based method for non-linear least squares estimation of perfusion parameters for prostate MRI is equivalent in accuracy and robustness to noise, while being more reliably (100%) convergent and computationally about 3× (TM) and 2× (ETM) faster than the LM-based method. Copyright © 2017 Elsevier Inc. All rights reserved.
Noise generated by convected gusts interacting with swept airfoil cascades
NASA Astrophysics Data System (ADS)
Envia, E.; Kerschen, E. J.
1986-07-01
An analysis is developed for the noise generated by the interaction of a rotor viscous wake with a cascade of swept stator vanes. The stator vanes span a channel formed by infinite parallel walls and containing a subsonic mean flow. High frequency interactions, for which the noise generation is concentrated at the vane leading edge, are considered. The analysis utilizes a superposition of the solution to the isolated stator vane problem, presented in an earlier paper, to develop an approximate solution to the cascade problem. The rotor wake model includes the features of wake circumferential lean and a linear spanwise variation of the magnitude of the wake deficit velocity. Calculations are presented which show that, for rotor wakes with moderate circumferential lean, stator sweep produces substantial reductions in noise level. The vane sweep must be oriented to enhance the phase lags along the vane leading edge produced by wake lean. The noise levels are found to be fairly insensitive to spanwise variations in the wake deficit.
Predicting financial market crashes using ghost singularities.
Smug, Damian; Ashwin, Peter; Sornette, Didier
2018-01-01
We analyse the behaviour of a non-linear model of coupled stock and bond prices exhibiting periodically collapsing bubbles. By using the formalism of dynamical system theory, we explain what drives the bubbles and how foreshocks or aftershocks are generated. A dynamical phase space representation of that system coupled with standard multiplicative noise rationalises the log-periodic power law singularity pattern documented in many historical financial bubbles. The notion of 'ghosts of finite-time singularities' is introduced and used to estimate the end of an evolving bubble, using finite-time singularities of an approximate normal form near the bifurcation point. We test the forecasting skill of this method on different stochastic price realisations and compare with Monte Carlo simulations of the full system. Remarkably, the approximate normal form is significantly more precise and less biased. Moreover, the method of ghosts of singularities is less sensitive to the noise realisation, thus providing more robust forecasts.
Predicting financial market crashes using ghost singularities
2018-01-01
We analyse the behaviour of a non-linear model of coupled stock and bond prices exhibiting periodically collapsing bubbles. By using the formalism of dynamical system theory, we explain what drives the bubbles and how foreshocks or aftershocks are generated. A dynamical phase space representation of that system coupled with standard multiplicative noise rationalises the log-periodic power law singularity pattern documented in many historical financial bubbles. The notion of ‘ghosts of finite-time singularities’ is introduced and used to estimate the end of an evolving bubble, using finite-time singularities of an approximate normal form near the bifurcation point. We test the forecasting skill of this method on different stochastic price realisations and compare with Monte Carlo simulations of the full system. Remarkably, the approximate normal form is significantly more precise and less biased. Moreover, the method of ghosts of singularities is less sensitive to the noise realisation, thus providing more robust forecasts. PMID:29596485
On optimal infinite impulse response edge detection filters
NASA Technical Reports Server (NTRS)
Sarkar, Sudeep; Boyer, Kim L.
1991-01-01
The authors outline the design of an optimal, computationally efficient, infinite impulse response edge detection filter. The optimal filter is computed based on Canny's high signal to noise ratio, good localization criteria, and a criterion on the spurious response of the filter to noise. An expression for the width of the filter, which is appropriate for infinite-length filters, is incorporated directly in the expression for spurious responses. The three criteria are maximized using the variational method and nonlinear constrained optimization. The optimal filter parameters are tabulated for various values of the filter performance criteria. A complete methodology for implementing the optimal filter using approximating recursive digital filtering is presented. The approximating recursive digital filter is separable into two linear filters operating in two orthogonal directions. The implementation is very simple and computationally efficient, has a constant time of execution for different sizes of the operator, and is readily amenable to real-time hardware implementation.
A Gaussian measure of quantum phase noise
NASA Technical Reports Server (NTRS)
Schleich, Wolfgang P.; Dowling, Jonathan P.
1992-01-01
We study the width of the semiclassical phase distribution of a quantum state in its dependence on the average number of photons (m) in this state. As a measure of phase noise, we choose the width, delta phi, of the best Gaussian approximation to the dominant peak of this probability curve. For a coherent state, this width decreases with the square root of (m), whereas for a truncated phase state it decreases linearly with increasing (m). For an optimal phase state, delta phi decreases exponentially but so does the area caught underneath the peak: all the probability is stored in the broad wings of the distribution.
Noise and linearity optimization methods for a 1.9GHz low noise amplifier.
Guo, Wei; Huang, Da-Quan
2003-01-01
Noise and linearity performances are critical characteristics for radio frequency integrated circuits (RFICs), especially for low noise amplifiers (LNAs). In this paper, a detailed analysis of noise and linearity for the cascode architecture, a widely used circuit structure in LNA designs, is presented. The noise and the linearity improvement techniques for cascode structures are also developed and have been proven by computer simulating experiments. Theoretical analysis and simulation results showed that, for cascode structure LNAs, the first metallic oxide semiconductor field effect transistor (MOSFET) dominates the noise performance of the LNA, while the second MOSFET contributes more to the linearity. A conclusion is thus obtained that the first and second MOSFET of the LNA can be designed to optimize the noise performance and the linearity performance separately, without trade-offs. The 1.9GHz Complementary Metal-Oxide-Semiconductor (CMOS) LNA simulation results are also given as an application of the developed theory.
NASA Astrophysics Data System (ADS)
Thomas, Philipp; Straube, Arthur V.; Grima, Ramon
2011-11-01
It is commonly believed that, whenever timescale separation holds, the predictions of reduced chemical master equations obtained using the stochastic quasi-steady-state approximation are in very good agreement with the predictions of the full master equations. We use the linear noise approximation to obtain a simple formula for the relative error between the predictions of the two master equations for the Michaelis-Menten reaction with substrate input. The reduced approach is predicted to overestimate the variance of the substrate concentration fluctuations by as much as 30%. The theoretical results are validated by stochastic simulations using experimental parameter values for enzymes involved in proteolysis, gluconeogenesis, and fermentation.
A quantum extended Kalman filter
NASA Astrophysics Data System (ADS)
Emzir, Muhammad F.; Woolley, Matthew J.; Petersen, Ian R.
2017-06-01
In quantum physics, a stochastic master equation (SME) estimates the state (density operator) of a quantum system in the Schrödinger picture based on a record of measurements made on the system. In the Heisenberg picture, the SME is a quantum filter. For a linear quantum system subject to linear measurements and Gaussian noise, the dynamics may be described by quantum stochastic differential equations (QSDEs), also known as quantum Langevin equations, and the quantum filter reduces to a so-called quantum Kalman filter. In this article, we introduce a quantum extended Kalman filter (quantum EKF), which applies a commutative approximation and a time-varying linearization to systems of nonlinear QSDEs. We will show that there are conditions under which a filter similar to a classical EKF can be implemented for quantum systems. The boundedness of estimation errors and the filtering problem with ‘state-dependent’ covariances for process and measurement noises are also discussed. We demonstrate the effectiveness of the quantum EKF by applying it to systems that involve multiple modes, nonlinear Hamiltonians, and simultaneous jump-diffusive measurements.
A State-Space Approach to Optimal Level-Crossing Prediction for Linear Gaussian Processes
NASA Technical Reports Server (NTRS)
Martin, Rodney Alexander
2009-01-01
In many complex engineered systems, the ability to give an alarm prior to impending critical events is of great importance. These critical events may have varying degrees of severity, and in fact they may occur during normal system operation. In this article, we investigate approximations to theoretically optimal methods of designing alarm systems for the prediction of level-crossings by a zero-mean stationary linear dynamic system driven by Gaussian noise. An optimal alarm system is designed to elicit the fewest false alarms for a fixed detection probability. This work introduces the use of Kalman filtering in tandem with the optimal level-crossing problem. It is shown that there is a negligible loss in overall accuracy when using approximations to the theoretically optimal predictor, at the advantage of greatly reduced computational complexity. I
IMNN: Information Maximizing Neural Networks
NASA Astrophysics Data System (ADS)
Charnock, Tom; Lavaux, Guilhem; Wandelt, Benjamin D.
2018-04-01
This software trains artificial neural networks to find non-linear functionals of data that maximize Fisher information: information maximizing neural networks (IMNNs). As compressing large data sets vastly simplifies both frequentist and Bayesian inference, important information may be inadvertently missed. Likelihood-free inference based on automatically derived IMNN summaries produces summaries that are good approximations to sufficient statistics. IMNNs are robustly capable of automatically finding optimal, non-linear summaries of the data even in cases where linear compression fails: inferring the variance of Gaussian signal in the presence of noise, inferring cosmological parameters from mock simulations of the Lyman-α forest in quasar spectra, and inferring frequency-domain parameters from LISA-like detections of gravitational waveforms. In this final case, the IMNN summary outperforms linear data compression by avoiding the introduction of spurious likelihood maxima.
Influence of vane sweep on rotor-stator interaction noise
NASA Technical Reports Server (NTRS)
Envia, Edmane; Kerschen, Edward J.
1990-01-01
The influence of vane sweep in rotor-stator interaction noise is investigated. In an analytical approach, the interaction of a convected gust representing the rotor viscous wake, with a cascade of cascade of finite span swept airfoils, representing the stator, is analyzed. The analysis is based on the solution of the exact linearized equations of motion. High frequency convected gusts for which noise generation is concentrated near the leading edge of airfoils is considered. In a preliminary study, the problem of an isolated finite span swept airfoil interacting with a convected gust is analyzed. Results indicate that sweep can substantially reduce the farfield noise levels for a single airfoil. Using the single airfoil model, an approximate solution to the problem of noise radiation from a cascade of finite span swept airfoils interacting with a convected gust is derived. A parametric study of noise generated by gust cascade interaction is carried out to assess the effectiveness of vane sweep in reducing rotor-stator interaction noise. The results show that sweep is beneficial in reducing noise levels. Rotor wake twist or circumferential lean substantially influences the effectiveness of vane sweep. The orientation of vane sweep must be chosen to enhance the natural phase lag caused by wake lean, in which case rather small sweep angles substantially reduce the noise levels.
Influence of vane sweep on rotor-stator interaction noise
NASA Astrophysics Data System (ADS)
Envia, Edmane; Kerschen, Edward J.
1990-12-01
The influence of vane sweep in rotor-stator interaction noise is investigated. In an analytical approach, the interaction of a convected gust representing the rotor viscous wake, with a cascade of cascade of finite span swept airfoils, representing the stator, is analyzed. The analysis is based on the solution of the exact linearized equations of motion. High frequency convected gusts for which noise generation is concentrated near the leading edge of airfoils is considered. In a preliminary study, the problem of an isolated finite span swept airfoil interacting with a convected gust is analyzed. Results indicate that sweep can substantially reduce the farfield noise levels for a single airfoil. Using the single airfoil model, an approximate solution to the problem of noise radiation from a cascade of finite span swept airfoils interacting with a convected gust is derived. A parametric study of noise generated by gust cascade interaction is carried out to assess the effectiveness of vane sweep in reducing rotor-stator interaction noise. The results show that sweep is beneficial in reducing noise levels. Rotor wake twist or circumferential lean substantially influences the effectiveness of vane sweep. The orientation of vane sweep must be chosen to enhance the natural phase lag caused by wake lean, in which case rather small sweep angles substantially reduce the noise levels.
Anomalous barrier escape: The roles of noise distribution and correlation.
Hu, Meng; Zhang, Jia-Ming; Bao, Jing-Dong
2017-05-28
We study numerically and analytically the barrier escape dynamics of a particle driven by an underlying correlated Lévy noise for a smooth metastable potential. A "quasi-monochrome-color" Lévy noise, i.e., the first-order derivative variable of a linear second-order differential equation subjected to a symmetric α-stable white Lévy noise, also called the harmonic velocity Lévy noise, is proposed. Note that the time-integral of the noise Green function of this kind is equal to zero. This leads to the existence of underlying negative time correlation and implies that a step in one direction is likely followed by a step in the other direction. By using the noise of this kind as a driving source, we discuss the competition between long flights and underlying negative correlations in the metastable dynamics. The quite rich behaviors in the parameter space including an optimum α for the stationary escape rate have been found. Remarkably, slow diffusion does not decrease the stationary rate while a negative correlation increases net escape. An approximate expression for the Lévy-Kramers rate is obtained to support the numerically observed dependencies.
Anomalous barrier escape: The roles of noise distribution and correlation
NASA Astrophysics Data System (ADS)
Hu, Meng; Zhang, Jia-Ming; Bao, Jing-Dong
2017-05-01
We study numerically and analytically the barrier escape dynamics of a particle driven by an underlying correlated Lévy noise for a smooth metastable potential. A "quasi-monochrome-color" Lévy noise, i.e., the first-order derivative variable of a linear second-order differential equation subjected to a symmetric α-stable white Lévy noise, also called the harmonic velocity Lévy noise, is proposed. Note that the time-integral of the noise Green function of this kind is equal to zero. This leads to the existence of underlying negative time correlation and implies that a step in one direction is likely followed by a step in the other direction. By using the noise of this kind as a driving source, we discuss the competition between long flights and underlying negative correlations in the metastable dynamics. The quite rich behaviors in the parameter space including an optimum α for the stationary escape rate have been found. Remarkably, slow diffusion does not decrease the stationary rate while a negative correlation increases net escape. An approximate expression for the Lévy-Kramers rate is obtained to support the numerically observed dependencies.
Visual Tracking Using 3D Data and Region-Based Active Contours
2016-09-28
adaptive control strategies which explicitly take uncertainty into account. Filtering methods ranging from the classical Kalman filters valid for...linear systems to the much more general particle filters also fit into this framework in a very natural manner. In particular, the particle filtering ...the number of samples required for accurate filtering increases with the dimension of the system noise. In our approach, we approximate curve
Prospects of second generation artificial intelligence tools in calibration of chemical sensors.
Braibanti, Antonio; Rao, Rupenaguntla Sambasiva; Ramam, Veluri Anantha; Rao, Gollapalli Nageswara; Rao, Vaddadi Venkata Panakala
2005-05-01
Multivariate data driven calibration models with neural networks (NNs) are developed for binary (Cu++ and Ca++) and quaternary (K+, Ca++, NO3- and Cl-) ion-selective electrode (ISE) data. The response profiles of ISEs with concentrations are non-linear and sub-Nernstian. This task represents function approximation of multi-variate, multi-response, correlated, non-linear data with unknown noise structure i.e. multi-component calibration/prediction in chemometric parlance. Radial distribution function (RBF) and Fuzzy-ARTMAP-NN models implemented in the software packages, TRAJAN and Professional II, are employed for the calibration. The optimum NN models reported are based on residuals in concentration space. Being a data driven information technology, NN does not require a model, prior- or posterior- distribution of data or noise structure. Missing information, spikes or newer trends in different concentration ranges can be modeled through novelty detection. Two simulated data sets generated from mathematical functions are modeled as a function of number of data points and network parameters like number of neurons and nearest neighbors. The success of RBF and Fuzzy-ARTMAP-NNs to develop adequate calibration models for experimental data and function approximation models for more complex simulated data sets ensures AI2 (artificial intelligence, 2nd generation) as a promising technology in quantitation.
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.
Using Kalman Filters to Reduce Noise from RFID Location System
Xavier, José; Reis, Luís Paulo; Petry, Marcelo
2014-01-01
Nowadays, there are many technologies that support location systems involving intrusive and nonintrusive equipment and also varying in terms of precision, range, and cost. However, the developers some time neglect the noise introduced by these systems, which prevents these systems from reaching their full potential. Focused on this problem, in this research work a comparison study between three different filters was performed in order to reduce the noise introduced by a location system based on RFID UWB technology with an associated error of approximately 18 cm. To achieve this goal, a set of experiments was devised and executed using a miniature train moving at constant velocity in a scenario with two distinct shapes—linear and oval. Also, this train was equipped with a varying number of active tags. The obtained results proved that the Kalman Filter achieved better results when compared to the other two filters. Also, this filter increases the performance of the location system by 15% and 12% for the linear and oval paths respectively, when using one tag. For a multiple tags and oval shape similar results were obtained (11–13% of improvement). PMID:24592186
NASA Technical Reports Server (NTRS)
Dahl, Milo D.; Hixon, Ray; Mankbadi, Reda R.
2003-01-01
An approximate technique is presented for the prediction of the large-scale turbulent structure sound source in a supersonic jet. A linearized Euler equations code is used to solve for the flow disturbances within and near a jet with a given mean flow. Assuming a normal mode composition for the wave-like disturbances, the linear radial profiles are used in an integration of the Navier-Stokes equations. This results in a set of ordinary differential equations representing the weakly nonlinear self-interactions of the modes along with their interaction with the mean flow. Solutions are then used to correct the amplitude of the disturbances that represent the source of large-scale turbulent structure sound in the jet.
Regularized wave equation migration for imaging and data reconstruction
NASA Astrophysics Data System (ADS)
Kaplan, Sam T.
The reflection seismic experiment results in a measurement (reflection seismic data) of the seismic wavefield. The linear Born approximation to the seismic wavefield leads to a forward modelling operator that we use to approximate reflection seismic data in terms of a scattering potential. We consider approximations to the scattering potential using two methods: the adjoint of the forward modelling operator (migration), and regularized numerical inversion using the forward and adjoint operators. We implement two parameterizations of the forward modelling and migration operators: source-receiver and shot-profile. For both parameterizations, we find requisite Green's function using the split-step approximation. We first develop the forward modelling operator, and then find the adjoint (migration) operator by recognizing a Fredholm integral equation of the first kind. The resulting numerical system is generally under-determined, requiring prior information to find a solution. In source-receiver migration, the parameterization of the scattering potential is understood using the migration imaging condition, and this encourages us to apply sparse prior models to the scattering potential. To that end, we use both a Cauchy prior and a mixed Cauchy-Gaussian prior, finding better resolved estimates of the scattering potential than are given by the adjoint. In shot-profile migration, the parameterization of the scattering potential has its redundancy in multiple active energy sources (i.e. shots). We find that a smallest model regularized inverse representation of the scattering potential gives a more resolved picture of the earth, as compared to the simpler adjoint representation. The shot-profile parameterization allows us to introduce a joint inversion to further improve the estimate of the scattering potential. Moreover, it allows us to introduce a novel data reconstruction algorithm so that limited data can be interpolated/extrapolated. The linearized operators are expensive, encouraging their parallel implementation. For the source-receiver parameterization of the scattering potential this parallelization is non-trivial. Seismic data is typically corrupted by various types of noise. Sparse coding can be used to suppress noise prior to migration. It is a method that stems from information theory and that we apply to noise suppression in seismic data.
2014-01-01
Background High-speed railway (HR, Electrified railway with service speed above 200 km/h.) noise and conventional railway (CR, Electrified railway with service speed under 200 km/h.) noise are different in both time and frequency domain. There is an urgent need to study the influence of HR noise and consequently, develop appropriate noise evaluation index and limits for the total railway noise including HR and CR noise. Methods Based on binaural recording of HR and CR noises in a approximate semi-free field, noise annoyance and activity disturbance induced by maximal train pass-by events in China were investigated through laboratory subjective evaluation. 80 students within recruited 102 students, 40 males and 40 females, 23.9 ± 2.1 years old, were finally selected as the subjects. After receiving noise stimulus via headphone of a binaural audio playback system, subjects were asked to express the annoyance or activity disturbance due to railway noise at a 0-100 numerical scale. Results The results show that with the same annoyance rating (A) or activity disturbance rating (D), the A-weighted equivalent sound pressure level (LAeq) of CR noise is approximately 7 dB higher than that of HR noise. Linear regression analysis between some acoustical parameters and A (or D) suggests that the coefficient of determination (R2) is higher with the instantaneous fast A-weighted sound pressure level (LAFmax) than that with LAeq. A combined acoustical parameter, LHC = 1.74LAFmax + 0.008LAFmax(Lp-LAeq), where Lp is the sound pressure level, was derived consequently, which could better evaluate the total railway noise, including HR and CR noise. More importantly, with a given LHC, the noise annoyance of HR and CR noise is the same. Conclusions Among various acoustical parameters including LHC and LAeq, A and D have the highest correlation with LHC. LHC has been proved to be an appropriate index to evaluate the total railway noise, including both HR and CR. However, it should be pointed out that this study provides suggestive evidence, rather than a final proof. Further study is expected to elucidate conclusions above by additional measurements. PMID:24602397
Modeling and Compensating Temperature-Dependent Non-Uniformity Noise in IR Microbolometer Cameras
Wolf, Alejandro; Pezoa, Jorge E.; Figueroa, Miguel
2016-01-01
Images rendered by uncooled microbolometer-based infrared (IR) cameras are severely degraded by the spatial non-uniformity (NU) noise. The NU noise imposes a fixed-pattern over the true images, and the intensity of the pattern changes with time due to the temperature instability of such cameras. In this paper, we present a novel model and a compensation algorithm for the spatial NU noise and its temperature-dependent variations. The model separates the NU noise into two components: a constant term, which corresponds to a set of NU parameters determining the spatial structure of the noise, and a dynamic term, which scales linearly with the fluctuations of the temperature surrounding the array of microbolometers. We use a black-body radiator and samples of the temperature surrounding the IR array to offline characterize both the constant and the temperature-dependent NU noise parameters. Next, the temperature-dependent variations are estimated online using both a spatially uniform Hammerstein-Wiener estimator and a pixelwise least mean squares (LMS) estimator. We compensate for the NU noise in IR images from two long-wave IR cameras. Results show an excellent NU correction performance and a root mean square error of less than 0.25 ∘C, when the array’s temperature varies by approximately 15 ∘C. PMID:27447637
Probabilistic inference using linear Gaussian importance sampling for hybrid Bayesian networks
NASA Astrophysics Data System (ADS)
Sun, Wei; Chang, K. C.
2005-05-01
Probabilistic inference for Bayesian networks is in general NP-hard using either exact algorithms or approximate methods. However, for very complex networks, only the approximate methods such as stochastic sampling could be used to provide a solution given any time constraint. There are several simulation methods currently available. They include logic sampling (the first proposed stochastic method for Bayesian networks, the likelihood weighting algorithm) the most commonly used simulation method because of its simplicity and efficiency, the Markov blanket scoring method, and the importance sampling algorithm. In this paper, we first briefly review and compare these available simulation methods, then we propose an improved importance sampling algorithm called linear Gaussian importance sampling algorithm for general hybrid model (LGIS). LGIS is aimed for hybrid Bayesian networks consisting of both discrete and continuous random variables with arbitrary distributions. It uses linear function and Gaussian additive noise to approximate the true conditional probability distribution for continuous variable given both its parents and evidence in a Bayesian network. One of the most important features of the newly developed method is that it can adaptively learn the optimal important function from the previous samples. We test the inference performance of LGIS using a 16-node linear Gaussian model and a 6-node general hybrid model. The performance comparison with other well-known methods such as Junction tree (JT) and likelihood weighting (LW) shows that LGIS-GHM is very promising.
Wind modeling and lateral control for automatic landing
NASA Technical Reports Server (NTRS)
Holley, W. E.; Bryson, A. E., Jr.
1975-01-01
For the purposes of aircraft control system design and analysis, the wind can be characterized by a mean component which varies with height and by turbulent components which are described by the von Karman correlation model. The aircraft aero-dynamic forces and moments depend linearly on uniform and gradient gust components obtained by averaging over the aircraft's length and span. The correlations of the averaged components are then approximated by the outputs of linear shaping filters forced by white noise. The resulting model of the crosswind shear and turbulence effects is used in the design of a lateral control system for the automatic landing of a DC-8 aircraft.
Optimal estimation of parameters and states in stochastic time-varying systems with time delay
NASA Astrophysics Data System (ADS)
Torkamani, Shahab; Butcher, Eric A.
2013-08-01
In this study estimation of parameters and states in stochastic linear and nonlinear delay differential systems with time-varying coefficients and constant delay is explored. The approach consists of first employing a continuous time approximation to approximate the stochastic delay differential equation with a set of stochastic ordinary differential equations. Then the problem of parameter estimation in the resulting stochastic differential system is represented as an optimal filtering problem using a state augmentation technique. By adapting the extended Kalman-Bucy filter to the resulting system, the unknown parameters of the time-delayed system are estimated from noise-corrupted, possibly incomplete measurements of the states.
Stochastic parameter estimation in nonlinear time-delayed vibratory systems with distributed delay
NASA Astrophysics Data System (ADS)
Torkamani, Shahab; Butcher, Eric A.
2013-07-01
The stochastic estimation of parameters and states in linear and nonlinear time-delayed vibratory systems with distributed delay is explored. The approach consists of first employing a continuous time approximation to approximate the delayed integro-differential system with a large set of ordinary differential equations having stochastic excitations. Then the problem of state and parameter estimation in the resulting stochastic ordinary differential system is represented as an optimal filtering problem using a state augmentation technique. By adapting the extended Kalman-Bucy filter to the augmented filtering problem, the unknown parameters of the time-delayed system are estimated from noise-corrupted, possibly incomplete measurements of the states. Similarly, the upper bound of the distributed delay can also be estimated by the proposed technique. As an illustrative example to a practical problem in vibrations, the parameter, delay upper bound, and state estimation from noise-corrupted measurements in a distributed force model widely used for modeling machine tool vibrations in the turning operation is investigated.
Linear Reconstruction of Non-Stationary Image Ensembles Incorporating Blur and Noise Models
1998-03-01
for phase distortions due to noise which leads to less deblurring as noise increases [41]. In contrast, the vector Wiener filter incorporates some a...AFIT/DS/ENG/98- 06 Linear Reconstruction of Non-Stationary Image Ensembles Incorporating Blur and Noise Models DISSERTATION Stephen D. Ford Captain...Dissertation 4. TITLE AND SUBTITLE 5. FUNDING NUMBERS LINEAR RECONSTRUCTION OF NON-STATIONARY IMAGE ENSEMBLES INCORPORATING BLUR AND NOISE MODELS 6. AUTHOR(S
Design and laboratory testing of a prototype linear temperature sensor
NASA Astrophysics Data System (ADS)
Dube, C. M.; Nielsen, C. M.
1982-07-01
This report discusses the basic theory, design, and laboratory testing of a prototype linear temperature sensor (or "line sensor'), which is an instrument for measuring internal waves in the ocean. The operating principle of the line sensor consists of measuring the average resistance change of a vertically suspended wire (or coil of wire) induced by the passage of an internal wave in a thermocline. The advantage of the line sensor over conventional internal wave measurement techniques is that it is insensitive to thermal finestructure which contaminates point sensor measurements, and its output is approximately linearly proportional to the internal wave displacement. An approximately one-half scale prototype line sensor module was teste in the laboratory. The line sensor signal was linearly related to the actual fluid displacement to within 10%. Furthermore, the absolute output was well predicted (within 25%) from the theoretical model and the sensor material properties alone. Comparisons of the line sensor and a point sensor in a wavefield with superimposed turbulence (finestructure) revealed negligible distortion in the line sensor signal, while the point sensor signal was swamped by "turbulent noise'. The effects of internal wave strain were also found to be negligible.
Estimation and Analysis of Nonlinear Stochastic Systems. Ph.D. Thesis
NASA Technical Reports Server (NTRS)
Marcus, S. I.
1975-01-01
The algebraic and geometric structures of certain classes of nonlinear stochastic systems were exploited in order to obtain useful stability and estimation results. The class of bilinear stochastic systems (or linear systems with multiplicative noise) was discussed. The stochastic stability of bilinear systems driven by colored noise was considered. Approximate methods for obtaining sufficient conditions for the stochastic stability of bilinear systems evolving on general Lie groups were discussed. Two classes of estimation problems involving bilinear systems were considered. It was proved that, for systems described by certain types of Volterra series expansions or by certain bilinear equations evolving on nilpotent or solvable Lie groups, the optimal conditional mean estimator consists of a finite dimensional nonlinear set of equations. The theory of harmonic analysis was used to derive suboptimal estimators for bilinear systems driven by white noise which evolve on compact Lie groups or homogeneous spaces.
NASA Astrophysics Data System (ADS)
Ullah, Asmat; Chen, Wen; Khan, Mushtaq Ahmad
2017-07-01
This paper introduces a fractional order total variation (FOTV) based model with three different weights in the fractional order derivative definition for multiplicative noise removal purpose. The fractional-order Euler Lagrange equation which is a highly non-linear partial differential equation (PDE) is obtained by the minimization of the energy functional for image restoration. Two numerical schemes namely an iterative scheme based on the dual theory and majorization- minimization algorithm (MMA) are used. To improve the restoration results, we opt for an adaptive parameter selection procedure for the proposed model by applying the trial and error method. We report numerical simulations which show the validity and state of the art performance of the fractional-order model in visual improvement as well as an increase in the peak signal to noise ratio comparing to corresponding methods. Numerical experiments also demonstrate that MMAbased methodology is slightly better than that of an iterative scheme.
Time-lapse joint AVO inversion using generalized linear method based on exact Zoeppritz equations
NASA Astrophysics Data System (ADS)
Zhi, Longxiao; Gu, Hanming
2018-03-01
The conventional method of time-lapse AVO (Amplitude Versus Offset) inversion is mainly based on the approximate expression of Zoeppritz equations. Though the approximate expression is concise and convenient to use, it has certain limitations. For example, its application condition is that the difference of elastic parameters between the upper medium and lower medium is little and the incident angle is small. In addition, the inversion of density is not stable. Therefore, we develop the method of time-lapse joint AVO inversion based on exact Zoeppritz equations. In this method, we apply exact Zoeppritz equations to calculate the reflection coefficient of PP wave. And in the construction of objective function for inversion, we use Taylor series expansion to linearize the inversion problem. Through the joint AVO inversion of seismic data in baseline survey and monitor survey, we can obtain the P-wave velocity, S-wave velocity, density in baseline survey and their time-lapse changes simultaneously. We can also estimate the oil saturation change according to inversion results. Compared with the time-lapse difference inversion, the joint inversion doesn't need certain assumptions and can estimate more parameters simultaneously. It has a better applicability. Meanwhile, by using the generalized linear method, the inversion is easily implemented and its calculation cost is small. We use the theoretical model to generate synthetic seismic records to test and analyze the influence of random noise. The results can prove the availability and anti-noise-interference ability of our method. We also apply the inversion to actual field data and prove the feasibility of our method in actual situation.
Noise Suppression and Surplus Synchrony by Coincidence Detection
Schultze-Kraft, Matthias; Diesmann, Markus; Grün, Sonja; Helias, Moritz
2013-01-01
The functional significance of correlations between action potentials of neurons is still a matter of vivid debate. In particular, it is presently unclear how much synchrony is caused by afferent synchronized events and how much is intrinsic due to the connectivity structure of cortex. The available analytical approaches based on the diffusion approximation do not allow to model spike synchrony, preventing a thorough analysis. Here we theoretically investigate to what extent common synaptic afferents and synchronized inputs each contribute to correlated spiking on a fine temporal scale between pairs of neurons. We employ direct simulation and extend earlier analytical methods based on the diffusion approximation to pulse-coupling, allowing us to introduce precisely timed correlations in the spiking activity of the synaptic afferents. We investigate the transmission of correlated synaptic input currents by pairs of integrate-and-fire model neurons, so that the same input covariance can be realized by common inputs or by spiking synchrony. We identify two distinct regimes: In the limit of low correlation linear perturbation theory accurately determines the correlation transmission coefficient, which is typically smaller than unity, but increases sensitively even for weakly synchronous inputs. In the limit of high input correlation, in the presence of synchrony, a qualitatively new picture arises. As the non-linear neuronal response becomes dominant, the output correlation becomes higher than the total correlation in the input. This transmission coefficient larger unity is a direct consequence of non-linear neural processing in the presence of noise, elucidating how synchrony-coded signals benefit from these generic properties present in cortical networks. PMID:23592953
Linear signal noise summer accurately determines and controls S/N ratio
NASA Technical Reports Server (NTRS)
Sundry, J. L.
1966-01-01
Linear signal noise summer precisely controls the relative power levels of signal and noise, and mixes them linearly in accurately known ratios. The S/N ratio accuracy and stability are greatly improved by this technique and are attained simultaneously.
Modeling Nonlinear Errors in Surface Electromyography Due To Baseline Noise: A New Methodology
Law, Laura Frey; Krishnan, Chandramouli; Avin, Keith
2010-01-01
The surface electromyographic (EMG) signal is often contaminated by some degree of baseline noise. It is customary for scientists to subtract baseline noise from the measured EMG signal prior to further analyses based on the assumption that baseline noise adds linearly to the observed EMG signal. The stochastic nature of both the baseline and EMG signal, however, may invalidate this assumption. Alternately, “true” EMG signals may be either minimally or nonlinearly affected by baseline noise. This information is particularly relevant at low contraction intensities when signal-to-noise ratios (SNR) may be lowest. Thus, the purpose of this simulation study was to investigate the influence of varying levels of baseline noise (approximately 2 – 40 % maximum EMG amplitude) on mean EMG burst amplitude and to assess the best means to account for signal noise. The simulations indicated baseline noise had minimal effects on mean EMG activity for maximum contractions, but increased nonlinearly with increasing noise levels and decreasing signal amplitudes. Thus, the simple baseline noise subtraction resulted in substantial error when estimating mean activity during low intensity EMG bursts. Conversely, correcting EMG signal as a nonlinear function of both baseline and measured signal amplitude provided highly accurate estimates of EMG amplitude. This novel nonlinear error modeling approach has potential implications for EMG signal processing, particularly when assessing co-activation of antagonist muscles or small amplitude contractions where the SNR can be low. PMID:20869716
Regression of non-linear coupling of noise in LIGO detectors
NASA Astrophysics Data System (ADS)
Da Silva Costa, C. F.; Billman, C.; Effler, A.; Klimenko, S.; Cheng, H.-P.
2018-03-01
In 2015, after their upgrade, the advanced Laser Interferometer Gravitational-Wave Observatory (LIGO) detectors started acquiring data. The effort to improve their sensitivity has never stopped since then. The goal to achieve design sensitivity is challenging. Environmental and instrumental noise couple to the detector output with different, linear and non-linear, coupling mechanisms. The noise regression method we use is based on the Wiener–Kolmogorov filter, which uses witness channels to make noise predictions. We present here how this method helped to determine complex non-linear noise couplings in the output mode cleaner and in the mirror suspension system of the LIGO detector.
Quantum propagation in single mode fiber
NASA Technical Reports Server (NTRS)
Joneckis, Lance G.; Shapiro, Jeffrey H.
1994-01-01
This paper presents a theory for quantum light propagation in a single-mode fiber which includes the effects of the Kerr nonlinearity, group-velocity dispersion, and linear loss. The theory reproduces the results of classical self-phase modulation, quantum four-wave mixing, and classical solution physics, within their respective regions of validity. It demonstrates the crucial role played by the Kerr-effect material time constant, in limiting the quantum phase shifts caused by the broadband zero-point fluctuations that accompany any quantized input field. Operator moment equations - approximated, numerically, via a terminated cumulant expansion - are used to obtain results for homodyne-measurement noise spectra when dispersion is negligible. More complicated forms of these equations can be used to incorporate dispersion into the noise calculations.
Banaszek, Konrad; Dragan, Andrzej; Wasilewski, Wojciech; Radzewicz, Czesław
2004-06-25
We present an experiment demonstrating the entanglement enhanced capacity of a quantum channel with correlated noise, modeled by a fiber optic link exhibiting fluctuating birefringence. In this setting, introducing entanglement between two photons is required to maximize the amount of information that can be encoded into their joint polarization degree of freedom. We demonstrated this effect using a fiber-coupled source of entangled photon pairs based on spontaneous parametric down-conversion, and a linear-optics Bell state measurement. The obtained experimental classical capacity with entangled states is equal to 0.82+/-0.04 per a photon pair, and it exceeds approximately 2.5 times the theoretical upper limit when no quantum correlations are allowed.
Perturbations of linear delay differential equations at the verge of instability.
Lingala, N; Namachchivaya, N Sri
2016-06-01
The characteristic equation for a linear delay differential equation (DDE) has countably infinite roots on the complex plane. This paper considers linear DDEs that are on the verge of instability, i.e., a pair of roots of the characteristic equation lies on the imaginary axis of the complex plane and all other roots have negative real parts. It is shown that when small noise perturbations are present, the probability distribution of the dynamics can be approximated by the probability distribution of a certain one-dimensional stochastic differential equation (SDE) without delay. This is advantageous because equations without delay are easier to simulate and one-dimensional SDEs are analytically tractable. When the perturbations are also linear, it is shown that the stability depends on a specific complex number. The theory is applied to study oscillators with delayed feedback. Some errors in other articles that use multiscale approach are pointed out.
Yoon, Yeomin; Noh, Suwoo; Jeong, Jiseong; Park, Kyihwan
2018-05-01
The topology image is constructed from the 2D matrix (XY directions) of heights Z captured from the force-feedback loop controller. For small height variations, nonlinear effects such as hysteresis or creep of the PZT-driven Z nano scanner can be neglected and its calibration is quite straightforward. For large height variations, the linear approximation of the PZT-driven Z nano scanner fail and nonlinear behaviors must be considered because this would cause inaccuracies in the measurement image. In order to avoid such inaccuracies, an additional strain gauge sensor is used to directly measure displacement of the PZT-driven Z nano scanner. However, this approach also has a disadvantage in its relatively low precision. In order to obtain high precision data with good linearity, we propose a method of overcoming the low precision problem of the strain gauge while its feature of good linearity is maintained. We expect that the topology image obtained from the strain gauge sensor showing significant noise at high frequencies. On the other hand, the topology image obtained from the controller output showing low noise at high frequencies. If the low and high frequency signals are separable from both topology images, the image can be constructed so that it is represented with high accuracy and low noise. In order to separate the low frequencies from high frequencies, a 2D Haar wavelet transform is used. Our proposed method use the 2D wavelet transform for obtaining good linearity from strain gauge sensor and good precision from controller output. The advantages of the proposed method are experimentally validated by using topology images. Copyright © 2018 Elsevier B.V. All rights reserved.
Effects of linear trends on estimation of noise in GNSS position time-series
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dmitrieva, K.; Segall, P.; Bradley, A. M.
A thorough understanding of time-dependent noise in Global Navigation Satellite System (GNSS) position time-series is necessary for computing uncertainties in any signals found in the data. However, estimation of time-correlated noise is a challenging task and is complicated by the difficulty in separating noise from signal, the features of greatest interest in the time-series. In this study, we investigate how linear trends affect the estimation of noise in daily GNSS position time-series. We use synthetic time-series to study the relationship between linear trends and estimates of time-correlated noise for the six most commonly cited noise models. We find that themore » effects of added linear trends, or conversely de-trending, vary depending on the noise model. The commonly adopted model of random walk (RW), flicker noise (FN) and white noise (WN) is the most severely affected by de-trending, with estimates of low-amplitude RW most severely biased. FN plus WN is least affected by adding or removing trends. Non-integer power-law noise estimates are also less affected by de-trending, but are very sensitive to the addition of trend when the spectral index is less than one. We derive an analytical relationship between linear trends and the estimated RW variance for the special case of pure RW noise. Finally, overall, we find that to ascertain the correct noise model for GNSS position time-series and to estimate the correct noise parameters, it is important to have independent constraints on the actual trends in the data.« less
Effects of linear trends on estimation of noise in GNSS position time-series
NASA Astrophysics Data System (ADS)
Dmitrieva, K.; Segall, P.; Bradley, A. M.
2017-01-01
A thorough understanding of time-dependent noise in Global Navigation Satellite System (GNSS) position time-series is necessary for computing uncertainties in any signals found in the data. However, estimation of time-correlated noise is a challenging task and is complicated by the difficulty in separating noise from signal, the features of greatest interest in the time-series. In this paper, we investigate how linear trends affect the estimation of noise in daily GNSS position time-series. We use synthetic time-series to study the relationship between linear trends and estimates of time-correlated noise for the six most commonly cited noise models. We find that the effects of added linear trends, or conversely de-trending, vary depending on the noise model. The commonly adopted model of random walk (RW), flicker noise (FN) and white noise (WN) is the most severely affected by de-trending, with estimates of low-amplitude RW most severely biased. FN plus WN is least affected by adding or removing trends. Non-integer power-law noise estimates are also less affected by de-trending, but are very sensitive to the addition of trend when the spectral index is less than one. We derive an analytical relationship between linear trends and the estimated RW variance for the special case of pure RW noise. Overall, we find that to ascertain the correct noise model for GNSS position time-series and to estimate the correct noise parameters, it is important to have independent constraints on the actual trends in the data.
Effects of linear trends on estimation of noise in GNSS position time-series
Dmitrieva, K.; Segall, P.; Bradley, A. M.
2016-10-20
A thorough understanding of time-dependent noise in Global Navigation Satellite System (GNSS) position time-series is necessary for computing uncertainties in any signals found in the data. However, estimation of time-correlated noise is a challenging task and is complicated by the difficulty in separating noise from signal, the features of greatest interest in the time-series. In this study, we investigate how linear trends affect the estimation of noise in daily GNSS position time-series. We use synthetic time-series to study the relationship between linear trends and estimates of time-correlated noise for the six most commonly cited noise models. We find that themore » effects of added linear trends, or conversely de-trending, vary depending on the noise model. The commonly adopted model of random walk (RW), flicker noise (FN) and white noise (WN) is the most severely affected by de-trending, with estimates of low-amplitude RW most severely biased. FN plus WN is least affected by adding or removing trends. Non-integer power-law noise estimates are also less affected by de-trending, but are very sensitive to the addition of trend when the spectral index is less than one. We derive an analytical relationship between linear trends and the estimated RW variance for the special case of pure RW noise. Finally, overall, we find that to ascertain the correct noise model for GNSS position time-series and to estimate the correct noise parameters, it is important to have independent constraints on the actual trends in the data.« less
NASA Astrophysics Data System (ADS)
Patrone, Paul N.; Einstein, T. L.; Margetis, Dionisios
2010-12-01
We study analytically and numerically a one-dimensional model of interacting line defects (steps) fluctuating on a vicinal crystal. Our goal is to formulate and validate analytical techniques for approximately solving systems of coupled nonlinear stochastic differential equations (SDEs) governing fluctuations in surface motion. In our analytical approach, the starting point is the Burton-Cabrera-Frank (BCF) model by which step motion is driven by diffusion of adsorbed atoms on terraces and atom attachment-detachment at steps. The step energy accounts for entropic and nearest-neighbor elastic-dipole interactions. By including Gaussian white noise to the equations of motion for terrace widths, we formulate large systems of SDEs under different choices of diffusion coefficients for the noise. We simplify this description via (i) perturbation theory and linearization of the step interactions and, alternatively, (ii) a mean-field (MF) approximation whereby widths of adjacent terraces are replaced by a self-consistent field but nonlinearities in step interactions are retained. We derive simplified formulas for the time-dependent terrace-width distribution (TWD) and its steady-state limit. Our MF analytical predictions for the TWD compare favorably with kinetic Monte Carlo simulations under the addition of a suitably conservative white noise in the BCF equations.
NASA Astrophysics Data System (ADS)
Dagrau, Franck; Coulouvrat, François; Marchiano, Régis; Héron, Nicolas
2008-06-01
Dassault Aviation as a civil aircraft manufacturer is studying the feasibility of a supersonic business jet with the target of an "acceptable" sonic boom at the ground level, and in particular in case of focusing. A sonic boom computational process has been performed, that takes into account meteorological effects and aircraft manoeuvres. Turn manoeuvres and aircraft acceleration create zones of convergence of rays (caustics) which are the place of sound amplification. Therefore two elements have to be evaluated: firstly the geometrical position of the caustics, and secondly the noise level in the neighbourhood of the caustics. The modelling of the sonic boom propagation is based essentially on the assumptions of geometrical acoustics. Ray tracing is obtained according to Fermat's principle as paths that minimise the propagation time between the source (the aircraft) and the receiver. Wave amplitude and time waveform result from the solution of the inviscid Burgers' equation written along each individual ray. The "age variable" measuring the cumulative nonlinear effects is linked to the ray tube area. Caustics are located as the place where the ray tube area vanishes. Since geometrical acoustics does not take into account diffraction effects, it breaks down in the neighbourhood of caustics where it would predict unphysical infinite pressure amplitude. The aim of this study is to describe an original method for computing the focused noise level. The approach involves three main steps that can be summarised as follows. The propagation equation is solved by a forward marching procedure split into three successive steps: linear propagation in a homogeneous medium, linear perturbation due to the weak heterogeneity of the medium, and non-linear effects. The first step is solved using an "exact" angular spectrum algorithm. Parabolic approximation is applied only for the weak perturbation due to the heterogeneities. Finally, non linear effects are performed by solving the in-viscid Burgers' equation. As this one is valid for a plane wave, the direction of this last one is not prescribed a priori, but is computed in a self-adaptative way using an efficient numerical solver of the non-linear eikonal equation (Fast Marching Method).
Effective amplifier noise for an optical receiver based on linear mode avalanche photodiodes
NASA Technical Reports Server (NTRS)
Chen, C.-C.
1989-01-01
The rms noise charge induced by the amplifier for an optical receiver based on the linear-mode avalanche photodiode (APD) was analyzed. It is shown that for an amplifier with a 1-pF capacitor and a noise temperature of 100 K, the rms noise charge due to the amplifier is about 300. Since the noise charge must be small compared to the signal gain, APD gains on the order of 1000 will be required to operate the receiver in the linear mode.
Seismic Linear Noise Attenuation with Use of Radial Transform
NASA Astrophysics Data System (ADS)
Szymańska-Małysa, Żaneta
2018-03-01
One of the goals of seismic data processing is to attenuate the recorded noise in order to enable correct interpretation of the image. Radial transform has been used as a very effective tool in the attenuation of various types of linear noise, both numerical and real (such as ground roll, direct waves, head waves, guided waves etc). The result of transformation from offset - time (X - T) domain into apparent velocity - time (R - T) domain is frequency separation between reflections and linear events. In this article synthetic and real seismic shot gathers were examined. One example was targeted at far offset area of dataset where reflections and noise had similar apparent velocities and frequency bands. Another example was a result of elastic modelling where linear artefacts were produced. Bandpass filtering and scaling operation executed in radial domain attenuated all discussed types of linear noise very effectively. After noise reduction all further processing steps reveal better results, especially velocity analysis, migration and stacking. In all presented cases signal-to-noise ratio was significantly increased and reflections covered previously by noise were revealed. Power spectra of filtered seismic records preserved real dynamics of reflections.
Theory of chromatic noise masking applied to testing linearity of S-cone detection mechanisms.
Giulianini, Franco; Eskew, Rhea T
2007-09-01
A method for testing the linearity of cone combination of chromatic detection mechanisms is applied to S-cone detection. This approach uses the concept of mechanism noise, the noise as seen by a postreceptoral neural mechanism, to represent the effects of superposing chromatic noise components in elevating thresholds and leads to a parameter-free prediction for a linear mechanism. The method also provides a test for the presence of multiple linear detectors and off-axis looking. No evidence for multiple linear mechanisms was found when using either S-cone increment or decrement tests. The results for both S-cone test polarities demonstrate that these mechanisms combine their cone inputs nonlinearly.
The Laguerre finite difference one-way equation solver
NASA Astrophysics Data System (ADS)
Terekhov, Andrew V.
2017-05-01
This paper presents a new finite difference algorithm for solving the 2D one-way wave equation with a preliminary approximation of a pseudo-differential operator by a system of partial differential equations. As opposed to the existing approaches, the integral Laguerre transform instead of Fourier transform is used. After carrying out the approximation of spatial variables it is possible to obtain systems of linear algebraic equations with better computing properties and to reduce computer costs for their solution. High accuracy of calculations is attained at the expense of employing finite difference approximations of higher accuracy order that are based on the dispersion-relationship-preserving method and the Richardson extrapolation in the downward continuation direction. The numerical experiments have verified that as compared to the spectral difference method based on Fourier transform, the new algorithm allows one to calculate wave fields with a higher degree of accuracy and a lower level of numerical noise and artifacts including those for non-smooth velocity models. In the context of solving the geophysical problem the post-stack migration for velocity models of the types Syncline and Sigsbee2A has been carried out. It is shown that the images obtained contain lesser noise and are considerably better focused as compared to those obtained by the known Fourier Finite Difference and Phase-Shift Plus Interpolation methods. There is an opinion that purely finite difference approaches do not allow carrying out the seismic migration procedure with sufficient accuracy, however the results obtained disprove this statement. For the supercomputer implementation it is proposed to use the parallel dichotomy algorithm when solving systems of linear algebraic equations with block-tridiagonal matrices.
Multivariate moment closure techniques for stochastic kinetic models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lakatos, Eszter, E-mail: e.lakatos13@imperial.ac.uk; Ale, Angelique; Kirk, Paul D. W.
2015-09-07
Stochastic effects dominate many chemical and biochemical processes. Their analysis, however, can be computationally prohibitively expensive and a range of approximation schemes have been proposed to lighten the computational burden. These, notably the increasingly popular linear noise approximation and the more general moment expansion methods, perform well for many dynamical regimes, especially linear systems. At higher levels of nonlinearity, it comes to an interplay between the nonlinearities and the stochastic dynamics, which is much harder to capture correctly by such approximations to the true stochastic processes. Moment-closure approaches promise to address this problem by capturing higher-order terms of the temporallymore » evolving probability distribution. Here, we develop a set of multivariate moment-closures that allows us to describe the stochastic dynamics of nonlinear systems. Multivariate closure captures the way that correlations between different molecular species, induced by the reaction dynamics, interact with stochastic effects. We use multivariate Gaussian, gamma, and lognormal closure and illustrate their use in the context of two models that have proved challenging to the previous attempts at approximating stochastic dynamics: oscillations in p53 and Hes1. In addition, we consider a larger system, Erk-mediated mitogen-activated protein kinases signalling, where conventional stochastic simulation approaches incur unacceptably high computational costs.« less
NASA Technical Reports Server (NTRS)
Dittmar, J. H.
1984-01-01
Previous comparisons between calculated and measured supersonic helical tip speed propeller noise show them to have different trends of peak blade passing tone versus helical tip Mach number. It was postulated that improvements in this comparison could be made first by including the drag force terms in the prediction and then by reducing the blade lift terms at the tip to allow the drag forces to dominate the noise prediction. Propeller hub to tip lift distributions were varied, but they did not yield sufficient change in the predicted lift noise to improve the comparison. This result indicates that some basic changes in the theory may be needed. In addition, the noise predicted by the drag forces did not exhibit the same curve shape as the measured data. So even if the drag force terms were to dominate, the trends with helical tip Mach number for theory and experiment would still not be the same. The effect of the blade shock wave pressure rise was approxmated by increasing the drag coefficient at the blade tip. Predictions using this shock wdave approximation did have a curve shape similar to the measured data. This result indicates that the shock pressure rise probably controls the noise at supersonic tip speed and that the linear prediction method can give the proper noise trend with Mach number.
A Comparative Study of a 1/4-Scale Gulfstream G550 Aircraft Nose Gear Model
NASA Technical Reports Server (NTRS)
Khorrami, Mehdi R.; Neuhart, Dan H.; Zawodny, Nikolas S.; Liu, Fei; Yardibi, Tarik; Cattafesta, Louis; Van de Ven, Thomas
2009-01-01
A series of fluid dynamic and aeroacoustic wind tunnel experiments are performed at the University of Florida Aeroacoustic Flow Facility and the NASA-Langley Basic Aerodynamic Research Tunnel Facility on a high-fidelity -scale model of Gulfstream G550 aircraft nose gear. The primary objectives of this study are to obtain a comprehensive aeroacoustic dataset for a nose landing gear and to provide a clearer understanding of landing gear contributions to overall airframe noise of commercial aircraft during landing configurations. Data measurement and analysis consist of mean and fluctuating model surface pressure, noise source localization maps using a large-aperture microphone directional array, and the determination of far field noise level spectra using a linear array of free field microphones. A total of 24 test runs are performed, consisting of four model assembly configurations, each of which is subjected to three test section speeds, in two different test section orientations. The different model assembly configurations vary in complexity from a fully-dressed to a partially-dressed geometry. The two model orientations provide flyover and sideline views from the perspective of a phased acoustic array for noise source localization via beamforming. Results show that the torque arm section of the model exhibits the highest rms pressures for all model configurations, which is also evidenced in the sideline view noise source maps for the partially-dressed model geometries. Analysis of acoustic spectra data from the linear array microphones shows a slight decrease in sound pressure levels at mid to high frequencies for the partially-dressed cavity open model configuration. In addition, far field sound pressure level spectra scale approximately with the 6th power of velocity and do not exhibit traditional Strouhal number scaling behavior.
Metallic-thin-film instability with spatially correlated thermal noise.
Diez, Javier A; González, Alejandro G; Fernández, Roberto
2016-01-01
We study the effects of stochastic thermal fluctuations on the instability of the free surface of a flat liquid metallic film on a solid substrate. These fluctuations are represented by a stochastic noise term added to the deterministic equation for the film thickness within the long-wave approximation. Unlike the case of polymeric films, we find that this noise, while remaining white in time, must be colored in space, at least in some regimes. The corresponding noise term is characterized by a nonzero correlation length, ℓ_{c}, which, combined with the size of the system, leads to a dimensionless parameter β that accounts for the relative importance of the spatial correlation (β∼ℓ_{c}^{-1}). We perform the linear stability analysis (LSA) of the film both with and without the noise term and find that for ℓ_{c} larger than some critical value (depending on the system size), the wavelength of the peak of the spectrum is larger than that corresponding to the deterministic case, while for smaller ℓ_{c} this peak corresponds to smaller wavelength than the latter. Interestingly, whatever the value of ℓ_{c}, the peak always approaches the deterministic one for larger times. We compare LSA results with the numerical simulations of the complete nonlinear problem and find a good agreement in the power spectra for early times at different values of β. For late times, we find that the stochastic LSA predicts well the position of the dominant wavelength, showing that nonlinear interactions do not modify the trends of the early linear stages. Finally, we fit the theoretical spectra to experimental data from a nanometric laser-melted copper film and find that at later times, the adjustment requires smaller values of β (larger space correlations).
Metallic-thin-film instability with spatially correlated thermal noise
NASA Astrophysics Data System (ADS)
Diez, Javier A.; González, Alejandro G.; Fernández, Roberto
2016-01-01
We study the effects of stochastic thermal fluctuations on the instability of the free surface of a flat liquid metallic film on a solid substrate. These fluctuations are represented by a stochastic noise term added to the deterministic equation for the film thickness within the long-wave approximation. Unlike the case of polymeric films, we find that this noise, while remaining white in time, must be colored in space, at least in some regimes. The corresponding noise term is characterized by a nonzero correlation length, ℓc, which, combined with the size of the system, leads to a dimensionless parameter β that accounts for the relative importance of the spatial correlation (β ˜ℓc-1 ). We perform the linear stability analysis (LSA) of the film both with and without the noise term and find that for ℓc larger than some critical value (depending on the system size), the wavelength of the peak of the spectrum is larger than that corresponding to the deterministic case, while for smaller ℓc this peak corresponds to smaller wavelength than the latter. Interestingly, whatever the value of ℓc, the peak always approaches the deterministic one for larger times. We compare LSA results with the numerical simulations of the complete nonlinear problem and find a good agreement in the power spectra for early times at different values of β . For late times, we find that the stochastic LSA predicts well the position of the dominant wavelength, showing that nonlinear interactions do not modify the trends of the early linear stages. Finally, we fit the theoretical spectra to experimental data from a nanometric laser-melted copper film and find that at later times, the adjustment requires smaller values of β (larger space correlations).
Phenomenology of stochastic exponential growth
NASA Astrophysics Data System (ADS)
Pirjol, Dan; Jafarpour, Farshid; Iyer-Biswas, Srividya
2017-06-01
Stochastic exponential growth is observed in a variety of contexts, including molecular autocatalysis, nuclear fission, population growth, inflation of the universe, viral social media posts, and financial markets. Yet literature on modeling the phenomenology of these stochastic dynamics has predominantly focused on one model, geometric Brownian motion (GBM), which can be described as the solution of a Langevin equation with linear drift and linear multiplicative noise. Using recent experimental results on stochastic exponential growth of individual bacterial cell sizes, we motivate the need for a more general class of phenomenological models of stochastic exponential growth, which are consistent with the observation that the mean-rescaled distributions are approximately stationary at long times. We show that this behavior is not consistent with GBM, instead it is consistent with power-law multiplicative noise with positive fractional powers. Therefore, we consider this general class of phenomenological models for stochastic exponential growth, provide analytical solutions, and identify the important dimensionless combination of model parameters, which determines the shape of the mean-rescaled distribution. We also provide a prescription for robustly inferring model parameters from experimentally observed stochastic growth trajectories.
Noncoherent pseudonoise code tracking performance of spread spectrum receivers
NASA Technical Reports Server (NTRS)
Simon, M. K.
1977-01-01
The optimum design and performance of two noncoherent PN tracking loop configurations, namely, the delay-locked loop and tau-dither loop, are described. In particular, the bandlimiting effects of the bandpass arm filters are considered by demonstrating that for a fixed data rate and data signal-to-noise ratio, there exists an optimum filter bandwidth in the sense of minimizing the loop's tracking jitter. Both the linear and nonlinear loop analyses are presented, and the region of validity of the former relative to the latter is indicated. In addition, numerical results are given for several filter types. For example, assuming ideal bandpass arm filters, it is shown that the tau-dither loop requires approximately 1 dB more signal-to-noise ratio than the delay-locked loop for equal rms tracking jitters.
Orio, Patricio; Soudry, Daniel
2012-01-01
Background The phenomena that emerge from the interaction of the stochastic opening and closing of ion channels (channel noise) with the non-linear neural dynamics are essential to our understanding of the operation of the nervous system. The effects that channel noise can have on neural dynamics are generally studied using numerical simulations of stochastic models. Algorithms based on discrete Markov Chains (MC) seem to be the most reliable and trustworthy, but even optimized algorithms come with a non-negligible computational cost. Diffusion Approximation (DA) methods use Stochastic Differential Equations (SDE) to approximate the behavior of a number of MCs, considerably speeding up simulation times. However, model comparisons have suggested that DA methods did not lead to the same results as in MC modeling in terms of channel noise statistics and effects on excitability. Recently, it was shown that the difference arose because MCs were modeled with coupled gating particles, while the DA was modeled using uncoupled gating particles. Implementations of DA with coupled particles, in the context of a specific kinetic scheme, yielded similar results to MC. However, it remained unclear how to generalize these implementations to different kinetic schemes, or whether they were faster than MC algorithms. Additionally, a steady state approximation was used for the stochastic terms, which, as we show here, can introduce significant inaccuracies. Main Contributions We derived the SDE explicitly for any given ion channel kinetic scheme. The resulting generic equations were surprisingly simple and interpretable – allowing an easy, transparent and efficient DA implementation, avoiding unnecessary approximations. The algorithm was tested in a voltage clamp simulation and in two different current clamp simulations, yielding the same results as MC modeling. Also, the simulation efficiency of this DA method demonstrated considerable superiority over MC methods, except when short time steps or low channel numbers were used. PMID:22629320
Klim, Søren; Mortensen, Stig Bousgaard; Kristensen, Niels Rode; Overgaard, Rune Viig; Madsen, Henrik
2009-06-01
The extension from ordinary to stochastic differential equations (SDEs) in pharmacokinetic and pharmacodynamic (PK/PD) modelling is an emerging field and has been motivated in a number of articles [N.R. Kristensen, H. Madsen, S.H. Ingwersen, Using stochastic differential equations for PK/PD model development, J. Pharmacokinet. Pharmacodyn. 32 (February(1)) (2005) 109-141; C.W. Tornøe, R.V. Overgaard, H. Agersø, H.A. Nielsen, H. Madsen, E.N. Jonsson, Stochastic differential equations in NONMEM: implementation, application, and comparison with ordinary differential equations, Pharm. Res. 22 (August(8)) (2005) 1247-1258; R.V. Overgaard, N. Jonsson, C.W. Tornøe, H. Madsen, Non-linear mixed-effects models with stochastic differential equations: implementation of an estimation algorithm, J. Pharmacokinet. Pharmacodyn. 32 (February(1)) (2005) 85-107; U. Picchini, S. Ditlevsen, A. De Gaetano, Maximum likelihood estimation of a time-inhomogeneous stochastic differential model of glucose dynamics, Math. Med. Biol. 25 (June(2)) (2008) 141-155]. PK/PD models are traditionally based ordinary differential equations (ODEs) with an observation link that incorporates noise. This state-space formulation only allows for observation noise and not for system noise. Extending to SDEs allows for a Wiener noise component in the system equations. This additional noise component enables handling of autocorrelated residuals originating from natural variation or systematic model error. Autocorrelated residuals are often partly ignored in PK/PD modelling although violating the hypothesis for many standard statistical tests. This article presents a package for the statistical program R that is able to handle SDEs in a mixed-effects setting. The estimation method implemented is the FOCE(1) approximation to the population likelihood which is generated from the individual likelihoods that are approximated using the Extended Kalman Filter's one-step predictions.
Laboratory test results for an airborne ASTER simulator
NASA Astrophysics Data System (ADS)
Ezaka, Teruya; Kannari, Yoshiaki; Mills, Franklin P.; Watanabe, Hiroshi; Sano, Masaharu; Chang, Sheng-Huei
1993-08-01
An airborne ASTER simulator (AAS) is being developed by the Geophysical Environmental Research Corporation (GER) to study land surface temperature and emittance in the thermal infrared. Laboratory tests in October 1992 at NASA's Stennis Space Center (SSC) measured the AAS's spectral, approximate NEdT, and approximate spatial response characteristics. The spectral FWHM for most channels is smaller than 0.3 micrometers ; the NEdT for most TIR channels is better than 0.4 K; and the nominal IFOV is 5 mrad. Flight data was collected over Cuprite and Goldfield, Nevada and near Valencia, California in November 1992. The silicified and opalized zones at Cuprite could be discriminated using decorrelation-stretch images. AAS decorrelation-stretch images agree, qualitatively, with data from NASA's thermal infrared mapping spectrometer (TIMS). These results indicate the AAS may be a good tool for remote sensing studies of geological materials. Lower noise detector arrays and linear variable (optical) filters for the TIR channels will be tested in flights over Cuprite, Nevada later this year. These and other improvements may reduce the NEdT and improve the signal-to-noise ratio.
Adaptive EMG noise reduction in ECG signals using noise level approximation
NASA Astrophysics Data System (ADS)
Marouf, Mohamed; Saranovac, Lazar
2017-12-01
In this paper the usage of noise level approximation for adaptive Electromyogram (EMG) noise reduction in the Electrocardiogram (ECG) signals is introduced. To achieve the adequate adaptiveness, a translation-invariant noise level approximation is employed. The approximation is done in the form of a guiding signal extracted as an estimation of the signal quality vs. EMG noise. The noise reduction framework is based on a bank of low pass filters. So, the adaptive noise reduction is achieved by selecting the appropriate filter with respect to the guiding signal aiming to obtain the best trade-off between the signal distortion caused by filtering and the signal readability. For the evaluation purposes; both real EMG and artificial noises are used. The tested ECG signals are from the MIT-BIH Arrhythmia Database Directory, while both real and artificial records of EMG noise are added and used in the evaluation process. Firstly, comparison with state of the art methods is conducted to verify the performance of the proposed approach in terms of noise cancellation while preserving the QRS complex waves. Additionally, the signal to noise ratio improvement after the adaptive noise reduction is computed and presented for the proposed method. Finally, the impact of adaptive noise reduction method on QRS complexes detection was studied. The tested signals are delineated using a state of the art method, and the QRS detection improvement for different SNR is presented.
Signal detection in power-law noise: effect of spectrum exponents.
Burgess, Arthur E; Judy, Philip F
2007-12-01
Many natural backgrounds have approximately isotropic power spectra of the power-law form, P(f)=K/f(beta), where f is radial frequency. For natural scenes and mammograms, the values of the exponent, beta, range from 1.5 to 3.5. The ideal observer model predicts that for signals with certain properties and backgrounds that can be treated as random noise, a plot of log (contrast threshold) versus log (signal size) will be linear with slope, m, given by: m=(beta-2)/2. This plot is referred to as a contrast-detail (CD) diagram. It is interesting that this predicts a detection threshold that is independent of signal size for beta equal to 2. We present two-alternative forced-choice (2AFC) detection results for human and channelized model observers of a simple signal in filtered noise with exponents from 1.5 to 3.5. The CD diagram results are in good agreement with the prediction of this equation.
Incorporating signal-dependent noise for hyperspectral target detection
NASA Astrophysics Data System (ADS)
Morman, Christopher J.; Meola, Joseph
2015-05-01
The majority of hyperspectral target detection algorithms are developed from statistical data models employing stationary background statistics or white Gaussian noise models. Stationary background models are inaccurate as a result of two separate physical processes. First, varying background classes often exist in the imagery that possess different clutter statistics. Many algorithms can account for this variability through the use of subspaces or clustering techniques. The second physical process, which is often ignored, is a signal-dependent sensor noise term. For photon counting sensors that are often used in hyperspectral imaging systems, sensor noise increases as the measured signal level increases as a result of Poisson random processes. This work investigates the impact of this sensor noise on target detection performance. A linear noise model is developed describing sensor noise variance as a linear function of signal level. The linear noise model is then incorporated for detection of targets using data collected at Wright Patterson Air Force Base.
NASA Technical Reports Server (NTRS)
Yu, Xiaolong; Lewis, Edwin R.
1989-01-01
It is shown that noise can be an important element in the translation of neuronal generator potentials (summed inputs) to neuronal spike trains (outputs), creating or expanding a range of amplitudes over which the spike rate is proportional to the generator potential amplitude. Noise converts the basically nonlinear operation of a spike initiator into a nearly linear modulation process. This linearization effect of noise is examined in a simple intuitive model of a static threshold and in a more realistic computer simulation of spike initiator based on the Hodgkin-Huxley (HH) model. The results are qualitatively similar; in each case larger noise amplitude results in a larger range of nearly linear modulation. The computer simulation of the HH model with noise shows linear and nonlinear features that were earlier observed in spike data obtained from the VIIIth nerve of the bullfrog. This suggests that these features can be explained in terms of spike initiator properties, and it also suggests that the HH model may be useful for representing basic spike initiator properties in vertebrates.
NASA Technical Reports Server (NTRS)
Jobson, Daniel J.; Rahman, Zia-Ur; Woodell, Glenn A.; Hines, Glenn D.
2004-01-01
Noise is the primary visibility limit in the process of non-linear image enhancement, and is no longer a statistically stable additive noise in the post-enhancement image. Therefore novel approaches are needed to both assess and reduce spatially variable noise at this stage in overall image processing. Here we will examine the use of edge pattern analysis both for automatic assessment of spatially variable noise and as a foundation for new noise reduction methods.
Discretized energy minimization in a wave guide with point sources
NASA Technical Reports Server (NTRS)
Propst, G.
1994-01-01
An anti-noise problem on a finite time interval is solved by minimization of a quadratic functional on the Hilbert space of square integrable controls. To this end, the one-dimensional wave equation with point sources and pointwise reflecting boundary conditions is decomposed into a system for the two propagating components of waves. Wellposedness of this system is proved for a class of data that includes piecewise linear initial conditions and piecewise constant forcing functions. It is shown that for such data the optimal piecewise constant control is the solution of a sparse linear system. Methods for its computational treatment are presented as well as examples of their applicability. The convergence of discrete approximations to the general optimization problem is demonstrated by finite element methods.
Nonlinear Estimation of Discrete-Time Signals Under Random Observation Delay
DOE Office of Scientific and Technical Information (OSTI.GOV)
Caballero-Aguila, R.; Jimenez-Lopez, J. D.; Hermoso-Carazo, A.
2008-11-06
This paper presents an approximation to the nonlinear least-squares estimation problem of discrete-time stochastic signals using nonlinear observations with additive white noise which can be randomly delayed by one sampling time. The observation delay is modelled by a sequence of independent Bernoulli random variables whose values, zero or one, indicate that the real observation arrives on time or it is delayed and, hence, the available measurement to estimate the signal is not up-to-date. Assuming that the state-space model generating the signal is unknown and only the covariance functions of the processes involved in the observation equation are ready for use,more » a filtering algorithm based on linear approximations of the real observations is proposed.« less
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
NASA Astrophysics Data System (ADS)
Barton, Sinead J.; Kerr, Laura T.; Domijan, Katarina; Hennelly, Bryan M.
2016-04-01
Raman micro-spectroscopy is an optoelectronic technique that can be used to evaluate the chemical composition of biological samples and has been shown to be a powerful diagnostic tool for the investigation of various cancer related diseases including bladder, breast, and cervical cancer. Raman scattering is an inherently weak process with approximately 1 in 107 photons undergoing scattering and for this reason, noise from the recording system can have a significant impact on the quality of the signal, and its suitability for diagnostic classification. The main sources of noise in the recorded signal are shot noise, CCD dark current, and CCD readout noise. Shot noise results from the low signal photon count while dark current results from thermally generated electrons in the semiconductor pixels. Both of these noise sources are time dependent; readout noise is time independent but is inherent in each individual recording and results in the fundamental limit of measurement, arising from the internal electronics of the camera. In this paper, each of the aforementioned noise sources are analysed in isolation, and used to experimentally validate a mathematical model. This model is then used to simulate spectra that might be acquired under various experimental conditions including the use of different cameras, different source wavelength, and power etc. Simulated noisy datasets of T24 and RT112 cell line spectra are generated based on true cell Raman spectrum irradiance values (recorded using very long exposure times) and the addition of simulated noise. These datasets are then input to multivariate classification using Principal Components Analysis and Linear Discriminant Analysis. This method enables an investigation into the effect of noise on the sensitivity and specificity of Raman based classification under various experimental conditions and using different equipment.
NASA Technical Reports Server (NTRS)
Wrigley, Chris J.; Hancock, Bruce R.; Newton, Kenneth W.; Cunningham, Thomas J.
2013-01-01
Single-slope analog-to-digital converters (ADCs) are particularly useful for onchip digitization in focal plane arrays (FPAs) because of their inherent monotonicity, relative simplicity, and efficiency for column-parallel applications, but they are comparatively slow. Squareroot encoding can allow the number of code values to be reduced without loss of signal-to-noise ratio (SNR) by keeping the quantization noise just below the signal shot noise. This encoding can be implemented directly by using a quadratic ramp. The reduction in the number of code values can substantially increase the quantization speed. However, in an FPA, the fixed pattern noise (FPN) limits the use of small quantization steps at low signal levels. If the zero-point is adjusted so that the lowest column is onscale, the other columns, including those at the center of the distribution, will be pushed up the ramp where the quantization noise is higher. Additionally, the finite frequency response of the ramp buffer amplifier and the comparator distort the shape of the ramp, so that the effective ramp value at the time the comparator trips differs from the intended value, resulting in errors. Allowing increased settling time decreases the quantization speed, while increasing the bandwidth increases the noise. The FPN problem is solved by breaking the ramp into two portions, with some fraction of the available code values allocated to a linear ramp and the remainder to a quadratic ramp. To avoid large transients, both the value and the slope of the linear and quadratic portions should be equal where they join. The span of the linear portion must cover the minimum offset, but not necessarily the maximum, since the fraction of the pixels above the upper limit will still be correctly quantized, albeit with increased quantization noise. The required linear span, maximum signal and ratio of quantization noise to shot noise at high signal, along with the continuity requirement, determines the number of code values that must be allocated to each portion. The distortion problem is solved by using a lookup table to convert captured code values back to signal levels. The values in this table will be similar to the intended ramp value, but with a correction for the finite bandwidth effects. Continuous-time comparators are used, and their bandwidth is set below the step rate, which smoothes the ramp and reduces the noise. No settling time is needed, as would be the case for clocked comparators, but the low bandwidth enhances the distortion of the non-linear portion. This is corrected by use of a return lookup table, which differs from the one used to generate the ramp. The return lookup table is obtained by calibrating against a stepped precision DC reference. This results in a residual non-linearity well below the quantization noise. This method can also compensate for differential non-linearity (DNL) in the DAC used to generate the ramp. The use of a ramp with a combination of linear and quadratic portions for a single-slope ADC is novel. The number of steps is minimized by keeping the step size just below the photon shot noise. This in turn maximizes the speed of the conversion. High resolution is maintained by keeping small quantization steps at low signals, and noise is minimized by allowing the lowest analog bandwidth, all without increasing the quantization noise. A calibrated return lookup table allows the system to maintain excellent linearity.
NASA Astrophysics Data System (ADS)
Jiang, Weiping; Ma, Jun; Li, Zhao; Zhou, Xiaohui; Zhou, Boye
2018-05-01
The analysis of the correlations between the noise in different components of GPS stations has positive significance to those trying to obtain more accurate uncertainty of velocity with respect to station motion. Previous research into noise in GPS position time series focused mainly on single component evaluation, which affects the acquisition of precise station positions, the velocity field, and its uncertainty. In this study, before and after removing the common-mode error (CME), we performed one-dimensional linear regression analysis of the noise amplitude vectors in different components of 126 GPS stations with a combination of white noise, flicker noise, and random walking noise in Southern California. The results show that, on the one hand, there are above-moderate degrees of correlation between the white noise amplitude vectors in all components of the stations before and after removal of the CME, while the correlations between flicker noise amplitude vectors in horizontal and vertical components are enhanced from un-correlated to moderately correlated by removing the CME. On the other hand, the significance tests show that, all of the obtained linear regression equations, which represent a unique function of the noise amplitude in any two components, are of practical value after removing the CME. According to the noise amplitude estimates in two components and the linear regression equations, more accurate noise amplitudes can be acquired in the two components.
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.
Scott, M
2012-08-01
The time-covariance function captures the dynamics of biochemical fluctuations and contains important information about the underlying kinetic rate parameters. Intrinsic fluctuations in biochemical reaction networks are typically modelled using a master equation formalism. In general, the equation cannot be solved exactly and approximation methods are required. For small fluctuations close to equilibrium, a linearisation of the dynamics provides a very good description of the relaxation of the time-covariance function. As the number of molecules in the system decrease, deviations from the linear theory appear. Carrying out a systematic perturbation expansion of the master equation to capture these effects results in formidable algebra; however, symbolic mathematics packages considerably expedite the computation. The authors demonstrate that non-linear effects can reveal features of the underlying dynamics, such as reaction stoichiometry, not available in linearised theory. Furthermore, in models that exhibit noise-induced oscillations, non-linear corrections result in a shift in the base frequency along with the appearance of a secondary harmonic.
Interventional MRI: tapering improves the distal sensitivity of the loopless antenna.
Qian, Di; El-Sharkawy, AbdEl-Monem M; Atalar, Ergin; Bottomley, Paul A
2010-03-01
The "loopless antenna" is an interventional MRI detector consisting of a tuned coaxial cable and an extended inner conductor or "whip". A limitation is the poor sensitivity afforded at, and immediately proximal to, its distal end, which is exacerbated by the extended whip length when the whip is uniformly insulated. It is shown here that tapered insulation dramatically improves the distal sensitivity of the loopless antenna by pushing the current sensitivity toward the tip. The absolute signal-to-noise ratio is numerically computed by the electromagnetic method-of-moments for three resonant 3-T antennae with no insulation, uniform insulation, and with linearly tapered insulation. The analysis shows that tapered insulation provides an approximately 400% increase in signal-to-noise ratio in trans-axial planes 1 cm from the tip and a 16-fold increase in the sensitive area as compared to an equivalent, uniformly insulated antenna. These findings are directly confirmed by phantom experiments and by MRI of an aorta specimen. The results demonstrate that numerical electromagnetic signal-to-noise ratio analysis can accurately predict the loopless detector's signal-to-noise ratio and play a central role in optimizing its design. The manifold improvement in distal signal-to-noise ratio afforded by redistributing the insulation should improve the loopless antenna's utility for interventional MRI. (c) 2010 Wiley-Liss, Inc.
While, Peter T; Teruel, Jose R; Vidić, Igor; Bathen, Tone F; Goa, Pål Erik
2018-06-01
To explore the relationship between relative enhanced diffusivity (RED) and intravoxel incoherent motion (IVIM), as well as the impact of noise and the choice of intermediate diffusion weighting (b value) on the RED parameter. A mathematical derivation was performed to cast RED in terms of the IVIM parameters. Noise analysis and b value optimization was conducted by using Monte Carlo calculations to generate diffusion-weighted imaging data appropriate to breast and liver tissue at three different signal-to-noise ratios. RED was shown to be approximately linearly proportional to the IVIM parameter f, inversely proportional to D and to follow an inverse exponential decay with respect to D*. The choice of intermediate b value was shown to be important in minimizing the impact of noise on RED and in maximizing its discriminatory power. RED was shown to be essentially a reparameterization of the IVIM estimates for f and D obtained with three b values. RED imaging in the breast and liver should be performed with intermediate b values of 100 and 50 s/mm 2 , respectively. Future clinical studies involving RED should also estimate the IVIM parameters f and D using three b values for comparison.
Improved nonlinear prediction method
NASA Astrophysics Data System (ADS)
Adenan, Nur Hamiza; Md Noorani, Mohd Salmi
2014-06-01
The analysis and prediction of time series data have been addressed by researchers. Many techniques have been developed to be applied in various areas, such as weather forecasting, financial markets and hydrological phenomena involving data that are contaminated by noise. Therefore, various techniques to improve the method have been introduced to analyze and predict time series data. In respect of the importance of analysis and the accuracy of the prediction result, a study was undertaken to test the effectiveness of the improved nonlinear prediction method for data that contain noise. The improved nonlinear prediction method involves the formation of composite serial data based on the successive differences of the time series. Then, the phase space reconstruction was performed on the composite data (one-dimensional) to reconstruct a number of space dimensions. Finally the local linear approximation method was employed to make a prediction based on the phase space. This improved method was tested with data series Logistics that contain 0%, 5%, 10%, 20% and 30% of noise. The results show that by using the improved method, the predictions were found to be in close agreement with the observed ones. The correlation coefficient was close to one when the improved method was applied on data with up to 10% noise. Thus, an improvement to analyze data with noise without involving any noise reduction method was introduced to predict the time series data.
Street-level noise in an urban setting: assessment and contribution to personal exposure.
McAlexander, Tara P; Gershon, Robyn R M; Neitzel, Richard L
2015-02-28
The urban soundscape, which represents the totality of noise in the urban setting, is formed from a wide range of sources. One of the most ubiquitous and least studied of these is street-level (i.e., sidewalk) noise. Mainly associated with vehicular traffic, street level noise is hard to ignore and hard to escape. It is also potentially dangerous, as excessive noise from any source is an important risk factor for adverse health effects. This study was conducted to better characterize the urban soundscape and the role of street level noise on overall personal noise exposure in an urban setting. Street-level noise measures were obtained at 99 street sites located throughout New York City (NYC), along with data on time, location, and sources of environmental noise. The relationship between street-level noise measures and potential predictors of noise was analyzed using linear and logistic regression models, and geospatial modeling was used to evaluate spatial trends in noise. Daily durations of street-level activities (time spent standing, sitting, walking and running on streets) were estimated via survey from a sample of NYC community members recruited at NYC street fairs. Street-level noise measurements were then combined with daily exposure durations for each member of the sample to estimate exposure to street noise, as well as exposure to other sources of noise. The mean street noise level was 73.4 dBA, with substantial spatial variation (range 55.8-95.0 dBA). Density of vehicular (road) traffic was significantly associated with excessive street level noise levels. Exposure duration data for street-level noise and other common sources of noise were collected from 1894 NYC community members. Based on individual street-level exposure estimates, and in consideration of all other sources of noise exposure in an urban population, we estimated that street noise exposure contributes approximately 4% to an average individual's annual noise dose. Street-level noise exposure is a potentially important source of overall noise exposure, and the reduction of environmental sources of excessive street- level noise should be a priority for public health and urban planning.
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
Black hole ringdown echoes and howls
NASA Astrophysics Data System (ADS)
Nakano, Hiroyuki; Sago, Norichika; Tagoshi, Hideyuki; Tanaka, Takahiro
2017-07-01
Recently the possibility of detecting echoes of ringdown gravitational waves from binary black hole mergers was shown. The presence of echoes is expected if the black hole is surrounded by a mirror that reflects gravitational waves near the horizon. Here, we present slightly more sophisticated templates motivated by a waveform which is obtained by solving the linear perturbation equation around a Kerr black hole with a complete reflecting boundary condition in the stationary traveling wave approximation. We estimate that the proposed template can bring about a 10% improvement in the signal-to-noise ratio.
NASA Technical Reports Server (NTRS)
Vlahopoulos, Nickolas; Lyle, Karen H.; Burley, Casey L.
1998-01-01
An algorithm for generating appropriate velocity boundary conditions for an acoustic boundary element analysis from the kinematics of an operating propeller is presented. It constitutes the initial phase of Integrating sophisticated rotorcraft models into a conventional boundary element analysis. Currently, the pressure field is computed by a linear approximation. An initial validation of the developed process was performed by comparing numerical results to test data for the external acoustic pressure on the surface of a tilt-rotor aircraft for one flight condition.
Quantum noise of a Bose-Einstein condensate in an optical cavity, correlations, and entanglement
NASA Astrophysics Data System (ADS)
Szirmai, G.; Nagy, D.; Domokos, P.
2010-04-01
A Bose-Einstein condensate of ultracold atoms inside the field of a laser-driven optical cavity exhibits dispersive optical bistability. We describe this system by using mean-field approximation and by analyzing the correlation functions of the linearized quantum fluctuations around the mean-field solution. The entanglement and the statistics of the atom-field quadratures are given in the stationary state. It is shown that the mean-field solution, that is, the Bose-Einstein condensate, is robust against entanglement generation for most of the phase diagram.
Pattern formation in individual-based systems with time-varying parameters
NASA Astrophysics Data System (ADS)
Ashcroft, Peter; Galla, Tobias
2013-12-01
We study the patterns generated in finite-time sweeps across symmetry-breaking bifurcations in individual-based models. Similar to the well-known Kibble-Zurek scenario of defect formation, large-scale patterns are generated when model parameters are varied slowly, whereas fast sweeps produce a large number of small domains. The symmetry breaking is triggered by intrinsic noise, originating from the discrete dynamics at the microlevel. Based on a linear-noise approximation, we calculate the characteristic length scale of these patterns. We demonstrate the applicability of this approach in a simple model of opinion dynamics, a model in evolutionary game theory with a time-dependent fitness structure, and a model of cell differentiation. Our theoretical estimates are confirmed in simulations. In further numerical work, we observe a similar phenomenon when the symmetry-breaking bifurcation is triggered by population growth.
Breadboard stellar tracker system test report
NASA Technical Reports Server (NTRS)
Kollodge, J. C.; Parrish, K. A.
1984-01-01
BASD has, in the past, developed several unique position tracking algorithms for charge transfer device (CTD) sensors. These algorithms provide an interpixel transfer function with the following characteristics: (1) high linearity; (2) simplified track logic; (3) high gain; and (4) high noise rejection. A previous test program using the GE charge injection device (CID) showed that accuracy for BASD's breadboard was limited to approximately 2% of a pixel (1 sigma) whereas analysis and simulation indicated the limit should be less than 0.5% of a pixel, assuming the limit to be detector response and dark current noise. The test program was conducted under NASA contract No. NAS8-34263. The test approach for that program did not provide sufficient data to identify the sources of error and left open the amount of contribution from parameters such as image distribution, geometric distortion and system alignment errors.
Noise limitations in optical linear algebra processors.
Batsell, S G; Jong, T L; Walkup, J F; Krile, T F
1990-05-10
A general statistical noise model is presented for optical linear algebra processors. A statistical analysis which includes device noise, the multiplication process, and the addition operation is undertaken. We focus on those processes which are architecturally independent. Finally, experimental results which verify the analytical predictions are also presented.
Quantum noise spectra for periodically driven cavity optomechanics
NASA Astrophysics Data System (ADS)
Aranas, E. B.; Akram, M. Javed; Malz, Daniel; Monteiro, T. S.
2017-12-01
A growing number of experimental setups in cavity optomechanics exploit periodically driven fields. However, such setups are not amenable to analysis by using simple, yet powerful, closed-form expressions of linearized optomechanics, which have provided so much of our present understanding of experimental optomechanics. In the present paper, we formulate a method to calculate quantum noise spectra in modulated optomechanical systems, which we analyze, compare, and discuss with two other recently proposed solutions: we term these (i) frequency-shifted operators, (ii) Floquet [Phys. Rev. A 94, 023803 (2016), 10.1103/PhysRevA.94.023803], and (iii) iterative analysis [New J. Phys. 18, 113021 (2016), 10.1088/1367-2630/18/11/113021]. We prove that (i) and (ii) yield equivalent noise spectra and find that (iii) is an analytical approximation to (i) for weak modulations. We calculate the noise spectra of a doubly modulated system describing experiments of levitated particles in hybrid electro-optical traps. We show excellent agreement with Langevin stochastic simulations in the thermal regime and predict squeezing in the quantum regime. Finally, we reveal how otherwise-inaccessible spectral components of a modulated system can be measured in heterodyne detection through an appropriate choice of modulation frequencies.
Optical linear algebra processors: noise and error-source modeling.
Casasent, D; Ghosh, A
1985-06-01
The modeling of system and component noise and error sources in optical linear algebra processors (OLAP's) are considered, with attention to the frequency-multiplexed OLAP. General expressions are obtained for the output produced as a function of various component errors and noise. A digital simulator for this model is discussed.
Optical linear algebra processors - Noise and error-source modeling
NASA Technical Reports Server (NTRS)
Casasent, D.; Ghosh, A.
1985-01-01
The modeling of system and component noise and error sources in optical linear algebra processors (OLAPs) are considered, with attention to the frequency-multiplexed OLAP. General expressions are obtained for the output produced as a function of various component errors and noise. A digital simulator for this model is discussed.
Information analysis of posterior canal afferents in the turtle, Trachemys scripta elegans.
Rowe, Michael H; Neiman, Alexander B
2012-01-24
We have used sinusoidal and band-limited Gaussian noise stimuli along with information measures to characterize the linear and non-linear responses of morpho-physiologically identified posterior canal (PC) afferents and to examine the relationship between mutual information rate and other physiological parameters. Our major findings are: 1) spike generation in most PC afferents is effectively a stochastic renewal process, and spontaneous discharges are fully characterized by their first order statistics; 2) a regular discharge, as measured by normalized coefficient of variation (cv*), reduces intrinsic noise in afferent discharges at frequencies below the mean firing rate; 3) coherence and mutual information rates, calculated from responses to band-limited Gaussian noise, are jointly determined by gain and intrinsic noise (discharge regularity), the two major determinants of signal to noise ratio in the afferent response; 4) measures of optimal non-linear encoding were only moderately greater than optimal linear encoding, indicating that linear stimulus encoding is limited primarily by internal noise rather than by non-linearities; and 5) a leaky integrate and fire model reproduces these results and supports the suggestion that the combination of high discharge regularity and high discharge rates serves to extend the linear encoding range of afferents to higher frequencies. These results provide a framework for future assessments of afferent encoding of signals generated during natural head movements and for comparison with coding strategies used by other sensory systems. This article is part of a Special Issue entitled: Neural Coding. Copyright © 2011 Elsevier B.V. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sablik, M.J.; Augustyniak, B.; Chmielewski, M.
1996-04-01
The almost linear dependence of the maximum Barkhausen noise signal amplitude on stress has made it a tool for nondestructive evaluation of residual stress. Recently, a model has been developed to account for the stress dependence of the Barkhausen noise signal. The model uses the development of Alessandro {ital et} {ital al}. who use coupled Langevin equations to derive an expression for the Barkhausen noise power spectrum. The model joins this expression to the magnetomechanical hysteresis model of Sablik {ital et} {ital al}., obtaining both a hysteretic and stress-dependent result for the magnetic-field-dependent Barkhausen noise envelope and obtaining specifically themore » almost linear stress dependence of the Barkhausen noise maximum experimentally. In this paper, we extend the model to derive the angular dependence observed by Kwun of the Barkhausen noise amplitude when stress axis is taken at different angles relative to magnetic field. We also apply the model to the experimental observation that in XC10 French steel, there is an apparent almost linear correlation with stress of hysteresis loss and of the integral of the Barkhausen noise signal over applied field {ital H}. Further, the two quantities, Barkhausen noise integral and hysteresis loss, are linearly correlated with each other. The model shows how that behavior is to be expected for the measured steel because of its sharply rising hysteresis curve. {copyright} {ital 1996 American Institute of Physics.}« less
Charge noise in quantum dot qubits: beyond the Markovian approximation.
NASA Astrophysics Data System (ADS)
Yang, Yuan-Chi; Friesen, Mark; Coppersmith, S. N.
Charge noise is a limiting factor in the performance of semiconductor quantum dot qubits, including both spin and charge qubits. In this work, we develop an analytical formalism for treating semiclassical noise beyond the Markovian approximation, which allows us to investigate noise models relevant for quantum dots, such as 1 / f noise. We apply our methods to both charge qubits and quantum dot hybrid qubits, and study the effects of charge noise on single-qubit rotations in these systems. The formalism is also directly applicable to the case of strong microwave driving, for which the rotating wave approximation breaks down. This work was supported in part by ARO (W911NF-12-0607) and ONR (N00014-15-1-0029), and the University of Wisconsin-Madison.
On estimating attenuation from the amplitude of the spectrally whitened ambient seismic field
NASA Astrophysics Data System (ADS)
Weemstra, Cornelis; Westra, Willem; Snieder, Roel; Boschi, Lapo
2014-06-01
Measuring attenuation on the basis of interferometric, receiver-receiver surface waves is a non-trivial task: the amplitude, more than the phase, of ensemble-averaged cross-correlations is strongly affected by non-uniformities in the ambient wavefield. In addition, ambient noise data are typically pre-processed in ways that affect the amplitude itself. Some authors have recently attempted to measure attenuation in receiver-receiver cross-correlations obtained after the usual pre-processing of seismic ambient-noise records, including, most notably, spectral whitening. Spectral whitening replaces the cross-spectrum with a unit amplitude spectrum. It is generally assumed that cross-terms have cancelled each other prior to spectral whitening. Cross-terms are peaks in the cross-correlation due to simultaneously acting noise sources, that is, spurious traveltime delays due to constructive interference of signal coming from different sources. Cancellation of these cross-terms is a requirement for the successful retrieval of interferometric receiver-receiver signal and results from ensemble averaging. In practice, ensemble averaging is replaced by integrating over sufficiently long time or averaging over several cross-correlation windows. Contrary to the general assumption, we show in this study that cross-terms are not required to cancel each other prior to spectral whitening, but may also cancel each other after the whitening procedure. Specifically, we derive an analytic approximation for the amplitude difference associated with the reversed order of cancellation and normalization. Our approximation shows that an amplitude decrease results from the reversed order. This decrease is predominantly non-linear at small receiver-receiver distances: at distances smaller than approximately two wavelengths, whitening prior to ensemble averaging causes a significantly stronger decay of the cross-spectrum.
The quasi-optimality criterion in the linear functional strategy
NASA Astrophysics Data System (ADS)
Kindermann, Stefan; Pereverzyev, Sergiy, Jr.; Pilipenko, Andrey
2018-07-01
The linear functional strategy for the regularization of inverse problems is considered. For selecting the regularization parameter therein, we propose the heuristic quasi-optimality principle and some modifications including the smoothness of the linear functionals. We prove convergence rates for the linear functional strategy with these heuristic rules taking into account the smoothness of the solution and the functionals and imposing a structural condition on the noise. Furthermore, we study these noise conditions in both a deterministic and stochastic setup and verify that for mildly-ill-posed problems and Gaussian noise, these conditions are satisfied almost surely, where on the contrary, in the severely-ill-posed case and in a similar setup, the corresponding noise condition fails to hold. Moreover, we propose an aggregation method for adaptively optimizing the parameter choice rule by making use of improved rates for linear functionals. Numerical results indicate that this method yields better results than the standard heuristic rule.
1976-04-09
of the signal and noise remain HH ***^-^*--~ 53 h, to r(Mc) h2(r» r(we) Figure 3-2 Sy&toetric Impulse Response for Two FIR Linear Phase...Inputs x,y and Outputs x.j. , 15 2-2 Linear System with Impulse Response h("r) 23 2-3 Model of Error Resulting from Linearly Filtering x(t) to...Corrupted with Additive Noise 42 2-6 Model of Directional Signal Corrupted with Additive Noise and Processed .... 45 2-7 Source Driving Two
Ultra-Fast Image Sensor Using Ge on Insulator MIS/Schottky Detectors
2008-05-28
electronic system. The noise equivalent power is defined as in /R, where in is the current noise and R is the responsivity. At 1 V, the current noise ...is limited by the dark current and can be approximated as the shot noise 2eIdf1/2, where Id is the measured dark current. At 0 V, the dark current...approaches zero, and the current noise should be approximated as Johnson noise 4kTGf1/2, where G is the measured conductance. Therefore, D* can be
Investigation of x-ray spectra for iodinated contrast-enhanced dedicated breast CT
Glick, Stephen J.; Makeev, Andrey
2017-01-01
Abstract. Screening for breast cancer with mammography has been very successful, resulting in part to a reduction of breast cancer mortality by approximately 39% since 1990. However, mammography still has limitations in performance, especially for women with dense breast tissue. Iodinated contrast-enhanced, dedicated breast CT (BCT) has been proposed to improve lesion analysis and the accuracy of diagnostic workup for patients suspected of having breast cancer. A mathematical analysis to explore the use of various x-ray filters for iodinated contrast-enhanced BCT is presented. To assess task-based performance, the ideal linear observer signal-to-noise ratio (SNR) is used as a figure-of-merit under the assumptions of a linear, shift-invariant imaging system. To estimate signal and noise propagation through the BCT detector, a parallel-cascade model was used. The lesion model was embedded into a structured background and included a realistic level of iodine uptake. SNR was computed for 84,000 different exposure settings by varying the kV setting, x-ray filter materials and thickness, breast size, and composition and radiation dose. It is shown that some x-ray filter material/thickness combinations can provide up to 75% improvement in the linear ideal observer SNR over a conventionally used x-ray filter for BCT. This improvement in SNR can be traded off for substantial reductions in mean glandular dose. PMID:28149923
Intensity position modulation for free-space laser communication system
NASA Astrophysics Data System (ADS)
Jangjoo, Alireza; Faghihi, F.
2004-12-01
In this research a novel modulation technique for free-space laser communication system called Intensity Position Modulation (IPM) is carried out. According to TEM00 mode of a laser beam and by linear fitting on the Gaussian function as an approximation, the variation of linear part on the reverse biased pn photodiode produced alternating currents which contain the information. Here, no characteristic property of the beam as intensity or frequency is changed and only the beam position moves laterally. We demonstrated that in this method no bandwidth is required, so it is possible to reduce the background radiation noise by narrowband filtering of the carrier. The fidelity of the analog voice communication system which is made upon the IPM is satisfactory and we are able to transmit the audio signals up to 1Km.
Characterization of a measurement-based noiseless linear amplifier and its applications
NASA Astrophysics Data System (ADS)
Zhao, Jie; Haw, Jing Yan; Symul, Thomas; Lam, Ping Koy; Assad, Syed M.
2017-07-01
A noiseless linear amplifier (NLA) adds no noise to the signals it processes, which works only in a probabilistic way. It can be realized approximately with either a physical implementation that truncates the working space of the NLA on a photon-number basis or a measurement-based implementation that realizes the truncation virtually by a bounded postselection filter. To examine the relationship between these two approximate NLAs, we characterize in detail the measurement-based NLA and compare it with its physical counterpart in terms of their abilities to preserve the state Gaussianity and their probability of success. The link between these amplifiers is further clarified by integrating them into a measure-and-prepare setup. We stress the equivalence between the physical and the measurement-based approaches holds only when the effective parameters, the amplification gain, the cutoff, and the amplitude of the input state, are taken into account. Finally, we construct a 1-to-infinity cloner using the two amplifiers and show that a fidelity surpassing the no-cloning limit is achievable with the measurement-based NLA.
NASA Astrophysics Data System (ADS)
Yang, Tao; Chen, Xue; Shi, Sheping; Sun, Erkun; Shi, Chen
2018-03-01
We propose a low-complexity and modulation-format-independent carrier phase estimation (CPE) scheme based on two-stage modified blind phase search (MBPS) with linear approximation to compensate the phase noise of arbitrary m-ary quadrature amplitude modulation (m-QAM) signals in elastic optical networks (EONs). Comprehensive numerical simulations are carried out in the case that the highest possible modulation format in EONs is 256-QAM. The simulation results not only verify its advantages of higher estimation accuracy and modulation-format independence, i.e., universality, but also demonstrate that the implementation complexity is significantly reduced by at least one-fourth in comparison with the traditional BPS scheme. In addition, the proposed scheme shows similar laser linewidth tolerance with the traditional BPS scheme. The slightly better OSNR performance of the scheme is also experimentally validated for PM-QPSK and PM-16QAM systems, respectively. The coexistent advantages of low-complexity and modulation-format-independence could make the proposed scheme an attractive candidate for flexible receiver-side DSP unit in EONs.
2017-09-27
ARL-TR-8161•SEP 2017 US Army Research Laboratory Excluding Noise from Short Krylov Subspace Approximations to the Truncated Singular Value...originator. ARL-TR-8161•SEP 2017 US Army Research Laboratory Excluding Noise from Short Krylov Subspace Approximations to the Truncated Singular Value...unlimited. October 2015–January 2016 US Army Research Laboratory ATTN: RDRL-CIH-C Aberdeen Proving Ground, MD 21005-5066 primary author’s email
Linear Space-Variant Image Restoration of Photon-Limited Images
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
NASA Astrophysics Data System (ADS)
Duan, Chaowei; Zhan, Yafeng
2016-03-01
The output characteristics of a linear monostable system driven with a periodic signal and an additive white Gaussian noise are studied in this paper. Theoretical analysis shows that the output signal-to-noise ratio (SNR) decreases monotonously with the increasing noise intensity but the output SNR-gain is stable. Inspired by this high SNR-gain phenomenon, this paper applies the linear monostable system in the parameters estimation algorithm for phase shift keying (PSK) signals and improves the estimation performance.
Structure of the Los Angeles Basin from Ambient Noise and Receiver Function Analysis
NASA Astrophysics Data System (ADS)
Clayton, R. W.; Ma, Y.; Cochran, E. S.
2015-12-01
We show the results from the LASSIE seismic experiment, which consists of a dense (1-km spacing) linear array of broadband stations deployed across the LA basin for approximately two months. Two common methods - ambient noise and receiver function (RF) - are applied to determine the velocity and structure of the basin. The basin RFs are complicated, however, the dense array enhances the lateral coherence of the signals and allows the structure to be imaged. The basement shape is clearly shown in the migrated image of the PpPs phase. The Ps conversion at the basement is the largest signal (including the direct wave) in the first 3 s. However, the Ps phase does not form as clear an image compared with the PpPs phase, possibly due to a requirement of more accurate velocity model. The surface wave signals from the ambient noise cross-correlations between LASSIE and surrounding SCSN stations are used for velocity inversion. A linear Dix-type inversion (Haney and Tsai, 2015, Geophysics) is applied to the extracted dispersion curves. The 1-10 s period Rayleigh wave and the 1-8 s period Love wave dispersion curves provide excellent constraints on top 5 km SV and top 3 km SH velocity structures respectively. Strong anisotropy (SV > SH) is observed for the top 1 km, and we plan to use this result to infer the fracture orientation and density of the shallow sedimentary rocks.
NASA Astrophysics Data System (ADS)
Madhav, B. T. P.; Pardhasaradhi, P.; Manepalli, R. K. N. R.; Pisipati, V. G. K. M.
2015-07-01
The compound undecyloxy benzoic acid (11Oba) exhibits nematic and smectic-C phases while a nano-doped undecyloxy benzoic acid with ZnO exhibits the same nematic and smectic-C phases with reduced clearing temperature as expected. The doping is done with 0.5% and 1% ZnO molecules. The clearing temperatures are reduced by approximately 4 ° and 6 °, respectively (differential scanning calorimeter data). While collecting the images from a polarizing microscope connected with hot stage and camera, the illumination and reflectance combined multiplicatively and the image quality was reduced to identify the exact phase in the compound. A novel technique of homomorphic filtering is used in this manuscript through which multiplicative noise components of the image are separated linearly in the frequency domain. This technique provides a frequency domain procedure to improve the appearance of an image by gray level range compression and contrast enhancement.
Effective equilibrium states in mixtures of active particles driven by colored noise
NASA Astrophysics Data System (ADS)
Wittmann, René; Brader, J. M.; Sharma, A.; Marconi, U. Marini Bettolo
2018-01-01
We consider the steady-state behavior of pairs of active particles having different persistence times and diffusivities. To this purpose we employ the active Ornstein-Uhlenbeck model, where the particles are driven by colored noises with exponential correlation functions whose intensities and correlation times vary from species to species. By extending Fox's theory to many components, we derive by functional calculus an approximate Fokker-Planck equation for the configurational distribution function of the system. After illustrating the predicted distribution in the solvable case of two particles interacting via a harmonic potential, we consider systems of particles repelling through inverse power-law potentials. We compare the analytic predictions to computer simulations for such soft-repulsive interactions in one dimension and show that at linear order in the persistence times the theory is satisfactory. This work provides the toolbox to qualitatively describe many-body phenomena, such as demixing and depletion, by means of effective pair potentials.
Image denoising in mixed Poisson-Gaussian noise.
Luisier, Florian; Blu, Thierry; Unser, Michael
2011-03-01
We propose a general methodology (PURE-LET) to design and optimize a wide class of transform-domain thresholding algorithms for denoising images corrupted by mixed Poisson-Gaussian noise. We express the denoising process as a linear expansion of thresholds (LET) that we optimize by relying on a purely data-adaptive unbiased estimate of the mean-squared error (MSE), derived in a non-Bayesian framework (PURE: Poisson-Gaussian unbiased risk estimate). We provide a practical approximation of this theoretical MSE estimate for the tractable optimization of arbitrary transform-domain thresholding. We then propose a pointwise estimator for undecimated filterbank transforms, which consists of subband-adaptive thresholding functions with signal-dependent thresholds that are globally optimized in the image domain. We finally demonstrate the potential of the proposed approach through extensive comparisons with state-of-the-art techniques that are specifically tailored to the estimation of Poisson intensities. We also present denoising results obtained on real images of low-count fluorescence microscopy.
NASA Astrophysics Data System (ADS)
Gross, Markus
2018-03-01
We consider a one-dimensional fluctuating interfacial profile governed by the Edwards–Wilkinson or the stochastic Mullins-Herring equation for periodic, standard Dirichlet and Dirichlet no-flux boundary conditions. The minimum action path of an interfacial fluctuation conditioned to reach a given maximum height M at a finite (first-passage) time T is calculated within the weak-noise approximation. Dynamic and static scaling functions for the profile shape are obtained in the transient and the equilibrium regime, i.e. for first-passage times T smaller or larger than the characteristic relaxation time, respectively. In both regimes, the profile approaches the maximum height M with a universal algebraic time dependence characterized solely by the dynamic exponent of the model. It is shown that, in the equilibrium regime, the spatial shape of the profile depends sensitively on boundary conditions and conservation laws, but it is essentially independent of them in the transient regime.
Asteroid orbital error analysis: Theory and application
NASA Technical Reports Server (NTRS)
Muinonen, K.; Bowell, Edward
1992-01-01
We present a rigorous Bayesian theory for asteroid orbital error estimation in which the probability density of the orbital elements is derived from the noise statistics of the observations. For Gaussian noise in a linearized approximation the probability density is also Gaussian, and the errors of the orbital elements at a given epoch are fully described by the covariance matrix. The law of error propagation can then be applied to calculate past and future positional uncertainty ellipsoids (Cappellari et al. 1976, Yeomans et al. 1987, Whipple et al. 1991). To our knowledge, this is the first time a Bayesian approach has been formulated for orbital element estimation. In contrast to the classical Fisherian school of statistics, the Bayesian school allows a priori information to be formally present in the final estimation. However, Bayesian estimation does give the same results as Fisherian estimation when no priori information is assumed (Lehtinen 1988, and reference therein).
Wiener Chaos and Nonlinear Filtering
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lototsky, S.V.
2006-11-15
The paper discusses two algorithms for solving the Zakai equation in the time-homogeneous diffusion filtering model with possible correlation between the state process and the observation noise. Both algorithms rely on the Cameron-Martin version of the Wiener chaos expansion, so that the approximate filter is a finite linear combination of the chaos elements generated by the observation process. The coefficients in the expansion depend only on the deterministic dynamics of the state and observation processes. For real-time applications, computing the coefficients in advance improves the performance of the algorithms in comparison with most other existing methods of nonlinear filtering. Themore » paper summarizes the main existing results about these Wiener chaos algorithms and resolves some open questions concerning the convergence of the algorithms in the noise-correlated setting. The presentation includes the necessary background on the Wiener chaos and optimal nonlinear filtering.« less
Can Anomalous Amplification be Attained without Postselection?
Martínez-Rincón, Julián; Liu, Wei-Tao; Viza, Gerardo I; Howell, John C
2016-03-11
We present a parameter estimation technique based on performing joint measurements of a weak interaction away from the weak-value-amplification approximation. Two detectors are used to collect full statistics of the correlations between two weakly entangled degrees of freedom. Without discarding of data, the protocol resembles the anomalous amplification of an imaginary-weak-value-like response. The amplification is induced in the difference signal of both detectors allowing robustness to different sources of technical noise, and offering in addition the advantages of balanced signals for precision metrology. All of the Fisher information about the parameter of interest is collected. A tunable phase controls the strength of the amplification response. We experimentally demonstrate the proposed technique by measuring polarization rotations in a linearly polarized laser pulse. We show that in the presence of technical noise the effective sensitivity and precision of a split detector is increased when compared to a conventional continuous-wave balanced detection technique.
Can Anomalous Amplification be Attained without Postselection?
NASA Astrophysics Data System (ADS)
Martínez-Rincón, Julián; Liu, Wei-Tao; Viza, Gerardo I.; Howell, John C.
2016-03-01
We present a parameter estimation technique based on performing joint measurements of a weak interaction away from the weak-value-amplification approximation. Two detectors are used to collect full statistics of the correlations between two weakly entangled degrees of freedom. Without discarding of data, the protocol resembles the anomalous amplification of an imaginary-weak-value-like response. The amplification is induced in the difference signal of both detectors allowing robustness to different sources of technical noise, and offering in addition the advantages of balanced signals for precision metrology. All of the Fisher information about the parameter of interest is collected. A tunable phase controls the strength of the amplification response. We experimentally demonstrate the proposed technique by measuring polarization rotations in a linearly polarized laser pulse. We show that in the presence of technical noise the effective sensitivity and precision of a split detector is increased when compared to a conventional continuous-wave balanced detection technique.
Nonlinear identification of the total baroreflex arc.
Moslehpour, Mohsen; Kawada, Toru; Sunagawa, Kenji; Sugimachi, Masaru; Mukkamala, Ramakrishna
2015-12-15
The total baroreflex arc [the open-loop system relating carotid sinus pressure (CSP) to arterial pressure (AP)] is known to exhibit nonlinear behaviors. However, few studies have quantitatively characterized its nonlinear dynamics. The aim of this study was to develop a nonlinear model of the sympathetically mediated total arc without assuming any model form. Normal rats were studied under anesthesia. The vagal and aortic depressor nerves were sectioned, the carotid sinus regions were isolated and attached to a servo-controlled piston pump, and the AP and sympathetic nerve activity (SNA) were measured. CSP was perturbed using a Gaussian white noise signal. A second-order Volterra model was developed by applying nonparametric identification to the measurements. The second-order kernel was mainly diagonal, but the diagonal differed in shape from the first-order kernel. Hence, a reduced second-order model was similarly developed comprising a linear dynamic system in parallel with a squaring system in cascade with a slower linear dynamic system. This "Uryson" model predicted AP changes 12% better (P < 0.01) than a linear model in response to new Gaussian white noise CSP. The model also predicted nonlinear behaviors, including thresholding and mean responses to CSP changes about the mean. Models of the neural arc (the system relating CSP to SNA) and peripheral arc (the system relating SNA to AP) were likewise developed and tested. However, these models of subsystems of the total arc showed approximately linear behaviors. In conclusion, the validated nonlinear model of the total arc revealed that the system takes on an Uryson structure. Copyright © 2015 the American Physiological Society.
Nonlinear identification of the total baroreflex arc
Moslehpour, Mohsen; Kawada, Toru; Sunagawa, Kenji; Sugimachi, Masaru
2015-01-01
The total baroreflex arc [the open-loop system relating carotid sinus pressure (CSP) to arterial pressure (AP)] is known to exhibit nonlinear behaviors. However, few studies have quantitatively characterized its nonlinear dynamics. The aim of this study was to develop a nonlinear model of the sympathetically mediated total arc without assuming any model form. Normal rats were studied under anesthesia. The vagal and aortic depressor nerves were sectioned, the carotid sinus regions were isolated and attached to a servo-controlled piston pump, and the AP and sympathetic nerve activity (SNA) were measured. CSP was perturbed using a Gaussian white noise signal. A second-order Volterra model was developed by applying nonparametric identification to the measurements. The second-order kernel was mainly diagonal, but the diagonal differed in shape from the first-order kernel. Hence, a reduced second-order model was similarly developed comprising a linear dynamic system in parallel with a squaring system in cascade with a slower linear dynamic system. This “Uryson” model predicted AP changes 12% better (P < 0.01) than a linear model in response to new Gaussian white noise CSP. The model also predicted nonlinear behaviors, including thresholding and mean responses to CSP changes about the mean. Models of the neural arc (the system relating CSP to SNA) and peripheral arc (the system relating SNA to AP) were likewise developed and tested. However, these models of subsystems of the total arc showed approximately linear behaviors. In conclusion, the validated nonlinear model of the total arc revealed that the system takes on an Uryson structure. PMID:26354845
White noise analysis of Phycomyces light growth response system. I. Normal intensity range.
Lipson, E D
1975-01-01
The Wiener-Lee-Schetzen method for the identification of a nonlinear system through white gaussian noise stimulation was applied to the transient light growth response of the sporangiophore of Phycomyces. In order to cover a moderate dynamic range of light intensity I, the imput variable was defined to be log I. The experiments were performed in the normal range of light intensity, centered about I0 = 10(-6) W/cm2. The kernels of the Wierner functionals were computed up to second order. Within the range of a few decades the system is reasonably linear with log I. The main nonlinear feature of the second-order kernel corresponds to the property of rectification. Power spectral analysis reveals that the slow dynamics of the system are of at least fifth order. The system can be represented approximately by a linear transfer function, including a first-order high-pass (adaptation) filter with a 4 min time constant and an underdamped fourth-order low-pass filter. Accordingly a linear electronic circuit was constructed to simulate the small scale response characteristics. In terms of the adaptation model of Delbrück and Reichardt (1956, in Cellular Mechanisms in Differentiation and Growth, Princeton University Press), kernels were deduced for the dynamic dependence of the growth velocity (output) on the "subjective intensity", a presumed internal variable. Finally the linear electronic simulator above was generalized to accommodate the large scale nonlinearity of the adaptation model and to serve as a tool for deeper test of the model. PMID:1203444
Linear dynamic range enhancement in a CMOS imager
NASA Technical Reports Server (NTRS)
Pain, Bedabrata (Inventor)
2008-01-01
A CMOS imager with increased linear dynamic range but without degradation in noise, responsivity, linearity, fixed-pattern noise, or photometric calibration comprises a linear calibrated dual gain pixel in which the gain is reduced after a pre-defined threshold level by switching in an additional capacitance. The pixel may include a novel on-pixel latch circuit that is used to switch in the additional capacitance.
The Prediction of Jet Noise Ground Effects Using an Acoustic Analogy and a Tailored Green's Function
NASA Technical Reports Server (NTRS)
Miller, Steven A. E.
2013-01-01
An assessment of an acoustic analogy for the mixing noise component of jet noise in the presence of an infinite surface is presented. The reflection of jet noise by the ground changes the distribution of acoustic energy and is characterized by constructive and destructive interference patterns. The equivalent sources are modeled based on the two-point cross- correlation of the turbulent velocity fluctuations and a steady Reynolds-Averaged Navier-Stokes (RANS) solution. Propagation effects, due to reflection by the surface and refaction by the jet shear layer, are taken into account by calculating the vector Green's function of the linearized Euler equations (LEE). The vector Green's function of the LEE is written in relation to Lilley's equation; that is, approximated with matched asymptotic solutions and the Green's function of the convective Helmholtz equation. The Green's function of the convective Helmholtz equation for an infinite flat plane with impedance is the Weyl-van der Pol equation. Predictions are compared with an unheated Mach 0.95 jet produced by a nozzle with an exit diameter of 0.3302 meters. Microphones are placed at various heights and distances from the nozzle exit in the peak jet noise direction above an acoustically hard and an asphalt surface. The predictions are shown to accurately capture jet noise ground effects that are characterized by constructive and destructive interference patterns in the mid- and far-field and capture overall trends in the near-field.
Mariano-Goulart, D; Fourcade, M; Bernon, J L; Rossi, M; Zanca, M
2003-01-01
Thanks to an experimental study based on simulated and physical phantoms, the propagation of the stochastic noise in slices reconstructed using the conjugate gradient algorithm has been analysed versus iterations. After a first increase corresponding to the reconstruction of the signal, the noise stabilises before increasing linearly with iterations. The level of the plateau as well as the slope of the subsequent linear increase depends on the noise in the projection data.
Estimating integrated variance in the presence of microstructure noise using linear regression
NASA Astrophysics Data System (ADS)
Holý, Vladimír
2017-07-01
Using financial high-frequency data for estimation of integrated variance of asset prices is beneficial but with increasing number of observations so-called microstructure noise occurs. This noise can significantly bias the realized variance estimator. We propose a method for estimation of the integrated variance robust to microstructure noise as well as for testing the presence of the noise. Our method utilizes linear regression in which realized variances estimated from different data subsamples act as dependent variable while the number of observations act as explanatory variable. We compare proposed estimator with other methods on simulated data for several microstructure noise structures.
A unified view on weakly correlated recurrent networks
Grytskyy, Dmytro; Tetzlaff, Tom; Diesmann, Markus; Helias, Moritz
2013-01-01
The diversity of neuron models used in contemporary theoretical neuroscience to investigate specific properties of covariances in the spiking activity raises the question how these models relate to each other. In particular it is hard to distinguish between generic properties of covariances and peculiarities due to the abstracted model. Here we present a unified view on pairwise covariances in recurrent networks in the irregular regime. We consider the binary neuron model, the leaky integrate-and-fire (LIF) model, and the Hawkes process. We show that linear approximation maps each of these models to either of two classes of linear rate models (LRM), including the Ornstein–Uhlenbeck process (OUP) as a special case. The distinction between both classes is the location of additive noise in the rate dynamics, which is located on the output side for spiking models and on the input side for the binary model. Both classes allow closed form solutions for the covariance. For output noise it separates into an echo term and a term due to correlated input. The unified framework enables us to transfer results between models. For example, we generalize the binary model and the Hawkes process to the situation with synaptic conduction delays and simplify derivations for established results. Our approach is applicable to general network structures and suitable for the calculation of population averages. The derived averages are exact for fixed out-degree network architectures and approximate for fixed in-degree. We demonstrate how taking into account fluctuations in the linearization procedure increases the accuracy of the effective theory and we explain the class dependent differences between covariances in the time and the frequency domain. Finally we show that the oscillatory instability emerging in networks of LIF models with delayed inhibitory feedback is a model-invariant feature: the same structure of poles in the complex frequency plane determines the population power spectra. PMID:24151463
NASA Astrophysics Data System (ADS)
Bogachev, Mikhail I.; Bunde, Armin
2011-06-01
We study the predictability of extreme events in records with linear and nonlinear long-range memory in the presence of additive white noise using two different approaches: (i) the precursory pattern recognition technique (PRT) that exploits solely the information about short-term precursors, and (ii) the return interval approach (RIA) that exploits long-range memory incorporated in the elapsed time after the last extreme event. We find that the PRT always performs better when only linear memory is present. In the presence of nonlinear memory, both methods demonstrate comparable efficiency in the absence of white noise. When additional white noise is present in the record (which is the case in most observational records), the efficiency of the PRT decreases monotonously with increasing noise level. In contrast, the RIA shows an abrupt transition between a phase of low level noise where the prediction is as good as in the absence of noise, and a phase of high level noise where the prediction becomes poor. In the phase of low and intermediate noise the RIA predicts considerably better than the PRT, which explains our recent findings in physiological and financial records.
NASA Astrophysics Data System (ADS)
Gross, Markus
2018-03-01
A fluctuating interfacial profile in one dimension is studied via Langevin simulations of the Edwards–Wilkinson equation with non-conserved noise and the Mullins–Herring equation with conserved noise. The profile is subject to either periodic or Dirichlet (no-flux) boundary conditions. We determine the noise-driven time-evolution of the profile between an initially flat configuration and the instant at which the profile reaches a given height M for the first time. The shape of the averaged profile agrees well with the prediction of weak-noise theory (WNT), which describes the most-likely trajectory to a fixed first-passage time. Furthermore, in agreement with WNT, on average the profile approaches the height M algebraically in time, with an exponent that is essentially independent of the boundary conditions. However, the actual value of the dynamic exponent turns out to be significantly smaller than predicted by WNT. This ‘renormalization’ of the exponent is explained in terms of the entropic repulsion exerted by the impenetrable boundary on the fluctuations of the profile around its most-likely path. The entropic repulsion mechanism is analyzed in detail for a single (fractional) Brownian walker, which describes the anomalous diffusion of a tagged monomer of the interface as it approaches the absorbing boundary. The present study sheds light on the accuracy and the limitations of the weak-noise approximation for the description of the full first-passage dynamics.
NASA Technical Reports Server (NTRS)
Hilton, D. A.; Henderson, H. R.; Maglieri, D. J.; Bigler, W. B., II
1978-01-01
In order to expand the data base of helicopter external noise characteristics, a flyover noise measurement program was conducted utilizing the NASA Civil Helicopter Research Aircraft. The remotely operated multiple array acoustics range (ROMAAR) and a 2560-m linear microphone array were utilized for the purpose of documenting the noise characteristics of the test helicopter during flyby and landing operations. By utilizing both ROMAAR concept and the linear array, the data necessary to plot the ground noise footprints and noise radiation patterns were obtained. Examples of the measured noise signature of the test helicopter, the ground noise footprint or contours, and the directivity patterns measured during level flyby and landing operations of a large, multibladed, nonbanging helicopter, the CH-53, are presented.
VINSON/AUTOVON Interface Applique for the Modem, Digital Data, AN/GSC-38
1980-11-01
Measurement Indication Result Before Step 6 None Noise and beeping are heard in handset After Step 7 None Noise and beepi ng disappear Condition Measurement...linear range due to the compression used. Lowering the levels below the compression range may give increased linearity, but may cause signal-to- noise ...are encountered where the bit error rate at 16 KB/S results is objectionable audio noise or causes the KY-58 to squelch. On these channels the bit
Aliabadi, Mohsen; Golmohammadi, Rostam; Mansoorizadeh, Muharram
2014-03-01
It is highly important to analyze the acoustic properties of workrooms in order to identify best noise control measures from the standpoint of noise exposure limits. Due to the fact that sound pressure is dependent upon environments, it cannot be a suitable parameter for determining the share of workroom acoustic characteristics in producing noise pollution. This paper aims to empirically analyze noise source characteristics and acoustic properties of noisy embroidery workrooms based on special parameters. In this regard, reverberation time as the special room acoustic parameter in 30 workrooms was measured based on ISO 3382-2. Sound power quantity of embroidery machines was also determined based on ISO 9614-3. Multiple linear regression was employed for predicting reverberation time based on acoustic features of the workrooms using MATLAB software. The results showed that the measured reverberation times in most of the workrooms were approximately within the ranges recommended by ISO 11690-1. Similarity between reverberation time values calculated by the Sabine formula and measured values was relatively poor (R (2) = 0.39). This can be due to the inaccurate estimation of the acoustic influence of furniture and formula preconditions. Therefore, this value cannot be considered representative of an actual acoustic room. However, the prediction performance of the regression method with root mean square error (RMSE) = 0.23 s and R (2) = 0.69 is relatively acceptable. Because the sound power of the embroidery machines was relatively high, these sources get the highest priority when it comes to applying noise controls. Finally, an objective approach for the determination of the share of workroom acoustic characteristics in producing noise could facilitate the identification of cost-effective noise controls.
Akkar, Sinan; Boore, David M.
2009-01-01
Most digital accelerograph recordings are plagued by long-period drifts, best seen in the velocity and displacement time series obtained from integration of the acceleration time series. These drifts often result in velocity values that are nonzero near the end of the record. This is clearly unphysical and can lead to inaccurate estimates of peak ground displacement and long-period spectral response. The source of the long-period noise seems to be variations in the acceleration baseline in many cases. These variations could be due to true ground motion (tilting and rotation, as well as local permanent ground deformation), instrumental effects, or analog-to-digital conversion. Very often the trends in velocity are well approximated by a linear trend after the strong shaking subsides. The linearity of the trend in velocity implies that no variations in the baseline could have occurred after the onset of linearity in the velocity time series. This observation, combined with the lack of any trends in the pre-event motion, allows us to compute the time interval in which any baseline variations could occur. We then use several models of the variations in a Monte Carlo procedure to derive a suite of baseline-corrected accelerations for each noise model using records from the 1999 Chi-Chi earthquake and several earthquakes in Turkey. Comparisons of the mean values of the peak ground displacements, spectral displacements, and residual displacements computed from these corrected accelerations for the different noise models can be used as a guide to the accuracy of the baseline corrections. For many of the records considered here the mean values are similar for each noise model, giving confidence in the estimation of the mean values. The dispersion of the ground-motion measures increases with period and is noise-model dependent. The dispersion of inelastic spectra is greater than the elastic spectra at short periods but approaches that of the elastic spectra at longer periods. The elastic spectra from the most basic processing, in which only the pre-event mean is removed from the acceleration time series, do not diverge from the baseline-corrected spectra until periods of 10-20 sec or more for the records studied here, implying that for many engineering purposes elastic spectra can be used from records with no baseline correction or filtering.
Enhancing Security of Double Random Phase Encoding Based on Random S-Box
NASA Astrophysics Data System (ADS)
Girija, R.; Singh, Hukum
2018-06-01
In this paper, we propose a novel asymmetric cryptosystem for double random phase encoding (DRPE) using random S-Box. While utilising S-Box separately is not reliable and DRPE does not support non-linearity, so, our system unites the effectiveness of S-Box with an asymmetric system of DRPE (through Fourier transform). The uniqueness of proposed cryptosystem lies on employing high sensitivity dynamic S-Box for our DRPE system. The randomness and scalability achieved due to applied technique is an additional feature of the proposed solution. The firmness of random S-Box is investigated in terms of performance parameters such as non-linearity, strict avalanche criterion, bit independence criterion, linear and differential approximation probabilities etc. S-Boxes convey nonlinearity to cryptosystems which is a significant parameter and very essential for DRPE. The strength of proposed cryptosystem has been analysed using various parameters such as MSE, PSNR, correlation coefficient analysis, noise analysis, SVD analysis, etc. Experimental results are conferred in detail to exhibit proposed cryptosystem is highly secure.
NASA Technical Reports Server (NTRS)
Cooper, D. B.; Yalabik, N.
1975-01-01
Approximation of noisy data in the plane by straight lines or elliptic or single-branch hyperbolic curve segments arises in pattern recognition, data compaction, and other problems. The efficient search for and approximation of data by such curves were examined. Recursive least-squares linear curve-fitting was used, and ellipses and hyperbolas are parameterized as quadratic functions in x and y. The error minimized by the algorithm is interpreted, and central processing unit (CPU) times for estimating parameters for fitting straight lines and quadratic curves were determined and compared. CPU time for data search was also determined for the case of straight line fitting. Quadratic curve fitting is shown to require about six times as much CPU time as does straight line fitting, and curves relating CPU time and fitting error were determined for straight line fitting. Results are derived on early sequential determination of whether or not the underlying curve is a straight line.
Sensory Information Processing
1975-12-31
system noise . To see how this is avoided, note that zeroes in the blur spectrum become sharp, spike-like negative «*»• Page impulses when the...Synthetic Speech Quality Using Binaural Reverberation-- Boll 12 13 Section 4. Noise Suppression with Linear Prediction Filtering—Peterson 24 Section...5. Speech Processing to Reduce Noise and Improve Intelligibility— Callahan 28 Section 6. Linear Predictive Coding with a Glottal 36 Section 7
NASA Technical Reports Server (NTRS)
Wu, Andy
1995-01-01
Allan Deviation computations of linear frequency synthesizer systems have been reported previously using real-time simulations. Even though it takes less time compared with the actual measurement, it is still very time consuming to compute the Allan Deviation for long sample times with the desired confidence level. Also noises, such as flicker phase noise and flicker frequency noise, can not be simulated precisely. The use of frequency domain techniques can overcome these drawbacks. In this paper the system error model of a fictitious linear frequency synthesizer is developed and its performance using a Cesium (Cs) atomic frequency standard (AFS) as a reference is evaluated using frequency domain techniques. For a linear timing system, the power spectral density at the system output can be computed with known system transfer functions and known power spectral densities from the input noise sources. The resulting power spectral density can then be used to compute the Allan Variance at the system output. Sensitivities of the Allan Variance at the system output to each of its independent input noises are obtained, and they are valuable for design trade-off and trouble-shooting.
Vibration and noise analysis of a gear transmission system
NASA Technical Reports Server (NTRS)
Choy, F. K.; Qian, W.; Zakrajsek, J. J.; Oswald, F. B.
1993-01-01
This paper presents a comprehensive procedure to predict both the vibration and noise generated by a gear transmission system under normal operating conditions. The gearbox vibrations were obtained from both numerical simulation and experimental studies using a gear noise test rig. In addition, the noise generated by the gearbox vibrations was recorded during the experimental testing. A numerical method was used to develop linear relationships between the gearbox vibration and the generated noise. The hypercoherence function is introduced to correlate the nonlinear relationship between the fundamental noise frequency and its harmonics. A numerical procedure was developed using both the linear and nonlinear relationships generated from the experimental data to predict noise resulting from the gearbox vibrations. The application of this methodology is demonstrated by comparing the numerical and experimental results from the gear noise test rig.
On optimal control of linear systems in the presence of multiplicative noise
NASA Technical Reports Server (NTRS)
Joshi, S. M.
1976-01-01
This correspondence considers the problem of optimal regulator design for discrete time linear systems subjected to white state-dependent and control-dependent noise in addition to additive white noise in the input and the observations. A pseudo-deterministic problem is first defined in which multiplicative and additive input disturbances are present, but noise-free measurements of the complete state vector are available. This problem is solved via discrete dynamic programming. Next is formulated the problem in which the number of measurements is less than that of the state variables and the measurements are contaminated with state-dependent noise. The inseparability of control and estimation is brought into focus, and an 'enforced separation' solution is obtained via heuristic reasoning in which the control gains are shown to be the same as those in the pseudo-deterministic problem. An optimal linear state estimator is given in order to implement the controller.
Techniques for measurement of thoracoabdominal asynchrony
NASA Technical Reports Server (NTRS)
Prisk, G. Kim; Hammer, J.; Newth, Christopher J L.
2002-01-01
Respiratory motion measured by respiratory inductance plethysmography often deviates from the sinusoidal pattern assumed in the traditional Lissajous figure (loop) analysis used to determine thoraco-abdominal asynchrony, or phase angle phi. We investigated six different time-domain methods of measuring phi, using simulated data with sinusoidal and triangular waveforms, phase shifts of 0-135 degrees, and 10% noise. The techniques were then used on data from 11 lightly anesthetized rhesus monkeys (Macaca mulatta; 7.6 +/- 0.8 kg; 5.7 +/- 0.5 years old), instrumented with a respiratory inductive plethysmograph, and subjected to increasing levels of inspiratory resistive loading ranging from 5-1,000 cmH(2)O. L(-1). sec(-1).The best results were obtained from cross-correlation and maximum linear correlation, with errors less than approximately 5 degrees from the actual phase angle in the simulated data. The worst performance was produced by the loop analysis, which in some cases was in error by more than 30 degrees. Compared to correlation, other analysis techniques performed at an intermediate level. Maximum linear correlation and cross-correlation produced similar results on the data collected from monkeys (SD of the difference, 4.1 degrees ) but all other techniques had a high SD of the difference compared to the correlation techniques.We conclude that phase angles are best measured using cross-correlation or maximum linear correlation, techniques that are independent of waveform shape, and robust in the presence of noise. Copyright 2002 Wiley-Liss, Inc.
NASA Astrophysics Data System (ADS)
Dittmann, Niklas; Splettstoesser, Janine; Helbig, Nicole
2018-03-01
We calculate the frequency-dependent equilibrium noise of a mesoscopic capacitor in time-dependent density functional theory (TDDFT). The capacitor is modeled as a single-level quantum dot with on-site Coulomb interaction and tunnel coupling to a nearby reservoir. The noise spectra are derived from linear-response conductances via the fluctuation-dissipation theorem. Thereby, we analyze the performance of a recently derived exchange-correlation potential with time-nonlocal density dependence in the finite-frequency linear-response regime. We compare our TDDFT noise spectra with real-time perturbation theory and find excellent agreement for noise frequencies below the reservoir temperature.
Huppert, Theodore J
2016-01-01
Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique that uses low levels of light to measure changes in cerebral blood oxygenation levels. In the majority of NIRS functional brain studies, analysis of this data is based on a statistical comparison of hemodynamic levels between a baseline and task or between multiple task conditions by means of a linear regression model: the so-called general linear model. Although these methods are similar to their implementation in other fields, particularly for functional magnetic resonance imaging, the specific application of these methods in fNIRS research differs in several key ways related to the sources of noise and artifacts unique to fNIRS. In this brief communication, we discuss the application of linear regression models in fNIRS and the modifications needed to generalize these models in order to deal with structured (colored) noise due to systemic physiology and noise heteroscedasticity due to motion artifacts. The objective of this work is to present an overview of these noise properties in the context of the linear model as it applies to fNIRS data. This work is aimed at explaining these mathematical issues to the general fNIRS experimental researcher but is not intended to be a complete mathematical treatment of these concepts.
Electrical NEP in Hot-Electron Titanium Superconducting Bolometers
NASA Technical Reports Server (NTRS)
Karasik, Boris S.; Pereverzev, Sergey V.; Olaya, David; Wei, Jian; Gershenson, Michael E.; Sergeev, Andrei V.
2008-01-01
We are presenting the current progress on the titanium (Ti) hot-electron transition-edge devices. The ultimate goal of this work is to develop a submillimeter Hot-Electron Direct Detector (HEDD) with the noise equivalent power NEP = 10(sup -1) - 10(sup -20) W/Hz(sup 1/2) for the moderate resolution spectroscopy and Cosmic Microwave Background (CMB) studies on future space telescope (e.g., SPICA, SAFIR, SPECS, CMBPol) with cryogenically cooled (approximately 4-5 K) mirrors. Recently, we have achieved the extremely low thermal conductance (approximately 20 fW/K at 300 mK and approximately 0.1 fW/K at 40 mK) due to the electron-phonon decoupling in Ti nanodevices with niobium (Nb) Andreev contacts. This thermal conductance translates into the "phonon-noise" NEP approximately equal to 3 x 10(sup -21) W/Hz(sup 1/2) at 40 mK and NEP approximately equal to 3 x 10(sup -19) W/Hz(sup 1/2) at 300 mK. These record data indicate the great potential of the hot-electron detector for meeting many application needs. Beside the extremely low phonon-noise NEP, the nanobolometers have a very low electron heat capacitance that makes them promising as detectors of single THz photons. As the next step towards the practical demonstration of the HEDD, we fabricated and tested somewhat larger than in Ref.1 devices (approximately 6 micrometers x 0.35 micrometers x 40 nm) whose critical temperature is well reproduced in the range 300-350 mK. The output electrical noise measured in these devices with a low-noise dc SQUID is dominated by the thermal energy fluctuations (ETF) aka "phonon noise". This indicates the high electrothermal loop gain that effectively suppresses the contributions of the Johnson noise and the amplifier (SQUID) noise. The electrical NEP = 6.7 x 10(sup -18) W/Hz(sup 1/2) derived from these measurements is in good agreement with the predictions based on the thermal conductance data. The very low NEP and the high speed (approximately microns) are a unique combination not found in other detectors.
Kallehauge, Jesper F; Sourbron, Steven; Irving, Benjamin; Tanderup, Kari; Schnabel, Julia A; Chappell, Michael A
2017-06-01
Fitting tracer kinetic models using linear methods is much faster than using their nonlinear counterparts, although this comes often at the expense of reduced accuracy and precision. The aim of this study was to derive and compare the performance of the linear compartmental tissue uptake (CTU) model with its nonlinear version with respect to their percentage error and precision. The linear and nonlinear CTU models were initially compared using simulations with varying noise and temporal sampling. Subsequently, the clinical applicability of the linear model was demonstrated on 14 patients with locally advanced cervical cancer examined with dynamic contrast-enhanced magnetic resonance imaging. Simulations revealed equal percentage error and precision when noise was within clinical achievable ranges (contrast-to-noise ratio >10). The linear method was significantly faster than the nonlinear method, with a minimum speedup of around 230 across all tested sampling rates. Clinical analysis revealed that parameters estimated using the linear and nonlinear CTU model were highly correlated (ρ ≥ 0.95). The linear CTU model is computationally more efficient and more stable against temporal downsampling, whereas the nonlinear method is more robust to variations in noise. The two methods may be used interchangeably within clinical achievable ranges of temporal sampling and noise. Magn Reson Med 77:2414-2423, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.
Zeng, Rongping; Petrick, Nicholas; Gavrielides, Marios A; Myers, Kyle J
2011-10-07
Multi-slice computed tomography (MSCT) scanners have become popular volumetric imaging tools. Deterministic and random properties of the resulting CT scans have been studied in the literature. Due to the large number of voxels in the three-dimensional (3D) volumetric dataset, full characterization of the noise covariance in MSCT scans is difficult to tackle. However, as usage of such datasets for quantitative disease diagnosis grows, so does the importance of understanding the noise properties because of their effect on the accuracy of the clinical outcome. The goal of this work is to study noise covariance in the helical MSCT volumetric dataset. We explore possible approximations to the noise covariance matrix with reduced degrees of freedom, including voxel-based variance, one-dimensional (1D) correlation, two-dimensional (2D) in-plane correlation and the noise power spectrum (NPS). We further examine the effect of various noise covariance models on the accuracy of a prewhitening matched filter nodule size estimation strategy. Our simulation results suggest that the 1D longitudinal, 2D in-plane and NPS prewhitening approaches can improve the performance of nodule size estimation algorithms. When taking into account computational costs in determining noise characterizations, the NPS model may be the most efficient approximation to the MSCT noise covariance matrix.
Acoustics of laminar boundary layers breakdown
NASA Technical Reports Server (NTRS)
Wang, Meng
1994-01-01
Boundary layer flow transition has long been suggested as a potential noise source in both marine (sonar-dome self noise) and aeronautical (aircraft cabin noise) applications, owing to the highly transient nature of process. The design of effective noise control strategies relies upon a clear understanding of the source mechanisms associated with the unsteady flow dynamics during transition. Due to formidable mathematical difficulties, theoretical predictions either are limited to early linear and weakly nonlinear stages of transition, or employ acoustic analogy theories based on approximate source field data, often in the form of empirical correlation. In the present work, an approach which combines direct numerical simulation of the source field with the Lighthill acoustic analogy is utilized. This approach takes advantage of the recent advancement in computational capabilities to obtain detailed information about the flow-induced acoustic sources. The transitional boundary layer flow is computed by solving the incompressible Navier-Stokes equations without model assumptions, thus allowing a direct evaluation of the pseudosound as well as source functions, including the Lighthill stress tensor and the wall shear stress. The latter are used for calculating the radiated pressure field based on the Curle-Powell solution of the Lighthill equation. This procedure allows a quantitative assessment of noise source mechanisms and the associated radiation characteristics during transition from primary instability up to the laminar breakdown stage. In particular, one is interested in comparing the roles played by the fluctuating volume Reynolds stress and the wall-shear-stresses, and in identifying specific flow processes and structures that are effective noise generators.
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.
Kim, Kyung Hyuk; Sauro, Herbert M
2015-01-01
This chapter introduces a computational analysis method for analyzing gene circuit dynamics in terms of modules while taking into account stochasticity, system nonlinearity, and retroactivity. (1) ANALOG ELECTRICAL CIRCUIT REPRESENTATION FOR GENE CIRCUITS: A connection between two gene circuit components is often mediated by a transcription factor (TF) and the connection signal is described by the TF concentration. The TF is sequestered to its specific binding site (promoter region) and regulates downstream transcription. This sequestration has been known to affect the dynamics of the TF by increasing its response time. The downstream effect-retroactivity-has been shown to be explicitly described in an electrical circuit representation, as an input capacitance increase. We provide a brief review on this topic. (2) MODULAR DESCRIPTION OF NOISE PROPAGATION: Gene circuit signals are noisy due to the random nature of biological reactions. The noisy fluctuations in TF concentrations affect downstream regulation. Thus, noise can propagate throughout the connected system components. This can cause different circuit components to behave in a statistically dependent manner, hampering a modular analysis. Here, we show that the modular analysis is still possible at the linear noise approximation level. (3) NOISE EFFECT ON MODULE INPUT-OUTPUT RESPONSE: We investigate how to deal with a module input-output response and its noise dependency. Noise-induced phenotypes are described as an interplay between system nonlinearity and signal noise. Lastly, we provide the comprehensive approach incorporating the above three analysis methods, which we call "stochastic modular analysis." This method can provide an analysis framework for gene circuit dynamics when the nontrivial effects of retroactivity, stochasticity, and nonlinearity need to be taken into account.
Study of image matching algorithm and sub-pixel fitting algorithm in target tracking
NASA Astrophysics Data System (ADS)
Yang, Ming-dong; Jia, Jianjun; Qiang, Jia; Wang, Jian-yu
2015-03-01
Image correlation matching is a tracking method that searched a region most approximate to the target template based on the correlation measure between two images. Because there is no need to segment the image, and the computation of this method is little. Image correlation matching is a basic method of target tracking. This paper mainly studies the image matching algorithm of gray scale image, which precision is at sub-pixel level. The matching algorithm used in this paper is SAD (Sum of Absolute Difference) method. This method excels in real-time systems because of its low computation complexity. The SAD method is introduced firstly and the most frequently used sub-pixel fitting algorithms are introduced at the meantime. These fitting algorithms can't be used in real-time systems because they are too complex. However, target tracking often requires high real-time performance, we put forward a fitting algorithm named paraboloidal fitting algorithm based on the consideration above, this algorithm is simple and realized easily in real-time system. The result of this algorithm is compared with that of surface fitting algorithm through image matching simulation. By comparison, the precision difference between these two algorithms is little, it's less than 0.01pixel. In order to research the influence of target rotation on precision of image matching, the experiment of camera rotation was carried on. The detector used in the camera is a CMOS detector. It is fixed to an arc pendulum table, take pictures when the camera rotated different angles. Choose a subarea in the original picture as the template, and search the best matching spot using image matching algorithm mentioned above. The result shows that the matching error is bigger when the target rotation angle is larger. It's an approximate linear relation. Finally, the influence of noise on matching precision was researched. Gaussian noise and pepper and salt noise were added in the image respectively, and the image was processed by mean filter and median filter, then image matching was processed. The result show that when the noise is little, mean filter and median filter can achieve a good result. But when the noise density of salt and pepper noise is bigger than 0.4, or the variance of Gaussian noise is bigger than 0.0015, the result of image matching will be wrong.
Baldwin, Alex S.; Baker, Daniel H.; Hess, Robert F.
2016-01-01
The internal noise present in a linear system can be quantified by the equivalent noise method. By measuring the effect that applying external noise to the system’s input has on its output one can estimate the variance of this internal noise. By applying this simple “linear amplifier” model to the human visual system, one can entirely explain an observer’s detection performance by a combination of the internal noise variance and their efficiency relative to an ideal observer. Studies using this method rely on two crucial factors: firstly that the external noise in their stimuli behaves like the visual system’s internal noise in the dimension of interest, and secondly that the assumptions underlying their model are correct (e.g. linearity). Here we explore the effects of these two factors while applying the equivalent noise method to investigate the contrast sensitivity function (CSF). We compare the results at 0.5 and 6 c/deg from the equivalent noise method against those we would expect based on pedestal masking data collected from the same observers. We find that the loss of sensitivity with increasing spatial frequency results from changes in the saturation constant of the gain control nonlinearity, and that this only masquerades as a change in internal noise under the equivalent noise method. Part of the effect we find can be attributed to the optical transfer function of the eye. The remainder can be explained by either changes in effective input gain, divisive suppression, or a combination of the two. Given these effects the efficiency of our observers approaches the ideal level. We show the importance of considering these factors in equivalent noise studies. PMID:26953796
Baldwin, Alex S; Baker, Daniel H; Hess, Robert F
2016-01-01
The internal noise present in a linear system can be quantified by the equivalent noise method. By measuring the effect that applying external noise to the system's input has on its output one can estimate the variance of this internal noise. By applying this simple "linear amplifier" model to the human visual system, one can entirely explain an observer's detection performance by a combination of the internal noise variance and their efficiency relative to an ideal observer. Studies using this method rely on two crucial factors: firstly that the external noise in their stimuli behaves like the visual system's internal noise in the dimension of interest, and secondly that the assumptions underlying their model are correct (e.g. linearity). Here we explore the effects of these two factors while applying the equivalent noise method to investigate the contrast sensitivity function (CSF). We compare the results at 0.5 and 6 c/deg from the equivalent noise method against those we would expect based on pedestal masking data collected from the same observers. We find that the loss of sensitivity with increasing spatial frequency results from changes in the saturation constant of the gain control nonlinearity, and that this only masquerades as a change in internal noise under the equivalent noise method. Part of the effect we find can be attributed to the optical transfer function of the eye. The remainder can be explained by either changes in effective input gain, divisive suppression, or a combination of the two. Given these effects the efficiency of our observers approaches the ideal level. We show the importance of considering these factors in equivalent noise studies.
Enhancement of flow measurements using fluid-dynamic constraints
NASA Astrophysics Data System (ADS)
Egger, H.; Seitz, T.; Tropea, C.
2017-09-01
Novel experimental modalities acquire spatially resolved velocity measurements for steady state and transient flows which are of interest for engineering and biological applications. One of the drawbacks of such high resolution velocity data is their susceptibility to measurement errors. In this paper, we propose a novel filtering strategy that allows enhancement of the noisy measurements to obtain reconstruction of smooth divergence free velocity and corresponding pressure fields which together approximately comply to a prescribed flow model. The main step in our approach consists of the appropriate use of the velocity measurements in the design of a linearized flow model which can be shown to be well-posed and consistent with the true velocity and pressure fields up to measurement and modeling errors. The reconstruction procedure is then formulated as an optimal control problem for this linearized flow model. The resulting filter has analyzable smoothing and approximation properties. We briefly discuss the discretization of the approach by finite element methods and comment on the efficient solution by iterative methods. The capability of the proposed filter to significantly reduce data noise is demonstrated by numerical tests including the application to experimental data. In addition, we compare with other methods like smoothing and solenoidal filtering.
The effects of correlated noise in intra-complex DSN arrays for S-band Galileo telemetry reception
NASA Technical Reports Server (NTRS)
Dewey, R. J.
1992-01-01
A number of the proposals for supporting a Galileo S-band (2.3-GHz) mission involve arraying several antennas to maximize the signal-to-noise ratio (and bit rate) obtainable from a given set of antennas. Arraying is no longer a new idea, having been used successfully during the Voyager encounters with Uranus and Neptune. However, arraying for Galileo's tour of Jupiter is complicated by Jupiter's strong radio emission, which produces correlated noise effects. This article discusses the general problem of correlated noise due to a planet, or other radio source, and applies the results to the specific case of an array of antennas at the DSN's Tidbinbilla, Australia, complex (DSS 42, DSS 43, DSS 45, and the yet-to-be-built DSS 34). The effects of correlated noise are highly dependent on the specific geometry of the array and on the spacecraft-planet configuration; in some cases, correlated noise effects produce an enhancement, rather than a degradation, of the signal-to-noise ratio. For the case considered here--an array of the DSN's Australian antennas observing Galileo and Jupiter--there are three regimes of interest. If the spacecraft-planet separation is approximately less than 75 arcsec, the average effect of correlated noise is a loss of signal to noise (approximately 0.2 dB as the spacecraft-planet separation approaches zero). For spacecraft-planet separations approximately greater than 75 arcsec, but approximately less than 400 arcsec, the effects of correlated noise cause signal-to-noise variations as large as several tenths of a decibel over time scales of hours or changes in spacecraft-planet separation of tens of arcseconds; however, on average its effects are small (less than 0.01 dB). When the spacecraft is more than 400 arcsec from Jupiter (as is the case for about half of Galileo's tour), correlated noise is a less than 0.05-dB effect.
Kittell, Aaron W.; Camenisch, Theodore G.; Ratke, Joseph J.; Sidabras, Jason W.; Hyde, James S.
2011-01-01
A continuous wave (CW) electron paramagnetic resonance (EPR) spectrum is typically displayed as the first harmonic response to the application of 100 kHz magnetic field modulation, which is used to enhance sensitivity by reducing the level of 1/f noise. However, magnetic field modulation of any amplitude causes spectral broadening and sacrifices EPR spectral intensity by at least a factor of two. In the work presented here, a CW rapid-scan spectroscopic technique that avoids these compromises and also provides a means of avoiding 1/f noise is developed. This technique, termed non-adiabatic rapid sweep (NARS) EPR, consists of repetitively sweeping the polarizing magnetic field in a linear manner over a spectral fragment with a small coil at a repetition rate that is sufficiently high that receiver noise, microwave phase noise, and environmental microphonics, each of which has 1/f characteristics, are overcome. Nevertheless, the rate of sweep is sufficiently slow that adiabatic responses are avoided and the spin system is always close to thermal equilibrium. The repetitively acquired spectra from the spectral fragment are averaged. Under these conditions, undistorted pure absorption spectra are obtained without broadening or loss of signal intensity. A digital filter such as a moving average is applied to remove high frequency noise, which is approximately equivalent in bandwidth to use of an integrating time constant in conventional field modulation with lock-in detection. Nitroxide spectra at L- and X-band are presented. PMID:21741868
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.
Diesel-Powered Heavy-Duty Refrigeration Unit Noise
DOT National Transportation Integrated Search
1976-01-01
A series of noise measurements were performed on a diesel-powered heavy-duty refrigeration unit. Noise survey information collected included: polar plots of the 'A Weighted' noise levels of the unit under maximum and minimum load conditions; a linear...
Multiscale morphological filtering for analysis of noisy and complex images
NASA Astrophysics Data System (ADS)
Kher, A.; Mitra, S.
Images acquired with passive sensing techniques suffer from illumination variations and poor local contrasts that create major difficulties in interpretation and identification tasks. On the other hand, images acquired with active sensing techniques based on monochromatic illumination are degraded with speckle noise. Mathematical morphology offers elegant techniques to handle a wide range of image degradation problems. Unlike linear filters, morphological filters do not blur the edges and hence maintain higher image resolution. Their rich mathematical framework facilitates the design and analysis of these filters as well as their hardware implementation. Morphological filters are easier to implement and are more cost effective and efficient than several conventional linear filters. Morphological filters to remove speckle noise while maintaining high resolution and preserving thin image regions that are particularly vulnerable to speckle noise were developed and applied to SAR imagery. These filters used combination of linear (one-dimensional) structuring elements in different (typically four) orientations. Although this approach preserves more details than the simple morphological filters using two-dimensional structuring elements, the limited orientations of one-dimensional elements approximate the fine details of the region boundaries. A more robust filter designed recently overcomes the limitation of the fixed orientations. This filter uses a combination of concave and convex structuring elements. Morphological operators are also useful in extracting features from visible and infrared imagery. A multiresolution image pyramid obtained with successive filtering and a subsampling process aids in the removal of the illumination variations and enhances local contrasts. A morphology-based interpolation scheme was also introduced to reduce intensity discontinuities created in any morphological filtering task. The generality of morphological filtering techniques in extracting information from a wide variety of images obtained with active and passive sensing techniques is discussed. Such techniques are particularly useful in obtaining more information from fusion of complex images by different sensors such as SAR, visible, and infrared.
Multiscale Morphological Filtering for Analysis of Noisy and Complex Images
NASA Technical Reports Server (NTRS)
Kher, A.; Mitra, S.
1993-01-01
Images acquired with passive sensing techniques suffer from illumination variations and poor local contrasts that create major difficulties in interpretation and identification tasks. On the other hand, images acquired with active sensing techniques based on monochromatic illumination are degraded with speckle noise. Mathematical morphology offers elegant techniques to handle a wide range of image degradation problems. Unlike linear filters, morphological filters do not blur the edges and hence maintain higher image resolution. Their rich mathematical framework facilitates the design and analysis of these filters as well as their hardware implementation. Morphological filters are easier to implement and are more cost effective and efficient than several conventional linear filters. Morphological filters to remove speckle noise while maintaining high resolution and preserving thin image regions that are particularly vulnerable to speckle noise were developed and applied to SAR imagery. These filters used combination of linear (one-dimensional) structuring elements in different (typically four) orientations. Although this approach preserves more details than the simple morphological filters using two-dimensional structuring elements, the limited orientations of one-dimensional elements approximate the fine details of the region boundaries. A more robust filter designed recently overcomes the limitation of the fixed orientations. This filter uses a combination of concave and convex structuring elements. Morphological operators are also useful in extracting features from visible and infrared imagery. A multiresolution image pyramid obtained with successive filtering and a subsampling process aids in the removal of the illumination variations and enhances local contrasts. A morphology-based interpolation scheme was also introduced to reduce intensity discontinuities created in any morphological filtering task. The generality of morphological filtering techniques in extracting information from a wide variety of images obtained with active and passive sensing techniques is discussed. Such techniques are particularly useful in obtaining more information from fusion of complex images by different sensors such as SAR, visible, and infrared.
Rabinowitz, Peter M; Slade, Martin D; Galusha, Deron; Dixon-Ernst, Christine; Cullen, Mark R
2006-08-01
Studies have suggested that hearing loss due to recreational noise exposure may be on the rise among adolescents and young adults. This study examines whether the hearing status of young US adults entering an industrial workforce has worsened over the past 20 yr. The baseline audiograms of 2526 individuals ages 17 to 25 beginning employment at a multisite US corporation between 1985 and 2004 were analyzed to determine the yearly prevalence of hearing loss. Approximately 16% of the young adults in the sample had high frequency hearing loss (defined as hearing thresholds greater than 15 dB in either ear at 3,4, or 6 kHz). In a linear regression model, this prevalence decreased over the 20-yr period (odds ratio (OR) = 0.96, 95% confidence interval (CI): 0.94, 0.99). Almost 20% of subjects had audiometric "notches" consistent with noise exposure; this rate remained constant over the 20 yr, as did the prevalence (5%) of low frequency hearing loss. These results indicate that despite concern about widespread recreational noise exposures, the prevalence of hearing loss among a group of young US adults has not significantly increased over the past two decades.
Picosecond Resolution Time-to-Digital Converter Using Gm-C Integrator and SAR-ADC
NASA Astrophysics Data System (ADS)
Xu, Zule; Miyahara, Masaya; Matsuzawa, Akira
2014-04-01
A picosecond resolution time-to-digital converter (TDC) is presented. The resolution of a conventional delay chain TDC is limited by the delay of a logic buffer. Various types of recent TDCs are successful in breaking this limitation, but they require a significant calibration effort to achieve picosecond resolution with a sufficient linear range. To address these issues, we propose a simple method to break the resolution limitation without any calibration: a Gm-C integrator followed by a successive approximation register analog-to-digital converter (SAR-ADC). This translates the time interval into charge, and then the charge is quantized. A prototype chip was fabricated in 90 nm CMOS. The measurement results reveal a 1 ps resolution, a -0.6/0.7 LSB differential nonlinearity (DNL), a -1.1/2.3 LSB integral nonlinearity (INL), and a 9-bit range. The measured 11.74 ps single-shot precision is caused by the noise of the integrator. We analyze the noise of the integrator and propose an improved front-end circuit to reduce this noise. The proposal is verified by simulations showing the maximum single-shot precision is less than 1 ps. The proposed front-end circuit can also diminish the mismatch effects.
Kia, Seyed Mostafa; Vega Pons, Sandro; Weisz, Nathan; Passerini, Andrea
2016-01-01
Brain decoding is a popular multivariate approach for hypothesis testing in neuroimaging. Linear classifiers are widely employed in the brain decoding paradigm to discriminate among experimental conditions. Then, the derived linear weights are visualized in the form of multivariate brain maps to further study spatio-temporal patterns of underlying neural activities. It is well known that the brain maps derived from weights of linear classifiers are hard to interpret because of high correlations between predictors, low signal to noise ratios, and the high dimensionality of neuroimaging data. Therefore, improving the interpretability of brain decoding approaches is of primary interest in many neuroimaging studies. Despite extensive studies of this type, at present, there is no formal definition for interpretability of multivariate brain maps. As a consequence, there is no quantitative measure for evaluating the interpretability of different brain decoding methods. In this paper, first, we present a theoretical definition of interpretability in brain decoding; we show that the interpretability of multivariate brain maps can be decomposed into their reproducibility and representativeness. Second, as an application of the proposed definition, we exemplify a heuristic for approximating the interpretability in multivariate analysis of evoked magnetoencephalography (MEG) responses. Third, we propose to combine the approximated interpretability and the generalization performance of the brain decoding into a new multi-objective criterion for model selection. Our results, for the simulated and real MEG data, show that optimizing the hyper-parameters of the regularized linear classifier based on the proposed criterion results in more informative multivariate brain maps. More importantly, the presented definition provides the theoretical background for quantitative evaluation of interpretability, and hence, facilitates the development of more effective brain decoding algorithms in the future.
Kia, Seyed Mostafa; Vega Pons, Sandro; Weisz, Nathan; Passerini, Andrea
2017-01-01
Brain decoding is a popular multivariate approach for hypothesis testing in neuroimaging. Linear classifiers are widely employed in the brain decoding paradigm to discriminate among experimental conditions. Then, the derived linear weights are visualized in the form of multivariate brain maps to further study spatio-temporal patterns of underlying neural activities. It is well known that the brain maps derived from weights of linear classifiers are hard to interpret because of high correlations between predictors, low signal to noise ratios, and the high dimensionality of neuroimaging data. Therefore, improving the interpretability of brain decoding approaches is of primary interest in many neuroimaging studies. Despite extensive studies of this type, at present, there is no formal definition for interpretability of multivariate brain maps. As a consequence, there is no quantitative measure for evaluating the interpretability of different brain decoding methods. In this paper, first, we present a theoretical definition of interpretability in brain decoding; we show that the interpretability of multivariate brain maps can be decomposed into their reproducibility and representativeness. Second, as an application of the proposed definition, we exemplify a heuristic for approximating the interpretability in multivariate analysis of evoked magnetoencephalography (MEG) responses. Third, we propose to combine the approximated interpretability and the generalization performance of the brain decoding into a new multi-objective criterion for model selection. Our results, for the simulated and real MEG data, show that optimizing the hyper-parameters of the regularized linear classifier based on the proposed criterion results in more informative multivariate brain maps. More importantly, the presented definition provides the theoretical background for quantitative evaluation of interpretability, and hence, facilitates the development of more effective brain decoding algorithms in the future. PMID:28167896
A Theoretical Basis for the Scaling Law of Broadband Shock Noise Intensity in Supersonic Jets
NASA Technical Reports Server (NTRS)
Kandula, Max
2011-01-01
A theoretical basis for the scaling of broadband shock noise intensity In supersonic jets was formulated considering linear shock-shear wave interaction. Modeling of broadband shock noise with the aid of shock-turbulence interaction with special reference to linear theories is briefly reviewed. An hypothesis has been postulated that the peak angle of incidence (closer to the critical angle) for the shear wave primarily governs the generation of sound in the interaction process with the noise generation contribution from off-peak incident angles being relatively unimportant. The proposed hypothesis satisfactorily explains the well-known scaling law for the broadband shock-associated noise in supersonic jets.
Noise temperature and noise figure concepts: DC to light
NASA Technical Reports Server (NTRS)
Stelzried, C. T.
1982-01-01
The Deep Space Network is investigating the use of higher operational frequencies for improved performance. Noise temperature and noise figure concepts are used to describe the noise performance of these receiving systems. It is proposed to modify present noise temperature definitions for linear amplifiers so they will be valid over the range (hf/kT) 1 (hf/kT). This is important for systems operating at high frequencies and low noise temperatures, or systems requiring very accurate calibrations. The suggested definitions are such that for an ideal amplifier, T sub e = (hg/k) = T sub q and F = 1. These definitions revert to the present definition for (hf/kT) 1. Noise temperature calibrations are illustrated with a detailed example. These concepts are applied to system signal-to-noise analysis. The fundamental limit to a receiving system sensitivity is determined by the thermal noise of the source and the quantum noise limit of the receiver. The sensitivity of a receiving system consisting of an ideal linear amplifier with a 2.7 K source, degrades significantly at higher frequencies.
Aerodynamic parameter estimation via Fourier modulating function techniques
NASA Technical Reports Server (NTRS)
Pearson, A. E.
1995-01-01
Parameter estimation algorithms are developed in the frequency domain for systems modeled by input/output ordinary differential equations. The approach is based on Shinbrot's method of moment functionals utilizing Fourier based modulating functions. Assuming white measurement noises for linear multivariable system models, an adaptive weighted least squares algorithm is developed which approximates a maximum likelihood estimate and cannot be biased by unknown initial or boundary conditions in the data owing to a special property attending Shinbrot-type modulating functions. Application is made to perturbation equation modeling of the longitudinal and lateral dynamics of a high performance aircraft using flight-test data. Comparative studies are included which demonstrate potential advantages of the algorithm relative to some well established techniques for parameter identification. Deterministic least squares extensions of the approach are made to the frequency transfer function identification problem for linear systems and to the parameter identification problem for a class of nonlinear-time-varying differential system models.
An investigation of the SNS Josephson junction as a three-terminal device. Ph.D. Thesis
NASA Technical Reports Server (NTRS)
Meissner, H.; Prans, G. P.
1973-01-01
A particular phenomenon of the SNS Josephson junction was investigated; i.e., control by a current entering the normal region and leaving through one of the superconducting regions. The effect of the control current on the junction was found to be dependent upon the ration of the resistances of the two halves of the N layer. A low frequency, lumped, nonlinear model was proposed to describe the electrical characteristics of the device, and a method was developed to plot the dynamic junction resistance as a function of junction current. The effective thermal noise temperature of the sample was determined. Small signal linearized analysis of the device suggests its use as an impedance transformer, although geometric limitations must be overcome. Linear approximation indicates that it is reciprocal and no power gain is possible. It is felt that, with suitable metallurgical and geometrical improvements, the device has promise to become a superconducting transistor.
Determination of sulphite in wines using suppressed ion chromatography.
Yoshikawa, Kenji; Uekusa, Yuki; Sakuragawa, Akio
2015-05-01
Suppressed ion chromatography with the use of a conductivity detector was developed for the determination of sulphite ions in wine samples. When a mixed solution of sodium carbonate, sodium bicarbonate, and acetone was used as the mobile phase, simultaneous determination of eight inorganic anions (i.e., fluoride, chloride, nitrite, nitrate, sulphite, phosphate, sulphate, and thiosulphate) was completed in approximately 25 min. Linearity, reproducibility, and detection limits were determined for the proposed method. In the case of sulphite detection, a linear calibration curve with a good correlation coefficient of 0.9992 was obtained from the peak height of sulphite with a relative standard deviation (n = 6) 1.48%. In addition, the detection limit of sulphite was 0.27 mg/L at a signal-to-noise ratio of 3. Further, the developed method was applied for the determination of sulphite contained in several wine samples. Copyright © 2014 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Wittmann, René; Maggi, C.; Sharma, A.; Scacchi, A.; Brader, J. M.; Marini Bettolo Marconi, U.
2017-11-01
The equations of motion of active systems can be modeled in terms of Ornstein-Uhlenbeck processes (OUPs) with appropriate correlators. For further theoretical studies, these should be approximated to yield a Markovian picture for the dynamics and a simplified steady-state condition. We perform a comparative study of the unified colored noise approximation (UCNA) and the approximation scheme by Fox recently employed within this context. We review the approximations necessary to define effective interaction potentials in the low-density limit and study the conditions for which these represent the behavior observed in two-body simulations for the OUPs model and active Brownian particles. The demonstrated limitations of the theory for potentials with a negative slope or curvature can be qualitatively corrected by a new empirical modification. In general, we find that in the presence of translational white noise the Fox approach is more accurate. Finally, we examine an alternative way to define a force-balance condition in the limit of small activity.
Speech Enhancement, Gain, and Noise Spectrum Adaptation Using Approximate Bayesian Estimation
Hao, Jiucang; Attias, Hagai; Nagarajan, Srikantan; Lee, Te-Won; Sejnowski, Terrence J.
2010-01-01
This paper presents a new approximate Bayesian estimator for enhancing a noisy speech signal. The speech model is assumed to be a Gaussian mixture model (GMM) in the log-spectral domain. This is in contrast to most current models in frequency domain. Exact signal estimation is a computationally intractable problem. We derive three approximations to enhance the efficiency of signal estimation. The Gaussian approximation transforms the log-spectral domain GMM into the frequency domain using minimal Kullback–Leiber (KL)-divergency criterion. The frequency domain Laplace method computes the maximum a posteriori (MAP) estimator for the spectral amplitude. Correspondingly, the log-spectral domain Laplace method computes the MAP estimator for the log-spectral amplitude. Further, the gain and noise spectrum adaptation are implemented using the expectation–maximization (EM) algorithm within the GMM under Gaussian approximation. The proposed algorithms are evaluated by applying them to enhance the speeches corrupted by the speech-shaped noise (SSN). The experimental results demonstrate that the proposed algorithms offer improved signal-to-noise ratio, lower word recognition error rate, and less spectral distortion. PMID:20428253
Four theorems on the psychometric function.
May, Keith A; Solomon, Joshua A
2013-01-01
In a 2-alternative forced-choice (2AFC) discrimination task, observers choose which of two stimuli has the higher value. The psychometric function for this task gives the probability of a correct response for a given stimulus difference, Δx. This paper proves four theorems about the psychometric function. Assuming the observer applies a transducer and adds noise, Theorem 1 derives a convenient general expression for the psychometric function. Discrimination data are often fitted with a Weibull function. Theorem 2 proves that the Weibull "slope" parameter, β, can be approximated by β(Noise) x β(Transducer), where β(Noise) is the β of the Weibull function that fits best to the cumulative noise distribution, and β(Transducer) depends on the transducer. We derive general expressions for β(Noise) and β(Transducer), from which we derive expressions for specific cases. One case that follows naturally from our general analysis is Pelli's finding that, when d' ∝ (Δx)(b), β ≈ β(Noise) x b. We also consider two limiting cases. Theorem 3 proves that, as sensitivity improves, 2AFC performance will usually approach that for a linear transducer, whatever the actual transducer; we show that this does not apply at signal levels where the transducer gradient is zero, which explains why it does not apply to contrast detection. Theorem 4 proves that, when the exponent of a power-function transducer approaches zero, 2AFC performance approaches that of a logarithmic transducer. We show that the power-function exponents of 0.4-0.5 fitted to suprathreshold contrast discrimination data are close enough to zero for the fitted psychometric function to be practically indistinguishable from that of a log transducer. Finally, Weibull β reflects the shape of the noise distribution, and we used our results to assess the recent claim that internal noise has higher kurtosis than a Gaussian. Our analysis of β for contrast discrimination suggests that, if internal noise is stimulus-independent, it has lower kurtosis than a Gaussian.
Thomas, Philipp; Matuschek, Hannes; Grima, Ramon
2012-01-01
The accepted stochastic descriptions of biochemical dynamics under well-mixed conditions are given by the Chemical Master Equation and the Stochastic Simulation Algorithm, which are equivalent. The latter is a Monte-Carlo method, which, despite enjoying broad availability in a large number of existing software packages, is computationally expensive due to the huge amounts of ensemble averaging required for obtaining accurate statistical information. The former is a set of coupled differential-difference equations for the probability of the system being in any one of the possible mesoscopic states; these equations are typically computationally intractable because of the inherently large state space. Here we introduce the software package intrinsic Noise Analyzer (iNA), which allows for systematic analysis of stochastic biochemical kinetics by means of van Kampen's system size expansion of the Chemical Master Equation. iNA is platform independent and supports the popular SBML format natively. The present implementation is the first to adopt a complementary approach that combines state-of-the-art analysis tools using the computer algebra system Ginac with traditional methods of stochastic simulation. iNA integrates two approximation methods based on the system size expansion, the Linear Noise Approximation and effective mesoscopic rate equations, which to-date have not been available to non-expert users, into an easy-to-use graphical user interface. In particular, the present methods allow for quick approximate analysis of time-dependent mean concentrations, variances, covariances and correlations coefficients, which typically outperforms stochastic simulations. These analytical tools are complemented by automated multi-core stochastic simulations with direct statistical evaluation and visualization. We showcase iNA's performance by using it to explore the stochastic properties of cooperative and non-cooperative enzyme kinetics and a gene network associated with circadian rhythms. The software iNA is freely available as executable binaries for Linux, MacOSX and Microsoft Windows, as well as the full source code under an open source license.
Grima, Ramon
2012-01-01
The accepted stochastic descriptions of biochemical dynamics under well-mixed conditions are given by the Chemical Master Equation and the Stochastic Simulation Algorithm, which are equivalent. The latter is a Monte-Carlo method, which, despite enjoying broad availability in a large number of existing software packages, is computationally expensive due to the huge amounts of ensemble averaging required for obtaining accurate statistical information. The former is a set of coupled differential-difference equations for the probability of the system being in any one of the possible mesoscopic states; these equations are typically computationally intractable because of the inherently large state space. Here we introduce the software package intrinsic Noise Analyzer (iNA), which allows for systematic analysis of stochastic biochemical kinetics by means of van Kampen’s system size expansion of the Chemical Master Equation. iNA is platform independent and supports the popular SBML format natively. The present implementation is the first to adopt a complementary approach that combines state-of-the-art analysis tools using the computer algebra system Ginac with traditional methods of stochastic simulation. iNA integrates two approximation methods based on the system size expansion, the Linear Noise Approximation and effective mesoscopic rate equations, which to-date have not been available to non-expert users, into an easy-to-use graphical user interface. In particular, the present methods allow for quick approximate analysis of time-dependent mean concentrations, variances, covariances and correlations coefficients, which typically outperforms stochastic simulations. These analytical tools are complemented by automated multi-core stochastic simulations with direct statistical evaluation and visualization. We showcase iNA’s performance by using it to explore the stochastic properties of cooperative and non-cooperative enzyme kinetics and a gene network associated with circadian rhythms. The software iNA is freely available as executable binaries for Linux, MacOSX and Microsoft Windows, as well as the full source code under an open source license. PMID:22723865
The derivation and approximation of coarse-grained dynamics from Langevin dynamics
NASA Astrophysics Data System (ADS)
Ma, Lina; Li, Xiantao; Liu, Chun
2016-11-01
We present a derivation of a coarse-grained description, in the form of a generalized Langevin equation, from the Langevin dynamics model that describes the dynamics of bio-molecules. The focus is placed on the form of the memory kernel function, the colored noise, and the second fluctuation-dissipation theorem that connects them. Also presented is a hierarchy of approximations for the memory and random noise terms, using rational approximations in the Laplace domain. These approximations offer increasing accuracy. More importantly, they eliminate the need to evaluate the integral associated with the memory term at each time step. Direct sampling of the colored noise can also be avoided within this framework. Therefore, the numerical implementation of the generalized Langevin equation is much more efficient.
Phase reconstruction using compressive two-step parallel phase-shifting digital holography
NASA Astrophysics Data System (ADS)
Ramachandran, Prakash; Alex, Zachariah C.; Nelleri, Anith
2018-04-01
The linear relationship between the sample complex object wave and its approximated complex Fresnel field obtained using single shot parallel phase-shifting digital holograms (PPSDH) is used in compressive sensing framework and an accurate phase reconstruction is demonstrated. It is shown that the accuracy of phase reconstruction of this method is better than that of compressive sensing adapted single exposure inline holography (SEOL) method. It is derived that the measurement model of PPSDH method retains both the real and imaginary parts of the Fresnel field but with an approximation noise and the measurement model of SEOL retains only the real part exactly equal to the real part of the complex Fresnel field and its imaginary part is completely not available. Numerical simulation is performed for CS adapted PPSDH and CS adapted SEOL and it is demonstrated that the phase reconstruction is accurate for CS adapted PPSDH and can be used for single shot digital holographic reconstruction.
Microwave inversion of leaf area and inclination angle distributions from backscattered data
NASA Technical Reports Server (NTRS)
Lang, R. H.; Saleh, H. A.
1985-01-01
The backscattering coefficient from a slab of thin randomly oriented dielectric disks over a flat lossy ground is used to reconstruct the inclination angle and area distributions of the disks. The disks are employed to model a leafy agricultural crop, such as soybeans, in the L-band microwave region of the spectrum. The distorted Born approximation, along with a thin disk approximation, is used to obtain a relationship between the horizontal-like polarized backscattering coefficient and the joint probability density of disk inclination angle and disk radius. Assuming large skin depth reduces the relationship to a linear Fredholm integral equation of the first kind. Due to the ill-posed nature of this equation, a Phillips-Twomey regularization method with a second difference smoothing condition is used to find the inversion. Results are obtained in the presence of 1 and 10 percent noise for both leaf inclination angle and leaf radius densities.
NASA Astrophysics Data System (ADS)
Basin, M.; Maldonado, J. J.; Zendejo, O.
2016-07-01
This paper proposes new mean-square filter and parameter estimator design for linear stochastic systems with unknown parameters over linear observations, where unknown parameters are considered as combinations of Gaussian and Poisson white noises. The problem is treated by reducing the original problem to a filtering problem for an extended state vector that includes parameters as additional states, modelled as combinations of independent Gaussian and Poisson processes. The solution to this filtering problem is based on the mean-square filtering equations for incompletely polynomial states confused with Gaussian and Poisson noises over linear observations. The resulting mean-square filter serves as an identifier for the unknown parameters. Finally, a simulation example shows effectiveness of the proposed mean-square filter and parameter estimator.
Detector noise statistics in the non-linear regime
NASA Technical Reports Server (NTRS)
Shopbell, P. L.; Bland-Hawthorn, J.
1992-01-01
The statistical behavior of an idealized linear detector in the presence of threshold and saturation levels is examined. It is assumed that the noise is governed by the statistical fluctuations in the number of photons emitted by the source during an exposure. Since physical detectors cannot have infinite dynamic range, our model illustrates that all devices have non-linear regimes, particularly at high count rates. The primary effect is a decrease in the statistical variance about the mean signal due to a portion of the expected noise distribution being removed via clipping. Higher order statistical moments are also examined, in particular, skewness and kurtosis. In principle, the expected distortion in the detector noise characteristics can be calibrated using flatfield observations with count rates matched to the observations. For this purpose, some basic statistical methods that utilize Fourier analysis techniques are described.
l/f Noise in the Superconducting Transition of a MgB2 Thin Film
NASA Technical Reports Server (NTRS)
Lakew, B.; Aslam, S.; Jones, H.; Stevenson, T.; Cao, N.
2010-01-01
The noise voltage spectral density in the superconducting transition of a MgB2 thin film on a SiN-coated Si thick substrate was measured over the frequency range 1 Hz-to-1 KHz. Using established bolometer noise theory the theoretical noise components due to Johnson, 1/f(excess) and phonon noise are modeled to the measured data. It is shown that for the case of a MgB2 thin film in the vicinity of the mid-point of transition, coupled to a heat sink via a fairly high thermal conductance (approximately equal to 10(sup -1) W/K)) that the measured noise voltage spectrum is 1/f limited and exhibits lit dependence with a varying between 0.3 and 0.5 in the measured frequency range. At a video frame rate frequency of 30 Hz the measured noise voltage density in the film is approximately equal to 61 nV /the square root of HZ, using this value an upper limit of electrical NEP approximately equal to 0.67pW / the square root of Hz is implied for a practical MgB2 bolometer operating at 36.1 K.
Reduction of Wake-Stator Interaction Noise Using Passive Porosity
NASA Technical Reports Server (NTRS)
Tinetti, Ana F.; Kelly, Jeffrey J.; Thomas, Russell H.; Bauer, Steven X. S.
2002-01-01
The present study was conducted to assess the potential of Passive Porosity Technology as a mechanism to reduce interaction noise in turbomachinery by reducing the fluctuating forces acting on the vane surfaces. To do so, a typical fan stator airfoil was subjected to the effects of a transversely moving wake; time histories of the primitive aerodynamic variables, obtained from Computational Fluid Dynamics (CFD) solutions, were then input into an acoustic prediction code. This procedure was performed on the solid airfoil to obtain a baseline, and on a series of porous configurations in order to isolate those that yield maximum noise reductions without compromising the aerodynamic performance of the stator. It was found that communication between regions of high pressure differential - made possible by the use of passive porosity - is necessary to significantly alter the noise radiation pattern of the stator airfoil. In general, noise reductions were obtained for those configurations incorporating passive porosity in the region between x/c is approximately 0.15 on the suction side of the airfoil and x/c is approximately 0.20 on the pressure side. Reductions in overall radiated noise of approximately 1.0 dB were obtained. The noise benefit increased to about 2.5 dB when the effects of loading noise alone were considered.
NASA Technical Reports Server (NTRS)
Fryer, B. A. (Compiler)
1980-01-01
Reference lists of approximately 900 published Langley Research Center reports in various areas of acoustics and noise control for the period 1940-1979 are presented. Specific topic areas covered include: duct acoustics; propagation and operations; rotating blade noise; jet noise; sonic boom; flow surface interaction noise; structural response/interior noise; human response; and noise prediction.
RADC Multi-Dimensional Signal-Processing Research Program.
1980-09-30
Formulation 7 3.2.2 Methods of Accelerating Convergence 8 3.2.3 Application to Image Deblurring 8 3.2.4 Extensions 11 3.3 Convergence of Iterative Signal... noise -driven linear filters, permit development of the joint probability density function oz " kelihood function for the image. With an expression...spatial linear filter driven by white noise (see Fig. i). If the probability density function for the white noise is known, Fig. t. Model for image
NASA Astrophysics Data System (ADS)
Ganguly, Jayanta; Ghosh, Manas
2015-07-01
We investigate the modulation of diagonal components of static linear (αxx, αyy) and first nonlinear (βxxx, βyyy) polarizabilities of quantum dots by Gaussian white noise. Quantum dot is doped with impurity represented by a Gaussian potential and repulsive in nature. The study reveals the importance of mode of application of noise (additive/multiplicative) on the polarizability components. The doped system is further exposed to a static external electric field of given intensity. As important observation we have found that the strength of additive noise becomes unable to influence the polarizability components. However, the multiplicative noise influences them conspicuously and gives rise to additional interesting features. Multiplicative noise even enhances the magnitude of the polarizability components immensely. The present investigation deems importance in view of the fact that noise seriously affects the optical properties of doped quantum dot devices.
On the Impact of a Quadratic Acceleration Term in the Analysis of Position Time Series
NASA Astrophysics Data System (ADS)
Bogusz, Janusz; Klos, Anna; Bos, Machiel Simon; Hunegnaw, Addisu; Teferle, Felix Norman
2016-04-01
The analysis of Global Navigation Satellite System (GNSS) position time series generally assumes that each of the coordinate component series is described by the sum of a linear rate (velocity) and various periodic terms. The residuals, the deviations between the fitted model and the observations, are then a measure of the epoch-to-epoch scatter and have been used for the analysis of the stochastic character (noise) of the time series. Often the parameters of interest in GNSS position time series are the velocities and their associated uncertainties, which have to be determined with the highest reliability. It is clear that not all GNSS position time series follow this simple linear behaviour. Therefore, we have added an acceleration term in the form of a quadratic polynomial function to the model in order to better describe the non-linear motion in the position time series. This non-linear motion could be a response to purely geophysical processes, for example, elastic rebound of the Earth's crust due to ice mass loss in Greenland, artefacts due to deficiencies in bias mitigation models, for example, of the GNSS satellite and receiver antenna phase centres, or any combination thereof. In this study we have simulated 20 time series with different stochastic characteristics such as white, flicker or random walk noise of length of 23 years. The noise amplitude was assumed at 1 mm/y-/4. Then, we added the deterministic part consisting of a linear trend of 20 mm/y (that represents the averaged horizontal velocity) and accelerations ranging from minus 0.6 to plus 0.6 mm/y2. For all these data we estimated the noise parameters with Maximum Likelihood Estimation (MLE) using the Hector software package without taken into account the non-linear term. In this way we set the benchmark to then investigate how the noise properties and velocity uncertainty may be affected by any un-modelled, non-linear term. The velocities and their uncertainties versus the accelerations for different types of noise are determined. Furthermore, we have selected 40 globally distributed stations that have a clear non-linear behaviour from two different International GNSS Service (IGS) analysis centers: JPL (Jet Propulsion Laboratory) and BLT (British Isles continuous GNSS Facility and University of Luxembourg Tide Gauge Benchmark Monitoring (TIGA) Analysis Center). We obtained maximum accelerations of -1.8±1.2 mm2/y and -4.5±3.3 mm2/y for the horizontal and vertical components, respectively. The noise analysis tests have shown that the addition of the non-linear term has significantly whitened the power spectra of the position time series, i.e. shifted the spectral index from flicker towards white noise.
NASA Astrophysics Data System (ADS)
Franović, Igor; Todorović, Kristina; Vasović, Nebojša; Burić, Nikola
2014-02-01
We consider the approximations behind the typical mean-field model derived for a class of systems made up of type II excitable units influenced by noise and coupling delays. The formulation of the two approximations, referred to as the Gaussian and the quasi-independence approximation, as well as the fashion in which their validity is verified, are adapted to reflect the essential properties of the underlying system. It is demonstrated that the failure of the mean-field model associated with the breakdown of the quasi-independence approximation can be predicted by the noise-induced bistability in the dynamics of the mean-field system. As for the Gaussian approximation, its violation is related to the increase of noise intensity, but the actual condition for failure can be cast in qualitative, rather than quantitative terms. We also discuss how the fulfillment of the mean-field approximations affects the statistics of the first return times for the local and global variables, further exploring the link between the fulfillment of the quasi-independence approximation and certain forms of synchronization between the individual units.
Aging of imaging properties of a CMOS flat-panel detector for dental cone-beam computed tomography
NASA Astrophysics Data System (ADS)
Kim, D. W.; Han, J. C.; Yun, S.; Kim, H. K.
2017-01-01
We have experimentally investigated the long-term stability of imaging properties of a flat-panel detector in conditions used for dental x-ray imaging. The detector consists of a CsI:Tl layer and CMOS photodiode pixel arrays. Aging simulations were carried out using an 80-kVp x-ray beam at an air-kerma rate of approximately 5 mGy s-1 at the entrance surface of the detector with a total air kerma of up to 0.6 kGy. Dark and flood-field images were periodically obtained during irradiation, and the mean signal and noise levels were evaluated for each image. We also evaluated the modulation-transfer function (MTF), noise-power spectrum (NPS), and detective quantum efficiency (DQE). The aging simulation showed a decrease in both the signal and noise of the gain-offset-corrected images, but there was negligible change in the signal-to-noise performance as a function of the accumulated dose. The gain-offset correction for analyzing images resulted in negligible changes in MTF, NPS, and DQE results over the total dose. Continuous x-ray exposure to a detector can cause degradation in the physical performance factors such the detector sensitivity, but linear analysis of the gain-offset-corrected images can assure integrity of the imaging properties of a detector during its lifetime.
Effect of Coannular Flow on Linearized Euler Equation Predictions of Jet Noise
NASA Technical Reports Server (NTRS)
Hixon, R.; Shih, S.-H.; Mankbadi, Reda R.
1997-01-01
An improved version of a previously validated linearized Euler equation solver is used to compute the noise generated by coannular supersonic jets. Results for a single supersonic jet are compared to the results from both a normal velocity profile and an inverted velocity profile supersonic jet.
Mean, covariance, and effective dimension of stochastic distributed delay dynamics
NASA Astrophysics Data System (ADS)
René, Alexandre; Longtin, André
2017-11-01
Dynamical models are often required to incorporate both delays and noise. However, the inherently infinite-dimensional nature of delay equations makes formal solutions to stochastic delay differential equations (SDDEs) challenging. Here, we present an approach, similar in spirit to the analysis of functional differential equations, but based on finite-dimensional matrix operators. This results in a method for obtaining both transient and stationary solutions that is directly amenable to computation, and applicable to first order differential systems with either discrete or distributed delays. With fewer assumptions on the system's parameters than other current solution methods and no need to be near a bifurcation, we decompose the solution to a linear SDDE with arbitrary distributed delays into natural modes, in effect the eigenfunctions of the differential operator, and show that relatively few modes can suffice to approximate the probability density of solutions. Thus, we are led to conclude that noise makes these SDDEs effectively low dimensional, which opens the possibility of practical definitions of probability densities over their solution space.
NASA Astrophysics Data System (ADS)
Walker, Ernest L.
1994-05-01
This paper presents results of a theoretical investigation to evaluate the performance of code division multiple access communications over multimode optical fiber channels in an asynchronous, multiuser communication network environment. The system is evaluated using Gold sequences for spectral spreading of the baseband signal from each user employing direct-sequence biphase shift keying and intensity modulation techniques. The transmission channel model employed is a lossless linear system approximation of the field transfer function for the alpha -profile multimode optical fiber. Due to channel model complexity, a correlation receiver model employing a suboptimal receive filter was used in calculating the peak output signal at the ith receiver. In Part 1, the performance measures for the system, i.e., signal-to-noise ratio and bit error probability for the ith receiver, are derived as functions of channel characteristics, spectral spreading, number of active users, and the bit energy to noise (white) spectral density ratio. In Part 2, the overall system performance is evaluated.
On effective temperature in network models of collective behavior
DOE Office of Scientific and Technical Information (OSTI.GOV)
Porfiri, Maurizio, E-mail: mporfiri@nyu.edu; Ariel, Gil, E-mail: arielg@math.biu.ac.il
Collective behavior of self-propelled units is studied analytically within the Vectorial Network Model (VNM), a mean-field approximation of the well-known Vicsek model. We propose a dynamical systems framework to study the stochastic dynamics of the VNM in the presence of general additive noise. We establish that a single parameter, which is a linear function of the circular mean of the noise, controls the macroscopic phase of the system—ordered or disordered. By establishing a fluctuation–dissipation relation, we posit that this parameter can be regarded as an effective temperature of collective behavior. The exact critical temperature is obtained analytically for systems withmore » small connectivity, equivalent to low-density ensembles of self-propelled units. Numerical simulations are conducted to demonstrate the applicability of this new notion of effective temperature to the Vicsek model. The identification of an effective temperature of collective behavior is an important step toward understanding order–disorder phase transitions, informing consistent coarse-graining techniques and explaining the physics underlying the emergence of collective phenomena.« less
Real-Time PCR Quantification Using A Variable Reaction Efficiency Model
Platts, Adrian E.; Johnson, Graham D.; Linnemann, Amelia K.; Krawetz, Stephen A.
2008-01-01
Quantitative real-time PCR remains a cornerstone technique in gene expression analysis and sequence characterization. Despite the importance of the approach to experimental biology the confident assignment of reaction efficiency to the early cycles of real-time PCR reactions remains problematic. Considerable noise may be generated where few cycles in the amplification are available to estimate peak efficiency. An alternate approach that uses data from beyond the log-linear amplification phase is explored with the aim of reducing noise and adding confidence to efficiency estimates. PCR reaction efficiency is regressed to estimate the per-cycle profile of an asymptotically departed peak efficiency, even when this is not closely approximated in the measurable cycles. The process can be repeated over replicates to develop a robust estimate of peak reaction efficiency. This leads to an estimate of the maximum reaction efficiency that may be considered primer-design specific. Using a series of biological scenarios we demonstrate that this approach can provide an accurate estimate of initial template concentration. PMID:18570886
Lensing bias to CMB measurements of compensated isocurvature perturbations
NASA Astrophysics Data System (ADS)
Heinrich, Chen He; Grin, Daniel; Hu, Wayne
2016-08-01
Compensated isocurvature perturbations (CIPs) are modes in which the baryon and dark matter density fluctuations cancel. They arise in the curvaton scenario as well as some models of baryogenesis. While they leave no observable effects on the cosmic microwave background (CMB) at linear order, they do spatially modulate two-point CMB statistics and can be reconstructed in a manner similar to gravitational lensing. Due to the similarity between the effects of CMB lensing and CIPs, lensing contributes nearly Gaussian random noise to the CIP estimator that approximately doubles the reconstruction noise power. Additionally, the cross correlation between lensing and the integrated Sachs-Wolfe effect generates a correlation between the CIP estimator and the temperature field even in the absence of a correlated CIP signal. For cosmic-variance limited temperature measurements out to multipoles l ≤2500 , subtracting a fixed lensing bias degrades the detection threshold for CIPs by a factor of 1.3, whether or not they are correlated with the adiabatic mode.
NASA Astrophysics Data System (ADS)
Sapia, Mark Angelo
2000-11-01
Three-dimensional microscope images typically suffer from reduced resolution due to the effects of convolution, optical aberrations and out-of-focus blurring. Two- dimensional ultrasound images are also degraded by convolutional bluffing and various sources of noise. Speckle noise is a major problem in ultrasound images. In microscopy and ultrasound, various methods of digital filtering have been used to improve image quality. Several methods of deconvolution filtering have been used to improve resolution by reversing the convolutional effects, many of which are based on regularization techniques and non-linear constraints. The technique discussed here is a unique linear filter for deconvolving 3D fluorescence microscopy or 2D ultrasound images. The process is to solve for the filter completely in the spatial-domain using an adaptive algorithm to converge to an optimum solution for de-blurring and resolution improvement. There are two key advantages of using an adaptive solution: (1)it efficiently solves for the filter coefficients by taking into account all sources of noise and degraded resolution at the same time, and (2)achieves near-perfect convergence to the ideal linear deconvolution filter. This linear adaptive technique has other advantages such as avoiding artifacts of frequency-domain transformations and concurrent adaptation to suppress noise. Ultimately, this approach results in better signal-to-noise characteristics with virtually no edge-ringing. Many researchers have not adopted linear techniques because of poor convergence, noise instability and negative valued data in the results. The methods presented here overcome many of these well-documented disadvantages and provide results that clearly out-perform other linear methods and may also out-perform regularization and constrained algorithms. In particular, the adaptive solution is most responsible for overcoming the poor performance associated with linear techniques. This linear adaptive approach to deconvolution is demonstrated with results of restoring blurred phantoms for both microscopy and ultrasound and restoring 3D microscope images of biological cells and 2D ultrasound images of human subjects (courtesy of General Electric and Diasonics, Inc.).
Christensen, Jeppe Schultz; Raaschou-Nielsen, Ole; Tjønneland, Anne; Overvad, Kim; Nordsborg, Rikke B; Ketzel, Matthias; Sørensen, Thorkild Ia; Sørensen, Mette
2016-03-01
Traffic noise has been associated with cardiovascular and metabolic disorders. Potential modes of action are through stress and sleep disturbance, which may lead to endocrine dysregulation and overweight. We aimed to investigate the relationship between residential traffic and railway noise and adiposity. In this cross-sectional study of 57,053 middle-aged people, height, weight, waist circumference, and bioelectrical impedance were measured at enrollment (1993-1997). Body mass index (BMI), body fat mass index (BFMI), and lean body mass index (LBMI) were calculated. Residential exposure to road and railway traffic noise exposure was calculated using the Nordic prediction method. Associations between traffic noise and anthropometric measures at enrollment were analyzed using general linear models and logistic regression adjusted for demographic and lifestyle factors. Linear regression models adjusted for age, sex, and socioeconomic factors showed that 5-year mean road traffic noise exposure preceding enrollment was associated with a 0.35-cm wider waist circumference (95% CI: 0.21, 0.50) and a 0.18-point higher BMI (95% CI: 0.12, 0.23) per 10 dB. Small, significant increases were also found for BFMI and LBMI. All associations followed linear exposure-response relationships. Exposure to railway noise was not linearly associated with adiposity measures. However, exposure > 60 dB was associated with a 0.71-cm wider waist circumference (95% CI: 0.23, 1.19) and a 0.19-point higher BMI (95% CI: 0.0072, 0.37) compared with unexposed participants (0-20 dB). The present study finds positive associations between residential exposure to road traffic and railway noise and adiposity.
Poznanski, Roman R
2010-02-01
An assumption commonly used in cable theory is revised by taking into account electrical amplification due to intracellular capacitive effects in passive dendritic cables. A generalized cable equation for a cylindrical volume representation of a dendritic segment is derived from Maxwell's equations under assumptions: (i) the electric-field polarization is restricted longitudinally along the cable length; (ii) extracellular isopotentiality; (iii) quasielectrostatic conditions; and (iv) homogeneous medium with constant conductivity and permittivity. The generalized cable equation is identical to Barenblatt's equation arising in the theory of infiltration in fissured strata with a known analytical solution expressed in terms of a definite integral involving a modified Bessel function and the solution to a linear one-dimensional classical cable equation. Its solution is used to determine the impact of thermal noise on voltage attenuation with distance at any particular time. A regular perturbation expansion for the membrane potential about the linear one-dimensional classical cable equation solution is derived in terms of a Green's function in order to describe the dynamics of free charge within the Debye layer of endogenous structures in passive dendritic cables. The asymptotic value of the first perturbative term is explicitly evaluated for small values of time to predict how the slowly fluctuating (in submillisecond range) electric field attributed to intracellular capacitive effects alters the amplitude of the membrane potential. It was found that capacitive effects are almost negligible for cables with electrotonic lengths L>0.5 , contributes up to 10% of the signal for cables with electrotonic lengths in the range between 0.25
NASA Astrophysics Data System (ADS)
Wang, Y.; Lin, F. C.; Allam, A. A.; Ben-Zion, Y.
2017-12-01
The San Jacinto fault is presently the most seismically active component of the San Andreas Transform system in Southern California. To study the damage zone structure, two dense linear geophone arrays (BS and RR) were deployed across the Clark segment of the San Jacinto Fault between Anza and Hemet during winter 2015 and Fall 2016, respectively. Both arrays were 2 km long with 20 m station spacing. Month-long three-component ambient seismic noise data were recorded and used to calculate multi-channel cross-correlation functions. All three-component noise records of each array were normalized simultaneously to retain relative amplitude information between different stations and different components. We observed clear Rayleigh waves and Love waves on the cross-correlations of both arrays at 0.3 - 1 s period. The phase travel times of the Rayleigh waves on both arrays were measured by frequency-time analysis (FTAN), and inverted for Rayleigh wave phase velocity profiles of the upper 500 m depth. For both arrays, we observe prominent asymmetric low velocity zones which narrow with depth. At the BS array near the Hemet Stepover, an approximately 250m wide slow zone is observed to be offset by 75m to the northeast of the surface fault trace. At the RR array near the Anza segment of the fault, a similar low velocity zone width and offset are observed, along with a 10% across-fault velocity contrast. Analyses of Rayleigh wave ellipticity (H/V ratio), Love wave phase travel times, and site amplification are in progress. By using multiple measurements from ambient noise cross-correlations, we can obtain strong constraints on the local damage zone structure of the San Jacinto Fault. The results contribute to improved understanding of rupture directivity, maximum earthquake magnitude and more generally seismic hazard associated with the San Jacinto fault zone.
Low Noise in a Diffusion-Cooled Hot-Electron Mixer at 2.5 THz
NASA Technical Reports Server (NTRS)
Karasik, B. S.; Gaidis, M. C.; McGrath, W. R.; Bumble, B.; LeDuc, H. G.
1997-01-01
The noise performance of a Nb hot-electron bolometer mixer at 2.5 THz has been investigated. The devices are fabricated from a 12-nm-thick Nb film, and have a 0.30 micrometer x 0.15 micrometer in-plane size, thus exploiting diffusion as the electron cooling mechanism. The rf coupling was provided by a twin-slot planar antenna on an elliptical Si lens. The experimentally measured double sideband noise temperature of the receiver was as low as 2750 +/- 250 K with an estimated mixer noise temperature of approximately equal 900 K. The mixer bandwidth derived from both noise bandwidth and IF impedance measurements was approximately equal 1.4 GHz. These results demonstrate the low-noise operation of the diffusion-cooled bolometer mixer above 2 THz.
NASA Astrophysics Data System (ADS)
Hao, Zhenhua; Cui, Ziqiang; Yue, Shihong; Wang, Huaxiang
2018-06-01
As an important means in electrical impedance tomography (EIT), multi-frequency phase-sensitive demodulation (PSD) can be viewed as a matched filter for measurement signals and as an optimal linear filter in the case of Gaussian-type noise. However, the additive noise usually possesses impulsive noise characteristics, so it is a challenging task to reduce the impulsive noise in multi-frequency PSD effectively. In this paper, an approach for impulsive noise reduction in multi-frequency PSD of EIT is presented. Instead of linear filters, a singular value decomposition filter is employed as the pre-stage filtering module prior to PSD, which has advantages of zero phase shift, little distortion, and a high signal-to-noise ratio (SNR) in digital signal processing. Simulation and experimental results demonstrated that the proposed method can effectively eliminate the influence of impulsive noise in multi-frequency PSD, and it was capable of achieving a higher SNR and smaller demodulation error.
1983-08-31
Noise using Linear Programming, Jaroslavcompositic- , theorem. (invited Paper) Keybl and George Eichmann, The City University of New York. Linear...programming is used to estimate two closely spaced frequencies of sinusoidal signals buried 2:30 PM WA13 in deep white Gaussian noise . Reconstruction of...S. Olson, and J. A. Weinman, University of coarsely sampled images degraded by diffraction and Wisconsin-Madison. Eight synthetic multichannel noise
Mixed, charge and heat noises in thermoelectric nanosystems
NASA Astrophysics Data System (ADS)
Crépieux, Adeline; Michelini, Fabienne
2015-01-01
Mixed, charge and heat current fluctuations as well as thermoelectric differential conductances are considered for non-interacting nanosystems connected to reservoirs. Using the Landauer-Büttiker formalism, we derive general expressions for these quantities and consider their possible relationships in the entire ranges of temperature, voltage and coupling to the environment or reservoirs. We introduce a dimensionless quantity given by the ratio between the product of mixed noises and the product of charge and heat noises, distinguishing between the auto-ratio defined in the same reservoir and the cross-ratio between distinct reservoirs. From the linear response regime to the high-voltage regime, we further specify the analytical expressions of differential conductances, noises and ratios of noises, and examine their behavior in two concrete nanosystems: a quantum point contact in an ohmic environment and a single energy level quantum dot connected to reservoirs. In the linear response regime, we find that these ratios are equal to each other and are simply related to the figure of merit. They can be expressed in terms of differential conductances with the help of the fluctuation-dissipation theorem. In the non-linear regime, these ratios radically distinguish between themselves as the auto-ratio remains bounded by one, while the cross-ratio exhibits rich and complex behaviors. In the quantum dot nanosystem, we moreover demonstrate that the thermoelectric efficiency can be expressed as a ratio of noises in the non-linear Schottky regime. In the intermediate voltage regime, the cross-ratio changes sign and diverges, which evidences a change of sign in the heat cross-noise.
Mixed, charge and heat noises in thermoelectric nanosystems.
Crépieux, Adeline; Michelini, Fabienne
2015-01-14
Mixed, charge and heat current fluctuations as well as thermoelectric differential conductances are considered for non-interacting nanosystems connected to reservoirs. Using the Landauer-Büttiker formalism, we derive general expressions for these quantities and consider their possible relationships in the entire ranges of temperature, voltage and coupling to the environment or reservoirs. We introduce a dimensionless quantity given by the ratio between the product of mixed noises and the product of charge and heat noises, distinguishing between the auto-ratio defined in the same reservoir and the cross-ratio between distinct reservoirs. From the linear response regime to the high-voltage regime, we further specify the analytical expressions of differential conductances, noises and ratios of noises, and examine their behavior in two concrete nanosystems: a quantum point contact in an ohmic environment and a single energy level quantum dot connected to reservoirs. In the linear response regime, we find that these ratios are equal to each other and are simply related to the figure of merit. They can be expressed in terms of differential conductances with the help of the fluctuation-dissipation theorem. In the non-linear regime, these ratios radically distinguish between themselves as the auto-ratio remains bounded by one, while the cross-ratio exhibits rich and complex behaviors. In the quantum dot nanosystem, we moreover demonstrate that the thermoelectric efficiency can be expressed as a ratio of noises in the non-linear Schottky regime. In the intermediate voltage regime, the cross-ratio changes sign and diverges, which evidences a change of sign in the heat cross-noise.
Stochastic Multiresonance for a Fractional Linear Oscillator with Quadratic Trichotomous Noise
NASA Astrophysics Data System (ADS)
Zhu, Jian-Qu; Jin, Wei-Dong; Zheng, Gao; Guo, Feng
2017-11-01
The stochastic multiresonance behavior for a fractional linear oscillator with random system frequency is investigated. The fluctuation of the system frequency is a quadratic trichotomous noise, the memory kernel of the fractional oscillator is modeled as a Mittag-Leffler function. Based on linear system theory, applying Laplace transform and the definition of fractional derivative, the expression of the system output amplitude (SPA) is obtained. Stochastic multiresonance phenomenon is found on the curves of SPA versus the memory time and the memory exponent of the fractional oscillator, as well as versus the trichotomous noise amplitude. The SPA depends non-monotonically on the stationary probability of the trichotomous noise, on the viscous damping coefficient and system characteristic frequency of the oscillator, as well as on the driving frequency of external force. Supported by National Natural Science Foundation of China under Grant No. 61134002
Jastreboff, P W
1979-06-01
Time histograms of neural responses evoked by sinuosidal stimulation often contain a slow drifting and an irregular noise which disturb Fourier analysis of these responses. Section 2 of this paper evaluates the extent to which a linear drift influences the Fourier analysis, and develops a combined Fourier and linear regression analysis for detecting and correcting for such a linear drift. Usefulness of this correcting method is demonstrated for the time histograms of actual eye movements and Purkinje cell discharges evoked by sinusoidal rotation of rabbits in the horizontal plane. In Sect. 3, the analysis of variance is adopted for estimating the probability of the random occurrence of the response curve extracted by Fourier analysis from noise. This method proved to be useful for avoiding false judgements as to whether the response curve was meaningful, particularly when the response was small relative to the contaminating noise.
Linear and nonlinear trending and prediction for AVHRR time series data
NASA Technical Reports Server (NTRS)
Smid, J.; Volf, P.; Slama, M.; Palus, M.
1995-01-01
The variability of AVHRR calibration coefficient in time was analyzed using algorithms of linear and non-linear time series analysis. Specifically we have used the spline trend modeling, autoregressive process analysis, incremental neural network learning algorithm and redundancy functional testing. The analysis performed on available AVHRR data sets revealed that (1) the calibration data have nonlinear dependencies, (2) the calibration data depend strongly on the target temperature, (3) both calibration coefficients and the temperature time series can be modeled, in the first approximation, as autonomous dynamical systems, (4) the high frequency residuals of the analyzed data sets can be best modeled as an autoregressive process of the 10th degree. We have dealt with a nonlinear identification problem and the problem of noise filtering (data smoothing). The system identification and filtering are significant problems for AVHRR data sets. The algorithms outlined in this study can be used for the future EOS missions. Prediction and smoothing algorithms for time series of calibration data provide a functional characterization of the data. Those algorithms can be particularly useful when calibration data are incomplete or sparse.
Bayesian linearized amplitude-versus-frequency inversion for quality factor and its application
NASA Astrophysics Data System (ADS)
Yang, Xinchao; Teng, Long; Li, Jingnan; Cheng, Jiubing
2018-06-01
We propose a straightforward attenuation inversion method by utilizing the amplitude-versus-frequency (AVF) characteristics of seismic data. A new linearized approximation equation of the angle and frequency dependent reflectivity in viscoelastic media is derived. We then use the presented equation to implement the Bayesian linear AVF inversion. The inversion result includes not only P-wave and S-wave velocities, and densities, but also P-wave and S-wave quality factors. Synthetic tests show that the AVF inversion surpasses the AVA inversion for quality factor estimation. However, a higher signal noise ratio (SNR) of data is necessary for the AVF inversion. To show its feasibility, we apply both the new Bayesian AVF inversion and conventional AVA inversion to a tight gas reservoir data in Sichuan Basin in China. Considering the SNR of the field data, a combination of AVF inversion for attenuation parameters and AVA inversion for elastic parameters is recommended. The result reveals that attenuation estimations could serve as a useful complement in combination with the AVA inversion results for the detection of tight gas reservoirs.
Internal noise sources limiting contrast sensitivity.
Silvestre, Daphné; Arleo, Angelo; Allard, Rémy
2018-02-07
Contrast sensitivity varies substantially as a function of spatial frequency and luminance intensity. The variation as a function of luminance intensity is well known and characterized by three laws that can be attributed to the impact of three internal noise sources: early spontaneous neural activity limiting contrast sensitivity at low luminance intensities (i.e. early noise responsible for the linear law), probabilistic photon absorption at intermediate luminance intensities (i.e. photon noise responsible for de Vries-Rose law) and late spontaneous neural activity at high luminance intensities (i.e. late noise responsible for Weber's law). The aim of this study was to characterize how the impact of these three internal noise sources vary with spatial frequency and determine which one is limiting contrast sensitivity as a function of luminance intensity and spatial frequency. To estimate the impact of the different internal noise sources, the current study used an external noise paradigm to factorize contrast sensitivity into equivalent input noise and calculation efficiency over a wide range of luminance intensities and spatial frequencies. The impact of early and late noise was found to drop linearly with spatial frequency, whereas the impact of photon noise rose with spatial frequency due to ocular factors.
Why noise is useful in functional and neural mechanisms of interval timing?
2013-01-01
Background The ability to estimate durations in the seconds-to-minutes range - interval timing - is essential for survival, adaptation and its impairment leads to severe cognitive and/or motor dysfunctions. The response rate near a memorized duration has a Gaussian shape centered on the to-be-timed interval (criterion time). The width of the Gaussian-like distribution of responses increases linearly with the criterion time, i.e., interval timing obeys the scalar property. Results We presented analytical and numerical results based on the striatal beat frequency (SBF) model showing that parameter variability (noise) mimics behavioral data. A key functional block of the SBF model is the set of oscillators that provide the time base for the entire timing network. The implementation of the oscillators block as simplified phase (cosine) oscillators has the additional advantage that is analytically tractable. We also checked numerically that the scalar property emerges in the presence of memory variability by using biophysically realistic Morris-Lecar oscillators. First, we predicted analytically and tested numerically that in a noise-free SBF model the output function could be approximated by a Gaussian. However, in a noise-free SBF model the width of the Gaussian envelope is independent of the criterion time, which violates the scalar property. We showed analytically and verified numerically that small fluctuations of the memorized criterion time leads to scalar property of interval timing. Conclusions Noise is ubiquitous in the form of small fluctuations of intrinsic frequencies of the neural oscillators, the errors in recording/retrieving stored information related to criterion time, fluctuation in neurotransmitters’ concentration, etc. Our model suggests that the biological noise plays an essential functional role in the SBF interval timing. PMID:23924391
Quantum error correction of continuous-variable states against Gaussian noise
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ralph, T. C.
2011-08-15
We describe a continuous-variable error correction protocol that can correct the Gaussian noise induced by linear loss on Gaussian states. The protocol can be implemented using linear optics and photon counting. We explore the theoretical bounds of the protocol as well as the expected performance given current knowledge and technology.
NASA Astrophysics Data System (ADS)
Proskurov, S.; Darbyshire, O. R.; Karabasov, S. A.
2017-12-01
The present work discusses modifications to the stochastic Fast Random Particle Mesh (FRPM) method featuring both tonal and broadband noise sources. The technique relies on the combination of incorporated vortex-shedding resolved flow available from Unsteady Reynolds-Averaged Navier-Stokes (URANS) simulation with the fine-scale turbulence FRPM solution generated via the stochastic velocity fluctuations in the context of vortex sound theory. In contrast to the existing literature, our method encompasses a unified treatment for broadband and tonal acoustic noise sources at the source level, thus, accounting for linear source interference as well as possible non-linear source interaction effects. When sound sources are determined, for the sound propagation, Acoustic Perturbation Equations (APE-4) are solved in the time-domain. Results of the method's application for two aerofoil benchmark cases, with both sharp and blunt trailing edges are presented. In each case, the importance of individual linear and non-linear noise sources was investigated. Several new key features related to the unsteady implementation of the method were tested and brought into the equation. Encouraging results have been obtained for benchmark test cases using the new technique which is believed to be potentially applicable to other airframe noise problems where both tonal and broadband parts are important.
Reduced-order modeling of fluids systems, with applications in unsteady aerodynamics
NASA Astrophysics Data System (ADS)
Dawson, Scott T. M.
This thesis focuses on two major themes: modeling and understanding the dynamics of rapidly pitching airfoils, and developing methods that can be used to extract models and pertinent features from datasets obtained in the study of these and other systems in fluid mechanics and aerodynamics. Much of the work utilizes in some capacity dynamic mode decomposition (DMD), a recently developed method to extract dynamical features and models from data. The investigation of pitching airfoils includes both wind tunnel experiments and direct numerical simulations. Experiments are performed on a NACA 0012 airfoil undergoing rapid pitching motion, with the focus on developing a switched linear modeling framework that can accurately predict unsteady aerodynamic forces and pressure distributions throughout arbitrary pitching motions. Numerical simulations are used to study the behavior of sinusoidally pitching airfoils. By systematically varying the amplitude, frequency, mean angle and axis of pitching, a comprehensive database of results is acquired, from which interesting regions in parameter space are identified and studied. Attention is given to pitching at "preferred" frequencies, where vortex shedding in the wake is excited or amplified, leading to larger lift forces. More generally, the ability to extract nonlinear models that describe the behavior of complex fluids systems can assist in not only understanding the dominant features of such systems, but also to achieve accurate prediction and control. One potential avenue to achieve this objective is through numerical approximation of the Koopman operator, an infinite-dimensional linear operator capable of describing finite-dimensional nonlinear systems, such as those that might describe the dominant dynamics of fluids systems. This idea is explored by showing that algorithms designed to approximate the Koopman operator can indeed be utilized to accurately model nonlinear fluids systems, even when the data available is limited or noisy. Data-driven algorithms can be adversely affected by noisy data. Focusing on DMD, it is shown analytically that the algorithm is biased to sensor noise, which explains a previously observed sensitivity to noisy data. Using this finding, a number of modifications to DMD are proposed, which all give better approximations of the true dynamics using noise-corrupted data.
Pre-Launch Noise Characterization of the Landsat-7 Enhanced Thematic Mapper Plus (ETM Plus)
NASA Technical Reports Server (NTRS)
Pedelty, J. A.; Markham, B. L.; Barker, J. L.; Seiferth, J. C.
1999-01-01
A noise characterization of the Landsat-7 Enhanced Thematic Mapper Plus (ETM+) instrument was performed as part of a near-real time performance assessment and health monitoring program. Perl'ormance data for the integrated Landsat-7 spacecraft and ETM+ were collected before, during, and after the spacecraft thermal vacuum testing program at the Lockheed Martin Missiles and Space (LMMS) facilities in Valley Forge, PA. The Landsat-7 spacecraft and ETM+ instrument were successfully launched on April 15, 1999. The spacecraft and ETM+ are now nearing the end of the on orbit engineering checkout phase, and Landsat-7 is expected to be declared operational on or about July 15, 1999. A preliminary post-launch noise characterization was performed and compared with the pre-launch characterization. In general the overall noise levels in the ETM+ are at or below the specification levels. Coherent noise is seen in most bands, but is only operationally significant when imaging in (he panchromatic band (band 8). This coherent noise has an amplitude as high as approximately 3 DN (peak-to-peak, high gain) at the Nyquist rate of 104 kHz, and causes the noise levels in panchromatic band images at times to exceed the total noise specification by up to approximately 10%. However, this 104 kHz noise is now much weaker than it was prior to the successful repair of the ETM+ power supplies that was completed in May 1998. Weak and stable coherent noise at approximately 5 kHz is seen in all bands in the prime focal plane (bands 1-4 and 8) with the prime (side A) electronics. Very strong coherent noise at approximately 20 kHz is seen in a few detectors of bands 1 and 8, but this noise is almost entirely in the turn-around region between scans when the ETM+ is not imaging the Earth. Strong coherent noise was seen in 2 detectors of band 5 during some of the pre-launch testing; however, this noise seems to be temperature dependent, and has not been seen in the current on orbit environment. Strong 91 kHz coherent noise was observed in the redundant (side B) panchromatic band data after the completion of spacecraft thermal vacuum testing. The cause of this coherent noise was identified as a failed capacitor that was replaced prior to launch, and this noise has not been seen on orbit.
NASA Astrophysics Data System (ADS)
Farahani, Hassan H.; Ditmar, Pavel; Inácio, Pedro; Didova, Olga; Gunter, Brian; Klees, Roland; Guo, Xiang; Guo, Jing; Sun, Yu; Liu, Xianglin; Zhao, Qile; Riva, Riccardo
2017-01-01
We present a high resolution model of the linear trend in the Earth's mass variations based on DMT-2 (Delft Mass Transport model, release 2). DMT-2 was produced primarily from K-Band Ranging (KBR) data of the Gravity Recovery And Climate Experiment (GRACE). It comprises a time series of monthly solutions complete to spherical harmonic degree 120. A novel feature in its production was the accurate computation and incorporation of stochastic properties of coloured noise when processing KBR data. The unconstrained DMT-2 monthly solutions are used to estimate the linear trend together with a bias, as well as annual and semi-annual sinusoidal terms. The linear term is further processed with an anisotropic Wiener filter, which uses full noise and signal covariance matrices. Given the fact that noise in an unconstrained model of the trend is reduced substantially as compared to monthly solutions, the Wiener filter associated with the trend is much less aggressive compared to a Wiener filter applied to monthly solutions. Consequently, the trend estimate shows an enhanced spatial resolution. It allows signals in relatively small water bodies, such as Aral sea and Ladoga lake, to be detected. Over the ice sheets, it allows for a clear identification of signals associated with some outlet glaciers or their groups. We compare the obtained trend estimate with the ones from the CSR-RL05 model using (i) the same approach based on monthly noise covariance matrices and (ii) a commonly-used approach based on the DDK-filtered monthly solutions. We use satellite altimetry data as independent control data. The comparison demonstrates a high spatial resolution of the DMT-2 linear trend. We link this to the usage of high-accuracy monthly noise covariance matrices, which is due to an accurate computation and incorporation of coloured noise when processing KBR data. A preliminary comparison of the linear trend based on DMT-2 with that computed from GSFC_global_mascons_v01 reveals, among other, a high concentration of the signal along the coast for both models in areas like the ice sheets, Gulf of Alaska, and Iceland.
Linear Models for Systematics and Nuisances
NASA Astrophysics Data System (ADS)
Luger, Rodrigo; Foreman-Mackey, Daniel; Hogg, David W.
2017-12-01
The target of many astronomical studies is the recovery of tiny astrophysical signals living in a sea of uninteresting (but usually dominant) noise. In many contexts (i.e., stellar time-series, or high-contrast imaging, or stellar spectroscopy), there are structured components in this noise caused by systematic effects in the astronomical source, the atmosphere, the telescope, or the detector. More often than not, evaluation of the true physical model for these nuisances is computationally intractable and dependent on too many (unknown) parameters to allow rigorous probabilistic inference. Sometimes, housekeeping data---and often the science data themselves---can be used as predictors of the systematic noise. Linear combinations of simple functions of these predictors are often used as computationally tractable models that can capture the nuisances. These models can be used to fit and subtract systematics prior to investigation of the signals of interest, or they can be used in a simultaneous fit of the systematics and the signals. In this Note, we show that if a Gaussian prior is placed on the weights of the linear components, the weights can be marginalized out with an operation in pure linear algebra, which can (often) be made fast. We illustrate this model by demonstrating the applicability of a linear model for the non-linear systematics in K2 time-series data, where the dominant noise source for many stars is spacecraft motion and variability.
Lainscsek, Claudia; Weyhenmeyer, Jonathan; Hernandez, Manuel E; Poizner, Howard; Sejnowski, Terrence J
2013-01-01
Time series analysis with delay differential equations (DDEs) reveals non-linear properties of the underlying dynamical system and can serve as a non-linear time-domain classification tool. Here global DDE models were used to analyze short segments of simulated time series from a known dynamical system, the Rössler system, in high noise regimes. In a companion paper, we apply the DDE model developed here to classify short segments of encephalographic (EEG) data recorded from patients with Parkinson's disease and healthy subjects. Nine simulated subjects in each of two distinct classes were generated by varying the bifurcation parameter b and keeping the other two parameters (a and c) of the Rössler system fixed. All choices of b were in the chaotic parameter range. We diluted the simulated data using white noise ranging from 10 to -30 dB signal-to-noise ratios (SNR). Structure selection was supervised by selecting the number of terms, delays, and order of non-linearity of the model DDE model that best linearly separated the two classes of data. The distances d from the linear dividing hyperplane was then used to assess the classification performance by computing the area A' under the ROC curve. The selected model was tested on untrained data using repeated random sub-sampling validation. DDEs were able to accurately distinguish the two dynamical conditions, and moreover, to quantify the changes in the dynamics. There was a significant correlation between the dynamical bifurcation parameter b of the simulated data and the classification parameter d from our analysis. This correlation still held for new simulated subjects with new dynamical parameters selected from each of the two dynamical regimes. Furthermore, the correlation was robust to added noise, being significant even when the noise was greater than the signal. We conclude that DDE models may be used as a generalizable and reliable classification tool for even small segments of noisy data.
Non-Linear Dynamical Classification of Short Time Series of the Rössler System in High Noise Regimes
Lainscsek, Claudia; Weyhenmeyer, Jonathan; Hernandez, Manuel E.; Poizner, Howard; Sejnowski, Terrence J.
2013-01-01
Time series analysis with delay differential equations (DDEs) reveals non-linear properties of the underlying dynamical system and can serve as a non-linear time-domain classification tool. Here global DDE models were used to analyze short segments of simulated time series from a known dynamical system, the Rössler system, in high noise regimes. In a companion paper, we apply the DDE model developed here to classify short segments of encephalographic (EEG) data recorded from patients with Parkinson’s disease and healthy subjects. Nine simulated subjects in each of two distinct classes were generated by varying the bifurcation parameter b and keeping the other two parameters (a and c) of the Rössler system fixed. All choices of b were in the chaotic parameter range. We diluted the simulated data using white noise ranging from 10 to −30 dB signal-to-noise ratios (SNR). Structure selection was supervised by selecting the number of terms, delays, and order of non-linearity of the model DDE model that best linearly separated the two classes of data. The distances d from the linear dividing hyperplane was then used to assess the classification performance by computing the area A′ under the ROC curve. The selected model was tested on untrained data using repeated random sub-sampling validation. DDEs were able to accurately distinguish the two dynamical conditions, and moreover, to quantify the changes in the dynamics. There was a significant correlation between the dynamical bifurcation parameter b of the simulated data and the classification parameter d from our analysis. This correlation still held for new simulated subjects with new dynamical parameters selected from each of the two dynamical regimes. Furthermore, the correlation was robust to added noise, being significant even when the noise was greater than the signal. We conclude that DDE models may be used as a generalizable and reliable classification tool for even small segments of noisy data. PMID:24379798
Optimal noise reduction in 3D reconstructions of single particles using a volume-normalized filter
Sindelar, Charles V.; Grigorieff, Nikolaus
2012-01-01
The high noise level found in single-particle electron cryo-microscopy (cryo-EM) image data presents a special challenge for three-dimensional (3D) reconstruction of the imaged molecules. The spectral signal-to-noise ratio (SSNR) and related Fourier shell correlation (FSC) functions are commonly used to assess and mitigate the noise-generated error in the reconstruction. Calculation of the SSNR and FSC usually includes the noise in the solvent region surrounding the particle and therefore does not accurately reflect the signal in the particle density itself. Here we show that the SSNR in a reconstructed 3D particle map is linearly proportional to the fractional volume occupied by the particle. Using this relationship, we devise a novel filter (the “single-particle Wiener filter”) to minimize the error in a reconstructed particle map, if the particle volume is known. Moreover, we show how to approximate this filter even when the volume of the particle is not known, by optimizing the signal within a representative interior region of the particle. We show that the new filter improves on previously proposed error-reduction schemes, including the conventional Wiener filter as well as figure-of-merit weighting, and quantify the relationship between all of these methods by theoretical analysis as well as numeric evaluation of both simulated and experimentally collected data. The single-particle Wiener filter is applicable across a broad range of existing 3D reconstruction techniques, but is particularly well suited to the Fourier inversion method, leading to an efficient and accurate implementation. PMID:22613568
Characterizing the Lyα forest flux probability distribution function using Legendre polynomials
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cieplak, Agnieszka M.; Slosar, Anze
The Lyman-α forest is a highly non-linear field with considerable information available in the data beyond the power spectrum. The flux probability distribution function (PDF) has been used as a successful probe of small-scale physics. In this paper we argue that measuring coefficients of the Legendre polynomial expansion of the PDF offers several advantages over measuring the binned values as is commonly done. In particular, the n-th Legendre coefficient can be expressed as a linear combination of the first n moments, allowing these coefficients to be measured in the presence of noise and allowing a clear route for marginalisation overmore » mean flux. Moreover, in the presence of noise, our numerical work shows that a finite number of coefficients are well measured with a very sharp transition into noise dominance. This compresses the available information into a small number of well-measured quantities. In conclusion, we find that the amount of recoverable information is a very non-linear function of spectral noise that strongly favors fewer quasars measured at better signal to noise.« less
Characterizing the Lyα forest flux probability distribution function using Legendre polynomials
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cieplak, Agnieszka M.; Slosar, Anže, E-mail: acieplak@bnl.gov, E-mail: anze@bnl.gov
The Lyman-α forest is a highly non-linear field with considerable information available in the data beyond the power spectrum. The flux probability distribution function (PDF) has been used as a successful probe of small-scale physics. In this paper we argue that measuring coefficients of the Legendre polynomial expansion of the PDF offers several advantages over measuring the binned values as is commonly done. In particular, the n -th Legendre coefficient can be expressed as a linear combination of the first n moments, allowing these coefficients to be measured in the presence of noise and allowing a clear route for marginalisationmore » over mean flux. Moreover, in the presence of noise, our numerical work shows that a finite number of coefficients are well measured with a very sharp transition into noise dominance. This compresses the available information into a small number of well-measured quantities. We find that the amount of recoverable information is a very non-linear function of spectral noise that strongly favors fewer quasars measured at better signal to noise.« less
Characterizing the Lyα forest flux probability distribution function using Legendre polynomials
Cieplak, Agnieszka M.; Slosar, Anze
2017-10-12
The Lyman-α forest is a highly non-linear field with considerable information available in the data beyond the power spectrum. The flux probability distribution function (PDF) has been used as a successful probe of small-scale physics. In this paper we argue that measuring coefficients of the Legendre polynomial expansion of the PDF offers several advantages over measuring the binned values as is commonly done. In particular, the n-th Legendre coefficient can be expressed as a linear combination of the first n moments, allowing these coefficients to be measured in the presence of noise and allowing a clear route for marginalisation overmore » mean flux. Moreover, in the presence of noise, our numerical work shows that a finite number of coefficients are well measured with a very sharp transition into noise dominance. This compresses the available information into a small number of well-measured quantities. In conclusion, we find that the amount of recoverable information is a very non-linear function of spectral noise that strongly favors fewer quasars measured at better signal to noise.« less
Characterizing the Lyα forest flux probability distribution function using Legendre polynomials
NASA Astrophysics Data System (ADS)
Cieplak, Agnieszka M.; Slosar, Anže
2017-10-01
The Lyman-α forest is a highly non-linear field with considerable information available in the data beyond the power spectrum. The flux probability distribution function (PDF) has been used as a successful probe of small-scale physics. In this paper we argue that measuring coefficients of the Legendre polynomial expansion of the PDF offers several advantages over measuring the binned values as is commonly done. In particular, the n-th Legendre coefficient can be expressed as a linear combination of the first n moments, allowing these coefficients to be measured in the presence of noise and allowing a clear route for marginalisation over mean flux. Moreover, in the presence of noise, our numerical work shows that a finite number of coefficients are well measured with a very sharp transition into noise dominance. This compresses the available information into a small number of well-measured quantities. We find that the amount of recoverable information is a very non-linear function of spectral noise that strongly favors fewer quasars measured at better signal to noise.
Midlatitude detection of ELF whistlers
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sentman, D.D.; Ehring, D.A.
1994-02-01
Narrow-band, whistlerlike magnetic events distinguished by nearly monochromatic signals decreasing in frequency with time have been observed for the first time at midlatitudes in the ELF band. Measurements performed during September 3 to October 5, 1985 at Table Mountain, California (34.4{degrees}N, 117.7{degrees}W), show that the frequency and dispersion characteristics of these events are similar to events detected at auroral latitudes, including a narrow-band magnetic signal monotonically decreasing in frequency from 120 to 60 Hz over a 40 s interval with a mean center frequency of approximately 90 Hz. No echoes were observed. Maximum amplitudes of the magnetic signals ranged frommore » just above the approximately 1 pT Hz{sup {minus}1/2} floor of the ambient background to roughly 20 pT Hz{sup {minus}1/2}. The polarization was predominantly linear in the geographic east-west direction. The midlatitude ELF whistlers reported here have a significantly lower average daily rate of occurrence than those reported for auroral latitudes. However, as with the high-latitude events, they displayed an occurrence rate that is maximum during local daytime. Following Heacock, it is suggested that a possible source for these events is whistler mode lion roars occurring in field-aligned ducts of enhanced cold plasma densities in the magnetosheath into the polar cusp, the waves may propagate to the Earth through the cusp acting as a waveguide. Although lightning is usually considered to be the dominant source of ELF noise in the Earth ionosphere cavity, magnetosheath ELF noise coupled into the cavity at high latitudes may represent an additional source. The fractional intensities of the natural ELF noise power within the cavity that are generated by this mechanism are presently unknown. 28 refs., 5 figs., 1 tab.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Samal, Pramoda Kumar; Jain, Pankaj; Saha, Rajib
We estimate cosmic microwave background (CMB) polarization and temperature power spectra using Wilkinson Microwave Anisotropy Probe (WMAP) 5 year foreground contaminated maps. The power spectrum is estimated by using a model-independent method, which does not utilize directly the diffuse foreground templates nor the detector noise model. The method essentially consists of two steps: (1) removal of diffuse foregrounds contamination by making linear combination of individual maps in harmonic space and (2) cross-correlation of foreground cleaned maps to minimize detector noise bias. For the temperature power spectrum we also estimate and subtract residual unresolved point source contamination in the cross-power spectrummore » using the point source model provided by the WMAP science team. Our TT, TE, and EE power spectra are in good agreement with the published results of the WMAP science team. We perform detailed numerical simulations to test for bias in our procedure. We find that the bias is small in almost all cases. A negative bias at low l in TT power spectrum has been pointed out in an earlier publication. We find that the bias-corrected quadrupole power (l(l + 1)C{sub l} /2{pi}) is 532 {mu}K{sup 2}, approximately 2.5 times the estimate (213.4 {mu}K{sup 2}) made by the WMAP team.« less
Context-dependent effects of noise on echolocation pulse characteristics in free-tailed bats
Smotherman, Michael S.
2010-01-01
Background noise evokes a similar suite of adaptations in the acoustic structure of communication calls across a diverse range of vertebrates. Echolocating bats may have evolved specialized vocal strategies for echolocating in noise, but also seem to exhibit generic vertebrate responses such as the ubiquitous Lombard response. We wondered how bats balance generic and echolocation-specific vocal responses to noise. To address this question, we first characterized the vocal responses of flying free-tailed bats (Tadarida brasiliensis) to broadband noises varying in amplitude. Secondly, we measured the bats’ responses to band-limited noises that varied in the extent of overlap with their echolocation pulse bandwidth. We hypothesized that the bats’ generic responses to noise would be graded proportionally with noise amplitude, total bandwidth and frequency content, and consequently that more selective responses to band-limited noise such as the jamming avoidance response could be explained by a linear decomposition of the response to broadband noise. Instead, the results showed that both the nature and the magnitude of the vocal responses varied with the acoustic structure of the outgoing pulse as well as non-linearly with noise parameters. We conclude that free-tailed bats utilize separate generic and specialized vocal responses to noise in a context-dependent fashion. PMID:19672604
Stochastic maps, continuous approximation, and stable distribution
NASA Astrophysics Data System (ADS)
Kessler, David A.; Burov, Stanislav
2017-10-01
A continuous approximation framework for general nonlinear stochastic as well as deterministic discrete maps is developed. For the stochastic map with uncorelated Gaussian noise, by successively applying the Itô lemma, we obtain a Langevin type of equation. Specifically, we show how nonlinear maps give rise to a Langevin description that involves multiplicative noise. The multiplicative nature of the noise induces an additional effective force, not present in the absence of noise. We further exploit the continuum description and provide an explicit formula for the stable distribution of the stochastic map and conditions for its existence. Our results are in good agreement with numerical simulations of several maps.
Iterative algorithms for a non-linear inverse problem in atmospheric lidar
NASA Astrophysics Data System (ADS)
Denevi, Giulia; Garbarino, Sara; Sorrentino, Alberto
2017-08-01
We consider the inverse problem of retrieving aerosol extinction coefficients from Raman lidar measurements. In this problem the unknown and the data are related through the exponential of a linear operator, the unknown is non-negative and the data follow the Poisson distribution. Standard methods work on the log-transformed data and solve the resulting linear inverse problem, but neglect to take into account the noise statistics. In this study we show that proper modelling of the noise distribution can improve substantially the quality of the reconstructed extinction profiles. To achieve this goal, we consider the non-linear inverse problem with non-negativity constraint, and propose two iterative algorithms derived using the Karush-Kuhn-Tucker conditions. We validate the algorithms with synthetic and experimental data. As expected, the proposed algorithms out-perform standard methods in terms of sensitivity to noise and reliability of the estimated profile.
Measurement of SQUID noise levels for SuperCDMS SNOLAB detectors - Final Paper
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lee, Maxwell
SuperCDMS SNOLAB is a second generation direct dark matter search. In the SuperCDMS SNOLAB experiment, detectors are able to pick up from signals from dark matter nuclear recoil interactions which occur inside the bulk of the detectors. These interactions produce both phonon and charge signals. HEMTs read out charge signals whereas TES are used to detect phonon signals which are then read out by SQUID amplifiers. SQUID amplifiers must add negligible noise to the TES intrinsic noise which has been previously measured and is approximately 50pA/√Hz down to 100Hz for ease of signal distinguishability in dark matter nuclear interactions. Themore » intrinsic noise level of the SQUID was tested in the SLAC 300mK fridge and determined to provide adequately low levels of noise with a floor of approximately 3pA/√Hz. Furthermore, a 10x amplifier was tested for addition of extraneous noise. This noise was investigated with and without this amplifier, and it was found that it did not add a significant amount of noise to the intrinsic SQUID noise.« less
Nichols, J.M.; Link, W.A.; Murphy, K.D.; Olson, C.C.
2010-01-01
This work discusses a Bayesian approach to approximating the distribution of parameters governing nonlinear structural systems. Specifically, we use a Markov Chain Monte Carlo method for sampling the posterior parameter distributions thus producing both point and interval estimates for parameters. The method is first used to identify both linear and nonlinear parameters in a multiple degree-of-freedom structural systems using free-decay vibrations. The approach is then applied to the problem of identifying the location, size, and depth of delamination in a model composite beam. The influence of additive Gaussian noise on the response data is explored with respect to the quality of the resulting parameter estimates.
Noise removal in extended depth of field microscope images through nonlinear signal processing.
Zahreddine, Ramzi N; Cormack, Robert H; Cogswell, Carol J
2013-04-01
Extended depth of field (EDF) microscopy, achieved through computational optics, allows for real-time 3D imaging of live cell dynamics. EDF is achieved through a combination of point spread function engineering and digital image processing. A linear Wiener filter has been conventionally used to deconvolve the image, but it suffers from high frequency noise amplification and processing artifacts. A nonlinear processing scheme is proposed which extends the depth of field while minimizing background noise. The nonlinear filter is generated via a training algorithm and an iterative optimizer. Biological microscope images processed with the nonlinear filter show a significant improvement in image quality and signal-to-noise ratio over the conventional linear filter.
Desired Accuracy Estimation of Noise Function from ECG Signal by Fuzzy Approach
Vahabi, Zahra; Kermani, Saeed
2012-01-01
Unknown noise and artifacts present in medical signals with non-linear fuzzy filter will be estimated and then removed. An adaptive neuro-fuzzy interference system which has a non-linear structure presented for the noise function prediction by before Samples. This paper is about a neuro-fuzzy method to estimate unknown noise of Electrocardiogram signal. Adaptive neural combined with Fuzzy System to construct a fuzzy Predictor. For this system setting parameters such as the number of Membership Functions for each input and output, training epochs, type of MFs for each input and output, learning algorithm and etc. is determined by learning data. At the end simulated experimental results are presented for proper validation. PMID:23717810
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shu, Deming
An U.S. DOE Cooperative Research and Development Agreement (CRADA) between ANL and Optodyne, Inc. has been established to develop a prototype laser Doppler displacement encoder system with ultra-low noise level for linear measurements to sub-nanometer resolution for synchrotron radiation applications. We have improved the heterodyne efficiency and reduced the detector shot noises by proper shielding and adding a low-pass filter. The laser Doppler displacement encoder system prototype demonstrated a ~ 1 nm system output noise floor with single reflection optics. With multiple-pass optical arrangement, 0.1 nm scale closed-loop feedback control is achieved.
NASA Astrophysics Data System (ADS)
Guo, Feng; Wang, Xue-Yuan; Zhu, Cheng-Yin; Cheng, Xiao-Feng; Zhang, Zheng-Yu; Huang, Xu-Hui
2017-12-01
The stochastic resonance for a fractional oscillator with time-delayed kernel and quadratic trichotomous noise is investigated. Applying linear system theory and Laplace transform, the system output amplitude (SPA) for the fractional oscillator is obtained. It is found that the SPA is a periodical function of the kernel delayed-time. Stochastic multiplicative phenomenon appears on the SPA versus the driving frequency, versus the noise amplitude, and versus the fractional exponent. The non-monotonous dependence of the SPA on the system parameters is also discussed.
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…
Effect of mass housing settlement type on the comfortable open areas in terms of noise.
Akdağ, Neşe Yüğrük; Gedik, Gülay Zorer; Kiraz, Fatih; Şener, Bekir
2017-09-12
The layout of the structures according to the noise source is an important parameter in terms of the level of noise reaching to both open usage areas and the structure surfaces. In this paper, it is aimed to reveal the effect of mass housing settlement type on the size of suitable open usage areas in terms of noise. Comfortable open usage areas in 25 mass housing alternatives are determined for the case of being affected by three different road noises. The reliability of the simulation results is validated by on-site noise level measurements. As a result, it is seen that better results are obtained in linear, L, C, and U type alternatives than point-type blocks. Especially in alternatives consisting of point-and linear-type blocks, if the noise level is above 75 Leq (dBA), the percentage of comfortable open usage areas is very low. It is determined that the percentage of comfortable open areas increases between 50 and 100% by means of appropriately designed noise barriers.
A Low Noise CMOS Readout Based on a Polymer-Coated SAW Array for Miniature Electronic Nose
Wu, Cheng-Chun; Liu, Szu-Chieh; Chiu, Shih-Wen; Tang, Kea-Tiong
2016-01-01
An electronic nose (E-Nose) is one of the applications for surface acoustic wave (SAW) sensors. In this paper, we present a low-noise complementary metal–oxide–semiconductor (CMOS) readout application-specific integrated circuit (ASIC) based on an SAW sensor array for achieving a miniature E-Nose. The center frequency of the SAW sensors was measured to be approximately 114 MHz. Because of interference between the sensors, we designed a low-noise CMOS frequency readout circuit to enable the SAW sensor to obtain frequency variation. The proposed circuit was fabricated in Taiwan Semiconductor Manufacturing Company (TSMC) 0.18 μm 1P6M CMOS process technology. The total chip size was nearly 1203 × 1203 μm2. The chip was operated at a supply voltage of 1 V for a digital circuit and 1.8 V for an analog circuit. The least measurable difference between frequencies was 4 Hz. The detection limit of the system, when estimated using methanol and ethanol, was 0.1 ppm. Their linearity was in the range of 0.1 to 26,000 ppm. The power consumption levels of the analog and digital circuits were 1.742 mW and 761 μW, respectively. PMID:27792131
A Low Noise CMOS Readout Based on a Polymer-Coated SAW Array for Miniature Electronic Nose.
Wu, Cheng-Chun; Liu, Szu-Chieh; Chiu, Shih-Wen; Tang, Kea-Tiong
2016-10-25
An electronic nose (E-Nose) is one of the applications for surface acoustic wave (SAW) sensors. In this paper, we present a low-noise complementary metal-oxide-semiconductor (CMOS) readout application-specific integrated circuit (ASIC) based on an SAW sensor array for achieving a miniature E-Nose. The center frequency of the SAW sensors was measured to be approximately 114 MHz. Because of interference between the sensors, we designed a low-noise CMOS frequency readout circuit to enable the SAW sensor to obtain frequency variation. The proposed circuit was fabricated in Taiwan Semiconductor Manufacturing Company (TSMC) 0.18 μm 1P6M CMOS process technology. The total chip size was nearly 1203 × 1203 μm². The chip was operated at a supply voltage of 1 V for a digital circuit and 1.8 V for an analog circuit. The least measurable difference between frequencies was 4 Hz. The detection limit of the system, when estimated using methanol and ethanol, was 0.1 ppm. Their linearity was in the range of 0.1 to 26,000 ppm. The power consumption levels of the analog and digital circuits were 1.742 mW and 761 μW, respectively.
Noise Reduction in Brainwaves by Using Both EEG Signals and Frontal Viewing Camera Images
Bang, Jae Won; Choi, Jong-Suk; Park, Kang Ryoung
2013-01-01
Electroencephalogram (EEG)-based brain-computer interfaces (BCIs) have been used in various applications, including human–computer interfaces, diagnosis of brain diseases, and measurement of cognitive status. However, EEG signals can be contaminated with noise caused by user's head movements. Therefore, we propose a new method that combines an EEG acquisition device and a frontal viewing camera to isolate and exclude the sections of EEG data containing these noises. This method is novel in the following three ways. First, we compare the accuracies of detecting head movements based on the features of EEG signals in the frequency and time domains and on the motion features of images captured by the frontal viewing camera. Second, the features of EEG signals in the frequency domain and the motion features captured by the frontal viewing camera are selected as optimal ones. The dimension reduction of the features and feature selection are performed using linear discriminant analysis. Third, the combined features are used as inputs to support vector machine (SVM), which improves the accuracy in detecting head movements. The experimental results show that the proposed method can detect head movements with an average error rate of approximately 3.22%, which is smaller than that of other methods. PMID:23669713
Adaptive aperture for Geiger mode avalanche photodiode flash ladar systems.
Wang, Liang; Han, Shaokun; Xia, Wenze; Lei, Jieyu
2018-02-01
Although the Geiger-mode avalanche photodiode (GM-APD) flash ladar system offers the advantages of high sensitivity and simple construction, its detection performance is influenced not only by the incoming signal-to-noise ratio but also by the absolute number of noise photons. In this paper, we deduce a hyperbolic approximation to estimate the noise-photon number from the false-firing percentage in a GM-APD flash ladar system under dark conditions. By using this hyperbolic approximation function, we introduce a method to adapt the aperture to reduce the number of incoming background-noise photons. Finally, the simulation results show that the adaptive-aperture method decreases the false probability in all cases, increases the detection probability provided that the signal exceeds the noise, and decreases the average ranging error per frame.
Adaptive aperture for Geiger mode avalanche photodiode flash ladar systems
NASA Astrophysics Data System (ADS)
Wang, Liang; Han, Shaokun; Xia, Wenze; Lei, Jieyu
2018-02-01
Although the Geiger-mode avalanche photodiode (GM-APD) flash ladar system offers the advantages of high sensitivity and simple construction, its detection performance is influenced not only by the incoming signal-to-noise ratio but also by the absolute number of noise photons. In this paper, we deduce a hyperbolic approximation to estimate the noise-photon number from the false-firing percentage in a GM-APD flash ladar system under dark conditions. By using this hyperbolic approximation function, we introduce a method to adapt the aperture to reduce the number of incoming background-noise photons. Finally, the simulation results show that the adaptive-aperture method decreases the false probability in all cases, increases the detection probability provided that the signal exceeds the noise, and decreases the average ranging error per frame.
Aircraft and road traffic noise and children's cognition and health: a cross-national study.
Stansfeld, S A; Berglund, B; Clark, C; Lopez-Barrio, I; Fischer, P; Ohrström, E; Haines, M M; Head, J; Hygge, S; van Kamp, I; Berry, B F
Exposure to environmental stressors can impair children's health and their cognitive development. The effects of air pollution, lead, and chemicals have been studied, but there has been less emphasis on the effects of noise. Our aim, therefore, was to assess the effect of exposure to aircraft and road traffic noise on cognitive performance and health in children. We did a cross-national, cross-sectional study in which we assessed 2844 of 3207 children aged 9-10 years who were attending 89 schools of 77 approached in the Netherlands, 27 in Spain, and 30 in the UK located in local authority areas around three major airports. We selected children by extent of exposure to external aircraft and road traffic noise at school as predicted from noise contour maps, modelling, and on-site measurements, and matched schools within countries for socioeconomic status. We measured cognitive and health outcomes with standardised tests and questionnaires administered in the classroom. We also used a questionnaire to obtain information from parents about socioeconomic status, their education, and ethnic origin. We identified linear exposure-effect associations between exposure to chronic aircraft noise and impairment of reading comprehension (p=0.0097) and recognition memory (p=0.0141), and a non-linear association with annoyance (p<0.0001) maintained after adjustment for mother's education, socioeconomic status, longstanding illness, and extent of classroom insulation against noise. Exposure to road traffic noise was linearly associated with increases in episodic memory (conceptual recall: p=0.0066; information recall: p=0.0489), but also with annoyance (p=0.0047). Neither aircraft noise nor traffic noise affected sustained attention, self-reported health, or overall mental health. Our findings indicate that a chronic environmental stressor-aircraft noise-could impair cognitive development in children, specifically reading comprehension. Schools exposed to high levels of aircraft noise are not healthy educational environments.
Annoyance caused by aircraft en route noise
NASA Astrophysics Data System (ADS)
McCurdy, David A.
1992-03-01
A laboratory experiment was conducted to quantify the annoyance response of people on the ground to enroute noise generated by aircraft at cruise conditions. The en route noises were ground level recordings of eight advanced turboprop aircraft flyovers and six conventional turbofan flyovers. The eight advanced turboprop enroute noises represented the NASA Propfan Test Assessment aircraft operating at different combinations of altitude, aircraft Mach number, and propeller tip speed. The conventional turbofan en route noises represented six different commercial airliners. The overall durations of the en route noises varied from approximately 40 to 160 sec. In the experiment, 32 subjects judged the annoyance of the en route noises as well as recordings of the takeoff and landing noises of each of 5 conventional turboprop and 5 conventional turbofan aircraft. Each of the noises was presented at three sound pressure levels to the subjects in an anechoic listening room. Analysis of the judgments found small differences in annoyance between three combinations of aircraft type and operation. Current tone and corrections did not significantly improve en route annoyance prediction. The optimum duration-correction magnitude for en route noise was approximately 1 dB per doubling of effective duration.
Annoyance caused by aircraft en route noise
NASA Technical Reports Server (NTRS)
Mccurdy, David A.
1992-01-01
A laboratory experiment was conducted to quantify the annoyance response of people on the ground to enroute noise generated by aircraft at cruise conditions. The en route noises were ground level recordings of eight advanced turboprop aircraft flyovers and six conventional turbofan flyovers. The eight advanced turboprop enroute noises represented the NASA Propfan Test Assessment aircraft operating at different combinations of altitude, aircraft Mach number, and propeller tip speed. The conventional turbofan en route noises represented six different commercial airliners. The overall durations of the en route noises varied from approximately 40 to 160 sec. In the experiment, 32 subjects judged the annoyance of the en route noises as well as recordings of the takeoff and landing noises of each of 5 conventional turboprop and 5 conventional turbofan aircraft. Each of the noises was presented at three sound pressure levels to the subjects in an anechoic listening room. Analysis of the judgments found small differences in annoyance between three combinations of aircraft type and operation. Current tone and corrections did not significantly improve en route annoyance prediction. The optimum duration-correction magnitude for en route noise was approximately 1 dB per doubling of effective duration.
Perceptual learning improves visual performance in juvenile amblyopia.
Li, Roger W; Young, Karen G; Hoenig, Pia; Levi, Dennis M
2005-09-01
To determine whether practicing a position-discrimination task improves visual performance in children with amblyopia and to determine the mechanism(s) of improvement. Five children (age range, 7-10 years) with amblyopia practiced a positional acuity task in which they had to judge which of three pairs of lines was misaligned. Positional noise was produced by distributing the individual patches of each line segment according to a Gaussian probability function. Observers were trained at three noise levels (including 0), with each observer performing between 3000 and 4000 responses in 7 to 10 sessions. Trial-by-trial feedback was provided. Four of the five observers showed significant improvement in positional acuity. In those four observers, on average, positional acuity with no noise improved by approximately 32% and with high noise by approximately 26%. A position-averaging model was used to parse the improvement into an increase in efficiency or a decrease in equivalent input noise. Two observers showed increased efficiency (51% and 117% improvements) with no significant change in equivalent input noise across sessions. The other two observers showed both a decrease in equivalent input noise (18% and 29%) and an increase in efficiency (17% and 71%). All five observers showed substantial improvement in Snellen acuity (approximately 26%) after practice. Perceptual learning can improve visual performance in amblyopic children. The improvement can be parsed into two important factors: decreased equivalent input noise and increased efficiency. Perceptual learning techniques may add an effective new method to the armamentarium of amblyopia treatments.
NASA Astrophysics Data System (ADS)
Dai, Xiaoqian; Tian, Jie; Chen, Zhe
2010-03-01
Parametric images can represent both spatial distribution and quantification of the biological and physiological parameters of tracer kinetics. The linear least square (LLS) method is a well-estimated linear regression method for generating parametric images by fitting compartment models with good computational efficiency. However, bias exists in LLS-based parameter estimates, owing to the noise present in tissue time activity curves (TTACs) that propagates as correlated error in the LLS linearized equations. To address this problem, a volume-wise principal component analysis (PCA) based method is proposed. In this method, firstly dynamic PET data are properly pre-transformed to standardize noise variance as PCA is a data driven technique and can not itself separate signals from noise. Secondly, the volume-wise PCA is applied on PET data. The signals can be mostly represented by the first few principle components (PC) and the noise is left in the subsequent PCs. Then the noise-reduced data are obtained using the first few PCs by applying 'inverse PCA'. It should also be transformed back according to the pre-transformation method used in the first step to maintain the scale of the original data set. Finally, the obtained new data set is used to generate parametric images using the linear least squares (LLS) estimation method. Compared with other noise-removal method, the proposed method can achieve high statistical reliability in the generated parametric images. The effectiveness of the method is demonstrated both with computer simulation and with clinical dynamic FDG PET study.
Separation and reconstruction of high pressure water-jet reflective sound signal based on ICA
NASA Astrophysics Data System (ADS)
Yang, Hongtao; Sun, Yuling; Li, Meng; Zhang, Dongsu; Wu, Tianfeng
2011-12-01
The impact of high pressure water-jet on the different materials target will produce different reflective mixed sound. In order to reconstruct the reflective sound signals distribution on the linear detecting line accurately and to separate the environment noise effectively, the mixed sound signals acquired by linear mike array were processed by ICA. The basic principle of ICA and algorithm of FASTICA were described in detail. The emulation experiment was designed. The environment noise signal was simulated by using band-limited white noise and the reflective sound signal was simulated by using pulse signal. The reflective sound signal attenuation produced by the different distance transmission was simulated by weighting the sound signal with different contingencies. The mixed sound signals acquired by linear mike array were synthesized by using the above simulated signals and were whitened and separated by ICA. The final results verified that the environment noise separation and the reconstruction of the detecting-line sound distribution can be realized effectively.
Wang, Shau-Chun; Lin, Chiao-Juan; Chiang, Shu-Min; Yu, Sung-Nien
2008-03-15
This paper reports a simple chemometric technique to alter the noise spectrum of a liquid chromatography-mass spectrometry (LC-MS) chromatogram between two consecutive second-derivative filter procedures to improve the peak signal-to-noise (S/N) ratio enhancement. This technique is to multiply one second-derivative filtered LC-MS chromatogram with another artificial chromatogram added with thermal noises prior to the other second-derivative filter. Because the second-derivative filter cannot eliminate frequency components within its own filter bandwidth, more efficient peak S/N ratio improvement cannot be accomplished using consecutive second-derivative filter procedures to process LC-MS chromatograms. In contrast, when the second-derivative filtered LC-MS chromatogram is conditioned with the multiplication alteration prior to the other second-derivative filter, much better ratio improvement is achieved. The noise frequency spectrum of the second-derivative filtered chromatogram, which originally contains frequency components within the filter bandwidth, is altered to span a broader range with multiplication operation. When the frequency range of this modified noise spectrum shifts toward the other regimes, the other second-derivative filter, working as a band-pass filter, is able to provide better filtering efficiency to obtain higher peak S/N ratios. Real LC-MS chromatograms, of which 5-fold peak S/N ratio improvement achieved with two consecutive second-derivative filters remains the same S/N ratio improvement using a one-step second-derivative filter, are improved to accomplish much better ratio enhancement, approximately 25-fold or higher when the noise frequency spectrum is modified between two matched filters. The linear standard curve using the filtered LC-MS signals is validated. The filtered LC-MS signals are also more reproducible. The more accurate determinations of very low-concentration samples (S/N ratio about 5-7) are obtained via standard addition procedures using the filtered signals rather than the determinations using the original signals.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, B.; Zeng, G. L.
2006-09-15
A rotating slat collimator can be used to acquire planar-integral data. It achieves higher geometric efficiency than a parallel-hole collimator by accepting more photons, but the planar-integral data contain less tomographic information that may result in larger noise amplification in the reconstruction. Lodge evaluated the rotating slat system and the parallel-hole system based on noise behavior for an FBP reconstruction. Here, we evaluate the noise propagation properties of the two collimation systems for iterative reconstruction. We extend Huesman's noise propagation analysis of the line-integral system to the planar-integral case, and show that approximately 2.0(D/dp) SPECT angles, 2.5(D/dp) self-spinning angles atmore » each detector position, and a 0.5dp detector sampling interval are required in order for the planar-integral data to be efficiently utilized. Here, D is the diameter of the object and dp is the linear dimension of the voxels that subdivide the object. The noise propagation behaviors of the two systems are then compared based on a least-square reconstruction using the ratio of the SNR in the image reconstructed using a planar-integral system to that reconstructed using a line-integral system. The ratio is found to be proportional to {radical}(F/D), where F is a geometric efficiency factor. This result has been verified by computer simulations. It confirms that for an iterative reconstruction, the noise tradeoff of the two systems is not only dependent on the increase of the geometric efficiency afforded by the planar projection method, but also dependent on the size of the object. The planar-integral system works better for small objects, while the line-integral system performs better for large ones. This result is consistent with Lodge's results based on the FBP method.« less
Approximate dynamic programming for optimal stationary control with control-dependent noise.
Jiang, Yu; Jiang, Zhong-Ping
2011-12-01
This brief studies the stochastic optimal control problem via reinforcement learning and approximate/adaptive dynamic programming (ADP). A policy iteration algorithm is derived in the presence of both additive and multiplicative noise using Itô calculus. The expectation of the approximated cost matrix is guaranteed to converge to the solution of some algebraic Riccati equation that gives rise to the optimal cost value. Moreover, the covariance of the approximated cost matrix can be reduced by increasing the length of time interval between two consecutive iterations. Finally, a numerical example is given to illustrate the efficiency of the proposed ADP methodology.
Noise elimination algorithm for modal analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bao, X. X., E-mail: baoxingxian@upc.edu.cn; Li, C. L.; Xiong, C. B.
2015-07-27
Modal analysis is an ongoing interdisciplinary physical issue. Modal parameters estimation is applied to determine the dynamic characteristics of structures under vibration excitation. Modal analysis is more challenging for the measured vibration response signals are contaminated with noise. This study develops a mathematical algorithm of structured low rank approximation combined with the complex exponential method to estimate the modal parameters. Physical experiments using a steel cantilever beam with ten accelerometers mounted, excited by an impulse load, demonstrate that this method can significantly eliminate noise from measured signals and accurately identify the modal frequencies and damping ratios. This study provides amore » fundamental mechanism of noise elimination using structured low rank approximation in physical fields.« less
SNDR enhancement in noisy sinusoidal signals by non-linear processing elements
NASA Astrophysics Data System (ADS)
Martorell, Ferran; McDonnell, Mark D.; Abbott, Derek; Rubio, Antonio
2007-06-01
We investigate the possibility of building linear amplifiers capable of enhancing the Signal-to-Noise and Distortion Ratio (SNDR) of sinusoidal input signals using simple non-linear elements. Other works have proven that it is possible to enhance the Signal-to-Noise Ratio (SNR) by using limiters. In this work we study a soft limiter non-linear element with and without hysteresis. We show that the SNDR of sinusoidal signals can be enhanced by 0.94 dB using a wideband soft limiter and up to 9.68 dB using a wideband soft limiter with hysteresis. These results indicate that linear amplifiers could be constructed using non-linear circuits with hysteresis. This paper presents mathematical descriptions for the non-linear elements using statistical parameters. Using these models, the input-output SNDR enhancement is obtained by optimizing the non-linear transfer function parameters to maximize the output SNDR.
Statistics of a neuron model driven by asymmetric colored noise.
Müller-Hansen, Finn; Droste, Felix; Lindner, Benjamin
2015-02-01
Irregular firing of neurons can be modeled as a stochastic process. Here we study the perfect integrate-and-fire neuron driven by dichotomous noise, a Markovian process that jumps between two states (i.e., possesses a non-Gaussian statistics) and exhibits nonvanishing temporal correlations (i.e., represents a colored noise). Specifically, we consider asymmetric dichotomous noise with two different transition rates. Using a first-passage-time formulation, we derive exact expressions for the probability density and the serial correlation coefficient of the interspike interval (time interval between two subsequent neural action potentials) and the power spectrum of the spike train. Furthermore, we extend the model by including additional Gaussian white noise, and we give approximations for the interspike interval (ISI) statistics in this case. Numerical simulations are used to validate the exact analytical results for pure dichotomous noise, and to test the approximations of the ISI statistics when Gaussian white noise is included. The results may help to understand how correlations and asymmetry of noise and signals in nerve cells shape neuronal firing statistics.
2012-08-01
small data noise and model error, the discrete Hessian can be approximated by a low-rank matrix. This in turn enables fast solution of an appropriately...implication of the compactness of the Hessian is that for small data noise and model error, the discrete Hessian can be approximated by a low-rank matrix. This...probability distribution is given by the inverse of the Hessian of the negative log likelihood function. For Gaussian data noise and model error, this
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.
Synthesis procedure for linear time-varying feedback systems with large parameter ignorance
NASA Technical Reports Server (NTRS)
Mcdonald, T. E., Jr.
1972-01-01
The development of synthesis procedures for linear time-varying feedback systems is considered. It is assumed that the plant can be described by linear differential equations with time-varying coefficients; however, ignorance is associated with the plant in that only the range of the time-variations are known instead of exact functional relationships. As a result of this plant ignorance the use of time-varying compensation is ineffective so that only time-invariant compensation is employed. In addition, there is a noise source at the plant output which feeds noise through the feedback elements to the plant input. Because of this noise source the gain of the feedback elements must be as small as possible. No attempt is made to develop a stability criterion for time-varying systems in this work.
NASA Astrophysics Data System (ADS)
Miecznik, Grzegorz; Illing, Rainer; Petroy, Shelley; Sokolik, Irina N.
2005-07-01
Linearly polarized radiation is sensitive to the microphysical properties of aerosols, namely, to the particle- size distribution and refractive index. The discriminating power of polarized radiation increases strongly with the increasing range of scattering angles and the addition of multiple wavelengths. The polarization and directionality of the Earth's reflectances (POLDER) missions demonstrate that some aerosol properties can be successfully derived from spaceborne polarimetric, multiangular measurements at two visible wavelengths. We extend the concept to analyze the retrieval capabilities of a spaceborne instrument with six polarimetric channels at 412, 445, 555, 865, 1250, and 2250 nm, measuring approximately 100 scattering angles covering a range between 50 and 150 deg. Our focus is development of an analysis methodology that can help quantify the benefits of such multiangular and multispectral polarimetric measurements. To that goal we employ a sensitivity metric approach in a framework of the principal-component analysis. The radiances and noise used to construct the sensitivity metric are calculated with the realistic solar flux for representative orbital viewing geometries, accounting for surface reflection from the ground, and statistical and calibration errors of a notional instrument. Spherical aerosol particles covering a range of representative microphysical properties (effective radius, effective variance, real and imaginary parts of the refractive index, single-scattering albedo) are considered in the calculations. We find that there is a limiting threshold for the effective size (approximately 0.7 μm), below which the weak scattering intensity results in a decreased signal-to-noise ratio and minimal polarization sensitivity, precluding reliable aerosol retrievals. For such small particles, close to the Rayleigh scattering limit, the total intensity provides a much stronger aerosol signature than the linear polarization, inspiring retrieval when the combined signals of intensities and the polarization fraction are used. We also find a strong correlation between aerosol parameters, in particular between the effective size and the variance, which forces one to simultaneously retrieve at least these two parameters.
Some comparisons of complexity in dictionary-based and linear computational models.
Gnecco, Giorgio; Kůrková, Věra; Sanguineti, Marcello
2011-03-01
Neural networks provide a more flexible approximation of functions than traditional linear regression. In the latter, one can only adjust the coefficients in linear combinations of fixed sets of functions, such as orthogonal polynomials or Hermite functions, while for neural networks, one may also adjust the parameters of the functions which are being combined. However, some useful properties of linear approximators (such as uniqueness, homogeneity, and continuity of best approximation operators) are not satisfied by neural networks. Moreover, optimization of parameters in neural networks becomes more difficult than in linear regression. Experimental results suggest that these drawbacks of neural networks are offset by substantially lower model complexity, allowing accuracy of approximation even in high-dimensional cases. We give some theoretical results comparing requirements on model complexity for two types of approximators, the traditional linear ones and so called variable-basis types, which include neural networks, radial, and kernel models. We compare upper bounds on worst-case errors in variable-basis approximation with lower bounds on such errors for any linear approximator. Using methods from nonlinear approximation and integral representations tailored to computational units, we describe some cases where neural networks outperform any linear approximator. Copyright © 2010 Elsevier Ltd. All rights reserved.
Alegre-Cortés, J; Soto-Sánchez, C; Pizá, Á G; Albarracín, A L; Farfán, F D; Felice, C J; Fernández, E
2016-07-15
Linear analysis has classically provided powerful tools for understanding the behavior of neural populations, but the neuron responses to real-world stimulation are nonlinear under some conditions, and many neuronal components demonstrate strong nonlinear behavior. In spite of this, temporal and frequency dynamics of neural populations to sensory stimulation have been usually analyzed with linear approaches. In this paper, we propose the use of Noise-Assisted Multivariate Empirical Mode Decomposition (NA-MEMD), a data-driven template-free algorithm, plus the Hilbert transform as a suitable tool for analyzing population oscillatory dynamics in a multi-dimensional space with instantaneous frequency (IF) resolution. The proposed approach was able to extract oscillatory information of neurophysiological data of deep vibrissal nerve and visual cortex multiunit recordings that were not evidenced using linear approaches with fixed bases such as the Fourier analysis. Texture discrimination analysis performance was increased when Noise-Assisted Multivariate Empirical Mode plus Hilbert transform was implemented, compared to linear techniques. Cortical oscillatory population activity was analyzed with precise time-frequency resolution. Similarly, NA-MEMD provided increased time-frequency resolution of cortical oscillatory population activity. Noise-Assisted Multivariate Empirical Mode Decomposition plus Hilbert transform is an improved method to analyze neuronal population oscillatory dynamics overcoming linear and stationary assumptions of classical methods. Copyright © 2016 Elsevier B.V. All rights reserved.
Speyer, Gavriel; Kaczkowski, Peter J.; Brayman, Andrew A.; Crum, Lawrence A.
2010-01-01
Accurate monitoring of high intensity focused ultrasound (HIFU) therapy is critical for widespread clinical use. Pulse-echo diagnostic ultrasound (DU) is known to exhibit temperature sensitivity through relative changes in time-of-flight between two sets of radio frequency (RF) backscatter measurements, one acquired before and one after therapy. These relative displacements, combined with knowledge of the exposure protocol, material properties, heat transfer, and measurement noise statistics, provide a natural framework for estimating the administered heating, and thereby therapy. The proposed method, termed displacement analysis, identifies the relative displacements using linearly independent displacement patterns, or modes, each induced by a particular time-varying heating applied during the exposure interval. These heating modes are themselves linearly independent. This relationship implies that a linear combination of displacement modes aligning the DU measurements is the response to an identical linear combination of heating modes, providing the heating estimate. Furthermore, the accuracy of coefficient estimates in this approximation is determined a priori, characterizing heating, thermal dose, and temperature estimates for any given protocol. Predicted performance is validated using simulations and experiments in alginate gel phantoms. Evidence for a spatially distributed interaction between temperature and time-of-flight changes is presented. PMID:20649206
Fast estimate of Hartley entropy in image sharpening
NASA Astrophysics Data System (ADS)
Krbcová, Zuzana; Kukal, Jaromír.; Svihlik, Jan; Fliegel, Karel
2016-09-01
Two classes of linear IIR filters: Laplacian of Gaussian (LoG) and Difference of Gaussians (DoG) are frequently used as high pass filters for contextual vision and edge detection. They are also used for image sharpening when linearly combined with the original image. Resulting sharpening filters are radially symmetric in spatial and frequency domains. Our approach is based on the radial approximation of unknown optimal filter, which is designed as a weighted sum of Gaussian filters with various radii. The novel filter is designed for MRI image enhancement where the image intensity represents anatomical structure plus additive noise. We prefer the gradient norm of Hartley entropy of whole image intensity as a measure which has to be maximized for the best sharpening. The entropy estimation procedure is as fast as FFT included in the filter but this estimate is a continuous function of enhanced image intensities. Physically motivated heuristic is used for optimum sharpening filter design by its parameter tuning. Our approach is compared with Wiener filter on MRI images.
Analysis of the Laser Calibration System for the CMS HCAL at CERN's Large Hadron Collider
NASA Astrophysics Data System (ADS)
Lebolo, Luis
2005-11-01
The European Organization for Nuclear Physics' (CERN) Large Hadron Collider uses the Compact Muon Solenoid (CMS) detector to measure collision products from proton-proton interactions. CMS uses a hadron calorimeter (HCAL) to measure the energy and position of quarks and gluons by reconstructing their hadronic decay products. An essential component of the detector is the calibration system, which was evaluated in terms of its misalignment, linearity, and resolution. In order to analyze the data, the authors created scripts in ROOT 5.02/00 and C++. The authors also used Mathematica 5.1 to perform complex mathematics and AutoCAD 2006 to produce optical ray traces. The misalignment of the optical components was found to be satisfactory; the Hybrid Photodiodes (HPDs) were confirmed to be linear; the constant, noise and stochastic contributions to its resolution were analyzed; and the quantum efficiency of most HPDs was determined to be approximately 40%. With a better understanding of the laser calibration system, one can further understand and improve the HCAL.
Analysis and generation of groundwater concentration time series
NASA Astrophysics Data System (ADS)
Crăciun, Maria; Vamoş, Călin; Suciu, Nicolae
2018-01-01
Concentration time series are provided by simulated concentrations of a nonreactive solute transported in groundwater, integrated over the transverse direction of a two-dimensional computational domain and recorded at the plume center of mass. The analysis of a statistical ensemble of time series reveals subtle features that are not captured by the first two moments which characterize the approximate Gaussian distribution of the two-dimensional concentration fields. The concentration time series exhibit a complex preasymptotic behavior driven by a nonstationary trend and correlated fluctuations with time-variable amplitude. Time series with almost the same statistics are generated by successively adding to a time-dependent trend a sum of linear regression terms, accounting for correlations between fluctuations around the trend and their increments in time, and terms of an amplitude modulated autoregressive noise of order one with time-varying parameter. The algorithm generalizes mixing models used in probability density function approaches. The well-known interaction by exchange with the mean mixing model is a special case consisting of a linear regression with constant coefficients.
Christensen, Jeppe Schultz; Raaschou-Nielsen, Ole; Tjønneland, Anne; Overvad, Kim; Nordsborg, Rikke B.; Ketzel, Matthias; Sørensen, Thorkild IA; Sørensen, Mette
2015-01-01
Background Traffic noise has been associated with cardiovascular and metabolic disorders. Potential modes of action are through stress and sleep disturbance, which may lead to endocrine dysregulation and overweight. Objectives We aimed to investigate the relationship between residential traffic and railway noise and adiposity. Methods In this cross-sectional study of 57,053 middle-aged people, height, weight, waist circumference, and bioelectrical impedance were measured at enrollment (1993–1997). Body mass index (BMI), body fat mass index (BFMI), and lean body mass index (LBMI) were calculated. Residential exposure to road and railway traffic noise exposure was calculated using the Nordic prediction method. Associations between traffic noise and anthropometric measures at enrollment were analyzed using general linear models and logistic regression adjusted for demographic and lifestyle factors. Results Linear regression models adjusted for age, sex, and socioeconomic factors showed that 5-year mean road traffic noise exposure preceding enrollment was associated with a 0.35-cm wider waist circumference (95% CI: 0.21, 0.50) and a 0.18-point higher BMI (95% CI: 0.12, 0.23) per 10 dB. Small, significant increases were also found for BFMI and LBMI. All associations followed linear exposure–response relationships. Exposure to railway noise was not linearly associated with adiposity measures. However, exposure > 60 dB was associated with a 0.71-cm wider waist circumference (95% CI: 0.23, 1.19) and a 0.19-point higher BMI (95% CI: 0.0072, 0.37) compared with unexposed participants (0–20 dB). Conclusions The present study finds positive associations between residential exposure to road traffic and railway noise and adiposity. Citation Christensen JS, Raaschou-Nielsen O, Tjønneland A, Overvad K, Nordsborg RB, Ketzel M, Sørensen TI, Sørensen M. 2016. Road traffic and railway noise exposures and adiposity in adults: a cross-sectional analysis of the Danish Diet, Cancer, and Health cohort. Environ Health Perspect 124:329–335; http://dx.doi.org/10.1289/ehp.1409052 PMID:26241990
Jet Noise Source Localization Using Linear Phased Array
NASA Technical Reports Server (NTRS)
Agboola, Ferni A.; Bridges, James
2004-01-01
A study was conducted to further clarify the interpretation and application of linear phased array microphone results, for localizing aeroacoustics sources in aircraft exhaust jet. Two model engine nozzles were tested at varying power cycles with the array setup parallel to the jet axis. The array position was varied as well to determine best location for the array. The results showed that it is possible to resolve jet noise sources with bypass and other components separation. The results also showed that a focused near field image provides more realistic noise source localization at low to mid frequencies.
A Refined Model for Radar Homing Intercepts.
1983-10-27
Helge Toutenburq, Prior Information in Linear Models ,(Wiley, NY, 1982). 7. F. A. Graybill , Introduction to Matrices with Applications in StatisticF... linear target trajectory model z i = 0 + 1 r i + wi () where w i i=I,..., N is a sequence of uncorrelated zero-mean A noise, the general formula for...z i (i=l,..., N) at r. and a linear regression model 1 z i = a0 + a1 r i + w i =(Al) where wi is the corruption noise; the problem is to estimate a0
NASA Astrophysics Data System (ADS)
Rubel, Aleksey S.; Lukin, Vladimir V.; Egiazarian, Karen O.
2015-03-01
Results of denoising based on discrete cosine transform for a wide class of images corrupted by additive noise are obtained. Three types of noise are analyzed: additive white Gaussian noise and additive spatially correlated Gaussian noise with middle and high correlation levels. TID2013 image database and some additional images are taken as test images. Conventional DCT filter and BM3D are used as denoising techniques. Denoising efficiency is described by PSNR and PSNR-HVS-M metrics. Within hard-thresholding denoising mechanism, DCT-spectrum coefficient statistics are used to characterize images and, subsequently, denoising efficiency for them. Results of denoising efficiency are fitted for such statistics and efficient approximations are obtained. It is shown that the obtained approximations provide high accuracy of prediction of denoising efficiency.
A Robust Approach For Acoustic Noise Suppression In Speech Using ANFIS
NASA Astrophysics Data System (ADS)
Martinek, Radek; Kelnar, Michal; Vanus, Jan; Bilik, Petr; Zidek, Jan
2015-11-01
The authors of this article deals with the implementation of a combination of techniques of the fuzzy system and artificial intelligence in the application area of non-linear noise and interference suppression. This structure used is called an Adaptive Neuro Fuzzy Inference System (ANFIS). This system finds practical use mainly in audio telephone (mobile) communication in a noisy environment (transport, production halls, sports matches, etc). Experimental methods based on the two-input adaptive noise cancellation concept was clearly outlined. Within the experiments carried out, the authors created, based on the ANFIS structure, a comprehensive system for adaptive suppression of unwanted background interference that occurs in audio communication and degrades the audio signal. The system designed has been tested on real voice signals. This article presents the investigation and comparison amongst three distinct approaches to noise cancellation in speech; they are LMS (least mean squares) and RLS (recursive least squares) adaptive filtering and ANFIS. A careful review of literatures indicated the importance of non-linear adaptive algorithms over linear ones in noise cancellation. It was concluded that the ANFIS approach had the overall best performance as it efficiently cancelled noise even in highly noise-degraded speech. Results were drawn from the successful experimentation, subjective-based tests were used to analyse their comparative performance while objective tests were used to validate them. Implementation of algorithms was experimentally carried out in Matlab to justify the claims and determine their relative performances.
Resonance-Based Time-Frequency Manifold for Feature Extraction of Ship-Radiated Noise.
Yan, Jiaquan; Sun, Haixin; Chen, Hailan; Junejo, Naveed Ur Rehman; Cheng, En
2018-03-22
In this paper, a novel time-frequency signature using resonance-based sparse signal decomposition (RSSD), phase space reconstruction (PSR), time-frequency distribution (TFD) and manifold learning is proposed for feature extraction of ship-radiated noise, which is called resonance-based time-frequency manifold (RTFM). This is suitable for analyzing signals with oscillatory, non-stationary and non-linear characteristics in a situation of serious noise pollution. Unlike the traditional methods which are sensitive to noise and just consider one side of oscillatory, non-stationary and non-linear characteristics, the proposed RTFM can provide the intact feature signature of all these characteristics in the form of a time-frequency signature by the following steps: first, RSSD is employed on the raw signal to extract the high-oscillatory component and abandon the low-oscillatory component. Second, PSR is performed on the high-oscillatory component to map the one-dimensional signal to the high-dimensional phase space. Third, TFD is employed to reveal non-stationary information in the phase space. Finally, manifold learning is applied to the TFDs to fetch the intrinsic non-linear manifold. A proportional addition of the top two RTFMs is adopted to produce the improved RTFM signature. All of the case studies are validated on real audio recordings of ship-radiated noise. Case studies of ship-radiated noise on different datasets and various degrees of noise pollution manifest the effectiveness and robustness of the proposed method.
Resonance-Based Time-Frequency Manifold for Feature Extraction of Ship-Radiated Noise
Yan, Jiaquan; Sun, Haixin; Chen, Hailan; Junejo, Naveed Ur Rehman; Cheng, En
2018-01-01
In this paper, a novel time-frequency signature using resonance-based sparse signal decomposition (RSSD), phase space reconstruction (PSR), time-frequency distribution (TFD) and manifold learning is proposed for feature extraction of ship-radiated noise, which is called resonance-based time-frequency manifold (RTFM). This is suitable for analyzing signals with oscillatory, non-stationary and non-linear characteristics in a situation of serious noise pollution. Unlike the traditional methods which are sensitive to noise and just consider one side of oscillatory, non-stationary and non-linear characteristics, the proposed RTFM can provide the intact feature signature of all these characteristics in the form of a time-frequency signature by the following steps: first, RSSD is employed on the raw signal to extract the high-oscillatory component and abandon the low-oscillatory component. Second, PSR is performed on the high-oscillatory component to map the one-dimensional signal to the high-dimensional phase space. Third, TFD is employed to reveal non-stationary information in the phase space. Finally, manifold learning is applied to the TFDs to fetch the intrinsic non-linear manifold. A proportional addition of the top two RTFMs is adopted to produce the improved RTFM signature. All of the case studies are validated on real audio recordings of ship-radiated noise. Case studies of ship-radiated noise on different datasets and various degrees of noise pollution manifest the effectiveness and robustness of the proposed method. PMID:29565288
Contact stiffness considerations when simulating tyre/road noise
NASA Astrophysics Data System (ADS)
Winroth, Julia; Kropp, Wolfgang; Hoever, Carsten; Höstmad, Patrik
2017-11-01
Tyre/road simulation tools that can capture tyre vibrations, rolling resistance and noise generation are useful for understanding the complex processes that are involved and thereby promoting further development and optimisation. The most detailed tyre/road contact models use a spatial discretisation of the contact and assume an interfacial stiffness to account for the small-scale roughness within the elements. This interfacial stiffness has been found to have a significant impact on the simulated noise emissions but no thorough investigations of this sensitivity have been conducted. Three mechanisms are thought to be involved: The horn effect, the modal composition of the vibrational field of the tyre and the contact forces exciting the tyre vibrations. This study used a numerical tyre/road noise simulation tool based on physical relations to investigate these aspects. The model includes a detailed time-domain contact model with linear or non-linear contact springs that accounts for the effect of local tread deformation on smaller length scales. Results confirm that an increase in contact spring stiffness causes a significant increase of the simulated tyre/road noise. This is primarily caused by a corresponding increase in the contact forces, resulting in larger vibrational amplitudes. The horn effect and the modal composition are relatively unaffected and have minor effects on the radiated noise. A more detailed non-linear contact spring formulation with lower stiffness at small indentations results in a reduced high-frequency content in the contact forces and the simulated noise.
Automatic threshold optimization in nonlinear energy operator based spike detection.
Malik, Muhammad H; Saeed, Maryam; Kamboh, Awais M
2016-08-01
In neural spike sorting systems, the performance of the spike detector has to be maximized because it affects the performance of all subsequent blocks. Non-linear energy operator (NEO), is a popular spike detector due to its detection accuracy and its hardware friendly architecture. However, it involves a thresholding stage, whose value is usually approximated and is thus not optimal. This approximation deteriorates the performance in real-time systems where signal to noise ratio (SNR) estimation is a challenge, especially at lower SNRs. In this paper, we propose an automatic and robust threshold calculation method using an empirical gradient technique. The method is tested on two different datasets. The results show that our optimized threshold improves the detection accuracy in both high SNR and low SNR signals. Boxplots are presented that provide a statistical analysis of improvements in accuracy, for instance, the 75th percentile was at 98.7% and 93.5% for the optimized NEO threshold and traditional NEO threshold, respectively.
NASA Astrophysics Data System (ADS)
Mayvan, Ali D.; Aghaeinia, Hassan; Kazemi, Mohammad
2017-12-01
This paper focuses on robust transceiver design for throughput enhancement on the interference channel (IC), under imperfect channel state information (CSI). In this paper, two algorithms are proposed to improve the throughput of the multi-input multi-output (MIMO) IC. Each transmitter and receiver has, respectively, M and N antennas and IC operates in a time division duplex mode. In the first proposed algorithm, each transceiver adjusts its filter to maximize the expected value of signal-to-interference-plus-noise ratio (SINR). On the other hand, the second algorithm tries to minimize the variances of the SINRs to hedge against the variability due to CSI error. Taylor expansion is exploited to approximate the effect of CSI imperfection on mean and variance. The proposed robust algorithms utilize the reciprocity of wireless networks to optimize the estimated statistical properties in two different working modes. Monte Carlo simulations are employed to investigate sum rate performance of the proposed algorithms and the advantage of incorporating variation minimization into the transceiver design.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dong, X; Petrongolo, M; Wang, T
Purpose: A general problem of dual-energy CT (DECT) is that the decomposition is sensitive to noise in the two sets of dual-energy projection data, resulting in severely degraded qualities of decomposed images. We have previously proposed an iterative denoising method for DECT. Using a linear decomposition function, the method does not gain the full benefits of DECT on beam-hardening correction. In this work, we expand the framework of our iterative method to include non-linear decomposition models for noise suppression in DECT. Methods: We first obtain decomposed projections, which are free of beam-hardening artifacts, using a lookup table pre-measured on amore » calibration phantom. First-pass material images with high noise are reconstructed from the decomposed projections using standard filter-backprojection reconstruction. Noise on the decomposed images is then suppressed by an iterative method, which is formulated in the form of least-square estimation with smoothness regularization. Based on the design principles of a best linear unbiased estimator, we include the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. Analytical formulae are derived to compute the variance-covariance matrix from the measured decomposition lookup table. Results: We have evaluated the proposed method via phantom studies. Using non-linear decomposition, our method effectively suppresses the streaking artifacts of beam-hardening and obtains more uniform images than our previous approach based on a linear model. The proposed method reduces the average noise standard deviation of two basis materials by one order of magnitude without sacrificing the spatial resolution. Conclusion: We propose a general framework of iterative denoising for material decomposition of DECT. Preliminary phantom studies have shown the proposed method improves the image uniformity and reduces noise level without resolution loss. In the future, we will perform more phantom studies to further validate the performance of the purposed method. This work is supported by a Varian MRA grant.« less
NASA Astrophysics Data System (ADS)
Tian, Wugang; Hu, Jiafei; Pan, Mengchun; Chen, Dixiang; Zhao, Jianqiang
2013-03-01
1/f noise is one of the main noise sources of magnetoresistive (MR) sensors, which can cause intrinsic detection limit at low frequency. To suppress this noise, the solution of flux concentration and vertical motion modulation (VMM) has been proposed. Magnetic hysteresis in MR sensors is another problem, which degrades their response linearity and detection ability. To reduce this impact, the method of pulse magnetization and magnetic compensation field with integrated planar coils has been introduced. A flux concentration and VMM based magnetoresistive prototype sensor with integrated planar coils was fabricated using microelectromechanical-system technology. The response linearity of the prototype sensors is improved from 0.8% to 0.12%. The noise level is reduced near to the thermal noise level, and the low-frequency detection ability of the prototype sensor is enhanced with a factor of more than 80.
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.
NASA Astrophysics Data System (ADS)
Zounia, M.; Shamirzaie, M.; Ashouri, A.
2017-09-01
In this paper quantum teleportation of an unknown quantum state via noisy maximally bipartite (Bell) and maximally tripartite (Greenberger-Horne-Zeilinger (GHZ)) entangled states are investigated. We suppose that one of the observers who would receive the sent state accelerates uniformly with respect to the sender. The interactions of the quantum system with its environment during the teleportation process impose noises. These (unital and nonunital) noises are: phase damping, phase flip, amplitude damping and bit flip. In expressing the modes of the Dirac field used as qubits, in the accelerating frame, the so-called single mode approximation is not imposed. We calculate the fidelities of teleportation, and discuss their behaviors using suitable plots. The effects of noise, acceleration and going beyond the single mode approximation are discussed. Although the Bell states bring higher fidelities than GHZ states, the global behaviors of the two quantum systems with respect to some noise types, and therefore their fidelities, are different.
Duan, Si-Bo; Li, Zhao-Liang; Tang, Bo-Hui; Wu, Hua; Ma, Lingling; Zhao, Enyu; Li, Chuanrong
2013-01-01
To evaluate the in-flight performance of a new hyperspectral sensor onboard an unmanned aerial vehicle (UAV-HYPER), a comprehensive field campaign was conducted over the Baotou test site in China on 3 September 2011. Several portable reference reflectance targets were deployed across the test site. The radiometric performance of the UAV-HYPER sensor was assessed in terms of signal-to-noise ratio (SNR) and the calibration accuracy. The SNR of the different bands of the UAV-HYPER sensor was estimated to be between approximately 5 and 120 over the homogeneous targets, and the linear response of the apparent reflectance ranged from approximately 0.05 to 0.45. The uniform and non-uniform Lambertian land surface reflectance was retrieved and validated using in situ measurements, with root mean square error (RMSE) of approximately 0.01–0.07 and relative RMSE of approximately 5%–12%. There were small discrepancies between the retrieved uniform and non-uniform Lambertian land surface reflectance over the homogeneous targets and under low aerosol optical depth (AOD) conditions (AOD = 0.18). However, these discrepancies must be taken into account when adjacent pixels had large land surface reflectance contrast and under high AOD conditions (e.g. AOD = 1.0). PMID:23785513
Clark, Charlotte; Martin, Rocio; van Kempen, Elise; Alfred, Tamuno; Head, Jenny; Davies, Hugh W; Haines, Mary M; Lopez Barrio, Isabel; Matheson, Mark; Stansfeld, Stephen A
2006-01-01
Transport noise is an increasingly prominent feature of the urban environment, making noise pollution an important environmental public health issue. This paper reports on the 2001-2003 RANCH project, the first cross-national epidemiologic study known to examine exposure-effect relations between aircraft and road traffic noise exposure and reading comprehension. Participants were 2,010 children aged 9-10 years from 89 schools around Amsterdam Schiphol, Madrid Barajas, and London Heathrow airports. Data from The Netherlands, Spain, and the United Kingdom were pooled and analyzed using multilevel modeling. Aircraft noise exposure at school was linearly associated with impaired reading comprehension; the association was maintained after adjustment for socioeconomic variables (beta = -0.008, p = 0.012), aircraft noise annoyance, and other cognitive abilities (episodic memory, working memory, and sustained attention). Aircraft noise exposure at home was highly correlated with aircraft noise exposure at school and demonstrated a similar linear association with impaired reading comprehension. Road traffic noise exposure at school was not associated with reading comprehension in either the absence or the presence of aircraft noise (beta = 0.003, p = 0.509; beta = 0.002, p = 0.540, respectively). Findings were consistent across the three countries, which varied with respect to a range of socioeconomic and environmental variables, thus offering robust evidence of a direct exposure-effect relation between aircraft noise and reading comprehension.
Measurements and analysis of aircraft airframe noise
NASA Technical Reports Server (NTRS)
Putnam, T. W.; Lasagna, P. L.; White, K. C.
1975-01-01
Flyover measurements of the airframe noise of AeroCommander, JetStar, CV-990, and B-747 aircraft are presented. Data are shown for both cruise and landing configurations. Correlations between airframe noise and aircraft parameters are developed and presented. The landing approach airframe noise for the test aircraft was approximately 10 EPNdB below present FAA certification requirements.
A mathematical model for simulating noise suppression of lined ejectors
NASA Technical Reports Server (NTRS)
Watson, Willie R.
1994-01-01
A mathematical model containing the essential features embodied in the noise suppression of lined ejectors is presented. Although some simplification of the physics is necessary to render the model mathematically tractable, the current model is the most versatile and technologically advanced at the current time. A system of linearized equations and the boundary conditions governing the sound field are derived starting from the equations of fluid dynamics. A nonreflecting boundary condition is developed. In view of the complex nature of the equations, a parametric study requires the use of numerical techniques and modern computers. A finite element algorithm that solves the differential equations coupled with the boundary condition is then introduced. The numerical method results in a matrix equation with several hundred thousand degrees of freedom that is solved efficiently on a supercomputer. The model is validated by comparing results either with exact solutions or with approximate solutions from other works. In each case, excellent correlations are obtained. The usefulness of the model as an optimization tool and the importance of variable impedance liners as a mechanism for achieving broadband suppression within a lined ejector are demonstrated.
NASA Astrophysics Data System (ADS)
Brousmiche, S.; Souris, K.; Orban de Xivry, J.; Lee, J. A.; Macq, B.; Seco, J.
2017-11-01
Proton range random and systematic uncertainties are the major factors undermining the advantages of proton therapy, namely, a sharp dose falloff and a better dose conformality for lower doses in normal tissues. The influence of CT artifacts such as beam hardening or scatter can easily be understood and estimated due to their large-scale effects on the CT image, like cupping and streaks. In comparison, the effects of weakly-correlated stochastic noise are more insidious and less attention is drawn on them partly due to the common belief that they only contribute to proton range uncertainties and not to systematic errors thanks to some averaging effects. A new source of systematic errors on the range and relative stopping powers (RSP) has been highlighted and proved not to be negligible compared to the 3.5% uncertainty reference value used for safety margin design. Hence, we demonstrate that the angular points in the HU-to-RSP calibration curve are an intrinsic source of proton range systematic error for typical levels of zero-mean stochastic CT noise. Systematic errors on RSP of up to 1% have been computed for these levels. We also show that the range uncertainty does not generally vary linearly with the noise standard deviation. We define a noise-dependent effective calibration curve that better describes, for a given material, the RSP value that is actually used. The statistics of the RSP and the range continuous slowing down approximation (CSDA) have been analytically derived for the general case of a calibration curve obtained by the stoichiometric calibration procedure. These models have been validated against actual CSDA simulations for homogeneous and heterogeneous synthetical objects as well as on actual patient CTs for prostate and head-and-neck treatment planning situations.
Four Theorems on the Psychometric Function
May, Keith A.; Solomon, Joshua A.
2013-01-01
In a 2-alternative forced-choice (2AFC) discrimination task, observers choose which of two stimuli has the higher value. The psychometric function for this task gives the probability of a correct response for a given stimulus difference, . This paper proves four theorems about the psychometric function. Assuming the observer applies a transducer and adds noise, Theorem 1 derives a convenient general expression for the psychometric function. Discrimination data are often fitted with a Weibull function. Theorem 2 proves that the Weibull “slope” parameter, , can be approximated by , where is the of the Weibull function that fits best to the cumulative noise distribution, and depends on the transducer. We derive general expressions for and , from which we derive expressions for specific cases. One case that follows naturally from our general analysis is Pelli's finding that, when , . We also consider two limiting cases. Theorem 3 proves that, as sensitivity improves, 2AFC performance will usually approach that for a linear transducer, whatever the actual transducer; we show that this does not apply at signal levels where the transducer gradient is zero, which explains why it does not apply to contrast detection. Theorem 4 proves that, when the exponent of a power-function transducer approaches zero, 2AFC performance approaches that of a logarithmic transducer. We show that the power-function exponents of 0.4–0.5 fitted to suprathreshold contrast discrimination data are close enough to zero for the fitted psychometric function to be practically indistinguishable from that of a log transducer. Finally, Weibull reflects the shape of the noise distribution, and we used our results to assess the recent claim that internal noise has higher kurtosis than a Gaussian. Our analysis of for contrast discrimination suggests that, if internal noise is stimulus-independent, it has lower kurtosis than a Gaussian. PMID:24124456
Selecting algorithms, sensors, and linear bases for optimum spectral recovery of skylight.
López-Alvarez, Miguel A; Hernández-Andrés, Javier; Valero, Eva M; Romero, Javier
2007-04-01
In a previous work [Appl. Opt.44, 5688 (2005)] we found the optimum sensors for a planned multispectral system for measuring skylight in the presence of noise by adapting a linear spectral recovery algorithm proposed by Maloney and Wandell [J. Opt. Soc. Am. A3, 29 (1986)]. Here we continue along these lines by simulating the responses of three to five Gaussian sensors and recovering spectral information from noise-affected sensor data by trying out four different estimation algorithms, three different sizes for the training set of spectra, and various linear bases. We attempt to find the optimum combination of sensors, recovery method, linear basis, and matrix size to recover the best skylight spectral power distributions from colorimetric and spectral (in the visible range) points of view. We show how all these parameters play an important role in the practical design of a real multispectral system and how to obtain several relevant conclusions from simulating the behavior of sensors in the presence of noise.
Phase contrast STEM for thin samples: Integrated differential phase contrast.
Lazić, Ivan; Bosch, Eric G T; Lazar, Sorin
2016-01-01
It has been known since the 1970s that the movement of the center of mass (COM) of a convergent beam electron diffraction (CBED) pattern is linearly related to the (projected) electrical field in the sample. We re-derive a contrast transfer function (CTF) for a scanning transmission electron microscopy (STEM) imaging technique based on this movement from the point of view of image formation and continue by performing a two-dimensional integration on the two images based on the two components of the COM movement. The resulting integrated COM (iCOM) STEM technique yields a scalar image that is linear in the phase shift caused by the sample and therefore also in the local (projected) electrostatic potential field of a thin sample. We confirm that the differential phase contrast (DPC) STEM technique using a segmented detector with 4 quadrants (4Q) yields a good approximation for the COM movement. Performing a two-dimensional integration, just as for the COM, we obtain an integrated DPC (iDPC) image which is approximately linear in the phase of the sample. Beside deriving the CTFs of iCOM and iDPC, we clearly point out the objects of the two corresponding imaging techniques, and highlight the differences to objects corresponding to COM-, DPC-, and (HA) ADF-STEM. The theory is validated with simulations and we present first experimental results of the iDPC-STEM technique showing its capability for imaging both light and heavy elements with atomic resolution and a good signal to noise ratio (SNR). Copyright © 2015 Elsevier B.V. All rights reserved.
An instrument to measure mechanical up-conversion phenomena in metals in the elastic regime
NASA Astrophysics Data System (ADS)
Vajente, G.; Quintero, E. A.; Ni, X.; Arai, K.; Gustafson, E. K.; Robertson, N. A.; Sanchez, E. J.; Greer, J. R.; Adhikari, R. X.
2016-06-01
Crystalline materials, such as metals, are known to exhibit deviation from a simple linear relation between strain and stress when the latter exceeds the yield stress. In addition, it has been shown that metals respond to varying external stress in a discontinuous way in this regime, exhibiting discrete releases of energy. This crackling noise has been extensively studied both experimentally and theoretically when the metals are operating in the plastic regime. In our study, we focus on the behavior of metals in the elastic regime, where the stresses are well below the yield stress. We describe an instrument that aims to characterize non-linear mechanical noise in metals when stressed in the elastic regime. In macroscopic systems, this phenomenon is expected to manifest as a non-stationary noise modulated by external disturbances applied to the material, a form of mechanical up-conversion of noise. The main motivation for this work is for the case of maraging steel components (cantilevers and wires) in the suspension systems of terrestrial gravitational wave detectors. Such instruments are planned to reach very ambitious displacement sensitivities, and therefore mechanical noise in the cantilevers could prove to be a limiting factor for the detectors' final sensitivities, mainly due to non-linear up-conversion of low frequency residual seismic motion to the frequencies of interest for the gravitational wave observations. We describe here the experimental setup, with a target sensitivity of 10-15 m/ √{ Hz } in the frequency range of 10-1000 Hz, a simple phenomenological model of the non-linear mechanical noise, and the analysis method that is inspired by this model.
Xie, Weilin; Xia, Zongyang; Zhou, Qian; Shi, Hongxiao; Dong, Yi; Hu, Weisheng
2015-07-13
We present a photonic approach for generating low phase noise, arbitrary chirped microwave waveforms based on heterodyne beating between high order correlated comb lines extracted from frequency-agile optical frequency comb. Using the dual heterodyne phase transfer scheme, extrinsic phase noises induced by the separate optical paths are efficiently suppressed by 42-dB at 1-Hz offset frequency. Linearly chirped microwave waveforms are achieved within 30-ms temporal duration, contributing to a large time-bandwidth product. The linearity measurement leads to less than 90 kHz RMS frequency error during the entire chirp duration, exhibiting excellent linearity for the microwave and sub-THz waveforms. The capability of generating arbitrary waveforms up to sub-THz band with flexible temporal duration, long repetition period, broad bandwidth, and large time-bandwidth product is investigated and discussed.
NASA Astrophysics Data System (ADS)
Yang, Huizhen; Ma, Liang; Wang, Bin
2018-01-01
In contrast to the conventional adaptive optics (AO) system, the wavefront sensorless (WFSless) AO system doesn't need a WFS to measure the wavefront aberrations. It is simpler than the conventional AO in system architecture and can be applied to the complex conditions. The model-based WFSless system has a great potential in real-time correction applications because of its fast convergence. The control algorithm of the model-based WFSless system is based on an important theory result that is the linear relation between the Mean-Square Gradient (MSG) magnitude of the wavefront aberration and the second moment of the masked intensity distribution in the focal plane (also called as Masked Detector Signal-MDS). The linear dependence between MSG and MDS for the point source imaging with a CCD sensor will be discussed from theory and simulation in this paper. The theory relationship between MSG and MDS is given based on our previous work. To verify the linear relation for the point source, we set up an imaging model under atmospheric turbulence. Additionally, the value of MDS will be deviate from that of theory because of the noise of detector and further the deviation will affect the correction effect. The theory results under noise will be obtained through theoretical derivation and then the linear relation between MDS and MDS under noise will be discussed through the imaging model. Results show the linear relation between MDS and MDS under noise is also maintained well, which provides a theoretical support to applications of the model-based WFSless system.
Laser Linewidth Requirements for Optical Bpsk and Qpsk Heterodyne Lightwave Systems.
NASA Astrophysics Data System (ADS)
Boukli-Hacene, Mokhtar
In this dissertation, optical Binary Phase-Shift Keying (BPSK) and Quadrature Phase-Shift Keying (QPSK) heterodyne communication receivers are investigated. The main objective of this research work is to analyze the performance of these receivers in the presence of laser phase noise and shot noise. The heterodyne optical BPSK is based on the square law carrier recovery (SLCR) scheme for phase detection. The BPSK heterodyne receiver is analyzed assuming a second order linear phase-locked loop (PLL) subsystem and a small phase error. The noise properties are analyzed and the problem of minimizing the effect of noise is addressed. The performance of the receiver is evaluated in terms of the bit error rate (BER), which leads to the analysis of the BER versus the laser linewidth and the number of photons/bit to achieve good performance. Since we cannot track the pure carrier component in the presence of noise, a non-linear model is used to solve the problem of recovery of the carrier. The non -linear system is analyzed in the presence of a low signal -to-noise ratio (SNR). The non-Gaussian noise model represented by its probability density function (PDF) is used to analyze the performance of the receiver, especially the phase error. In addition the effect of the PLL is analyzed by studying the cycle slippage (cs). Finally, the research effort is expanded from BPSK to QPSK systems. The heterodyne optical QPSK based on the fourth power multiplier scheme (FPMS) in conjunction with linear and non-linear PLL model is investigated. Optimum loop and higher power penalty in the presence of phase noise and shot noise are analyzed. It is shown that the QPSK system yields a high speed and high sensitivity coherent means for transmission of information accompanied by a small degradation in the laser linewidth. Comparative analysis of BPSK and QPSK systems leads us to conclude that in terms of laser linewidth, bit rate, phase error and power penalty, the QPSK system is more sensitive than the BPSK system and suffers less from higher power penalty. The BPSK and QPSK heterodyne receivers used in the uncoded scheme demand a realistic laser linewidth. Since the laser linewidth is the critical measure of the performance of a receiver, a convolutional code applied to QPSK of the system is used to improve the sensitivity of the system. The effect of coding is particularly important as means of relaxing the laser linewidth requirement. The validity and usefulness of the analysis presented in the dissertation is supported by computer simulations.
NASA Astrophysics Data System (ADS)
Stansfeld, Stephen A.; Clark, Charlotte
2005-04-01
Studies in West London have found associations between aircraft noise exposure and childrens' cognitive performance. This has culminated in the RANCH Study examining exposure-effect associations between aircraft and road traffic noise exposure and cognitive performance and health. The RANCH project, the largest cross-sectional study of noise and childrens health, examined 2844 children, 9-10 years old, from 89 schools around three major airports: in the Netherlands, Spain and the United Kingdom. Children were selected by external aircraft and road traffic noise exposure at school predicted from noise contour maps, modeling and on-site measurements. A substudy indicated high internal levels of noise within classrooms. Schools were matched for socioeconomic position within countries. Cognitive and health outcomes were measured by standardized tests and questionnaires administered in the classroom. A parental questionnaire collected information on socioeconomic position, parental education and ethnicity. Linear exposure-effect associations were found between chronic aircraft noise exposure and impairment of reading comprehension and recognition memory, maintained after adjustment for mothers education, socioeconomic factors, longstanding illness and classroom insulation. Road traffic noise exposure was linearly associated with episodic memory. The implications of these results for childrens' learning environments will be discussed. [Work supported by European Community (QLRT-2000-00197) Vth framework program.
Inverse solutions for electrical impedance tomography based on conjugate gradients methods
NASA Astrophysics Data System (ADS)
Wang, M.
2002-01-01
A multistep inverse solution for two-dimensional electric field distribution is developed to deal with the nonlinear inverse problem of electric field distribution in relation to its boundary condition and the problem of divergence due to errors introduced by the ill-conditioned sensitivity matrix and the noise produced by electrode modelling and instruments. This solution is based on a normalized linear approximation method where the change in mutual impedance is derived from the sensitivity theorem and a method of error vector decomposition. This paper presents an algebraic solution of the linear equations at each inverse step, using a generalized conjugate gradients method. Limiting the number of iterations in the generalized conjugate gradients method controls the artificial errors introduced by the assumption of linearity and the ill-conditioned sensitivity matrix. The solution of the nonlinear problem is approached using a multistep inversion. This paper also reviews the mathematical and physical definitions of the sensitivity back-projection algorithm based on the sensitivity theorem. Simulations and discussion based on the multistep algorithm, the sensitivity coefficient back-projection method and the Newton-Raphson method are given. Examples of imaging gas-liquid mixing and a human hand in brine are presented.
Determination of seasonals using wavelets in terms of noise parameters changeability
NASA Astrophysics Data System (ADS)
Klos, Anna; Bogusz, Janusz; Figurski, Mariusz
2015-04-01
The reliable velocities of GNSS-derived observations are becoming of high importance nowadays. The fact on how we determine and subtract the seasonals may all cause the time series autocorrelation and affect uncertainties of linear parameters. The periodic changes in GNSS time series are commonly assumed as the sum of annual and semi-annual changes with amplitudes and phases being constant in time and the Least-Squares Estimation (LSE) is used in general to model these sine waves. However, not only seasonals' time-changeability, but also their higher harmonics should be considered. In this research, we focused on more than 230 globally distributed IGS stations that were processed at the Military University of Technology EPN Local Analysis Centre (MUT LAC) in Bernese 5.0 software. The network was divided into 7 different sub-networks with few of overlapping stations and processed separately with newest models. Here, we propose a wavelet-based trend and seasonals determination and removal of whole frequency spectrum between Chandler and quarter-annual periods from North, East and Up components and compare it with LSE-determined values. We used a Meyer symmetric, orthogonal wavelet and assumed nine levels of decomposition. The details from 6 up to 9 were analyzed here as periodic components with frequencies between 0.3-2.5 cpy. The characteristic oscillations for each of frequency band were pointed out. The details lower than 6 summed together with detrended approximation were considered as residua. The power spectral densities (PSDs) of original and decomposed data were stacked for North, East and Up components for each of sub-networks so as to show what power was removed with each of decomposition levels. Moreover, the noises that the certain frequency band follows (in terms of spectral indices of power-law dependencies) were estimated here using a spectral method and compared for all processed sub-networks. It seems, that lowest frequencies up to 0.7 cpy are characterized by lower spectral indices in comparison to higher ones being close to white noise. Basing on the fact, that decomposition levels overlap each other, the frequency-window choice becomes a main point in spectral index estimation. Our results were compared with those obtained by Maximum Likelihood Estimation (MLE) and possible differences as well as their impact on velocity uncertainties pointed out. The results show that the spectral indices estimated in time and frequency domains differ of 0.15 in maximum. Moreover, we compared the removed power basing on wavelet decomposition levels with the one subtracted with LSE, assuming the same periodicities. In comparison to LSE, the wavelet-based approach leaves the residua being closer to white noise with lower power-law amplitudes of them, what strictly reduces velocity uncertainties. The last approximation was analyzed here as long-term trend, being the non-linear and compared with LSE-determined linear one. It seems that these two trends differ at the level of 0.3 mm/yr in the most extreme case, what makes wavelet decomposition being useful for velocity determination.
Chen, Bor-Sen; Hsu, Chih-Yuan
2012-10-26
Collective rhythms of gene regulatory networks have been a subject of considerable interest for biologists and theoreticians, in particular the synchronization of dynamic cells mediated by intercellular communication. Synchronization of a population of synthetic genetic oscillators is an important design in practical applications, because such a population distributed over different host cells needs to exploit molecular phenomena simultaneously in order to emerge a biological phenomenon. However, this synchronization may be corrupted by intrinsic kinetic parameter fluctuations and extrinsic environmental molecular noise. Therefore, robust synchronization is an important design topic in nonlinear stochastic coupled synthetic genetic oscillators with intrinsic kinetic parameter fluctuations and extrinsic molecular noise. Initially, the condition for robust synchronization of synthetic genetic oscillators was derived based on Hamilton Jacobi inequality (HJI). We found that if the synchronization robustness can confer enough intrinsic robustness to tolerate intrinsic parameter fluctuation and extrinsic robustness to filter the environmental noise, then robust synchronization of coupled synthetic genetic oscillators is guaranteed. If the synchronization robustness of a population of nonlinear stochastic coupled synthetic genetic oscillators distributed over different host cells could not be maintained, then robust synchronization could be enhanced by external control input through quorum sensing molecules. In order to simplify the analysis and design of robust synchronization of nonlinear stochastic synthetic genetic oscillators, the fuzzy interpolation method was employed to interpolate several local linear stochastic coupled systems to approximate the nonlinear stochastic coupled system so that the HJI-based synchronization design problem could be replaced by a simple linear matrix inequality (LMI)-based design problem, which could be solved with the help of LMI toolbox in MATLAB easily. If the synchronization robustness criterion, i.e. the synchronization robustness ≥ intrinsic robustness + extrinsic robustness, then the stochastic coupled synthetic oscillators can be robustly synchronized in spite of intrinsic parameter fluctuation and extrinsic noise. If the synchronization robustness criterion is violated, external control scheme by adding inducer can be designed to improve synchronization robustness of coupled synthetic genetic oscillators. The investigated robust synchronization criteria and proposed external control method are useful for a population of coupled synthetic networks with emergent synchronization behavior, especially for multi-cellular, engineered networks.
2012-01-01
Background Collective rhythms of gene regulatory networks have been a subject of considerable interest for biologists and theoreticians, in particular the synchronization of dynamic cells mediated by intercellular communication. Synchronization of a population of synthetic genetic oscillators is an important design in practical applications, because such a population distributed over different host cells needs to exploit molecular phenomena simultaneously in order to emerge a biological phenomenon. However, this synchronization may be corrupted by intrinsic kinetic parameter fluctuations and extrinsic environmental molecular noise. Therefore, robust synchronization is an important design topic in nonlinear stochastic coupled synthetic genetic oscillators with intrinsic kinetic parameter fluctuations and extrinsic molecular noise. Results Initially, the condition for robust synchronization of synthetic genetic oscillators was derived based on Hamilton Jacobi inequality (HJI). We found that if the synchronization robustness can confer enough intrinsic robustness to tolerate intrinsic parameter fluctuation and extrinsic robustness to filter the environmental noise, then robust synchronization of coupled synthetic genetic oscillators is guaranteed. If the synchronization robustness of a population of nonlinear stochastic coupled synthetic genetic oscillators distributed over different host cells could not be maintained, then robust synchronization could be enhanced by external control input through quorum sensing molecules. In order to simplify the analysis and design of robust synchronization of nonlinear stochastic synthetic genetic oscillators, the fuzzy interpolation method was employed to interpolate several local linear stochastic coupled systems to approximate the nonlinear stochastic coupled system so that the HJI-based synchronization design problem could be replaced by a simple linear matrix inequality (LMI)-based design problem, which could be solved with the help of LMI toolbox in MATLAB easily. Conclusion If the synchronization robustness criterion, i.e. the synchronization robustness ≥ intrinsic robustness + extrinsic robustness, then the stochastic coupled synthetic oscillators can be robustly synchronized in spite of intrinsic parameter fluctuation and extrinsic noise. If the synchronization robustness criterion is violated, external control scheme by adding inducer can be designed to improve synchronization robustness of coupled synthetic genetic oscillators. The investigated robust synchronization criteria and proposed external control method are useful for a population of coupled synthetic networks with emergent synchronization behavior, especially for multi-cellular, engineered networks. PMID:23101662
On the Use of Linearized Euler Equations in the Prediction of Jet Noise
NASA Technical Reports Server (NTRS)
Mankbadi, Reda R.; Hixon, R.; Shih, S.-H.; Povinelli, L. A.
1995-01-01
Linearized Euler equations are used to simulate supersonic jet noise generation and propagation. Special attention is given to boundary treatment. The resulting solution is stable and nearly free from boundary reflections without the need for artificial dissipation, filtering, or a sponge layer. The computed solution is in good agreement with theory and observation and is much less CPU-intensive as compared to large-eddy simulations.
Flyover noise characteristics of a tilt-wing V/STOL aircraft (XC-142A)
NASA Technical Reports Server (NTRS)
Pegg, R. J.; Henderson, H. R.; Hilton, D. A.
1974-01-01
A field noise measurement investigation was conducted during the flight testing of an XC-142A tilt-wing V/STOL aircraft to define its external noise characteristics. Measured time histories of overall sound pressure level show that noise levels are higher at lower airspeeds and decrease with increased speed up to approximately 160 knots. The primary noise sources were the four high-speed, main propellers. Flyover-noise time histories calculated by existing techniques for propeller noise prediction are in reasonable agreement with the experimental data.
Preliminary status of POLICAN: A near-infrared imaging polarimeter
NASA Astrophysics Data System (ADS)
Devaraj, R.; Luna, A.; Carrasco, L.; Mayya, Y. D.
2015-10-01
POLICAN is a near-infrared (J, H, K) imaging polarimeter developed for the Cananea near infrared camera (CANICA) at the 2.1m telescope of the Guillermo Haro Astrophysical Observatory (OAGH) located at Cananea, Sonora, México. The camera has a 1024 x 1024 HgCdTe detector (HAWAII array) with a plate scale of 0.32 arcsec/pixel providing a field of view of 5.5 x 5.5 arcmin. POLICAN is mounted externally to CANICA for narrow-field (f/12) linear polarimetric observations. It consists of a rotating super achromatic (1-2.7μm) half waveplate and a fixed wire-grid polarizer as the analyzer. The light is modulated by setting the half waveplate at different angles (0°, 22.5°, 45°, 67.5°) and linear combinations of the Stokes parameters (I, Q and U) are obtained. Image reduction and removal of instrumental polarization consist of dark noise subtraction, polarimetric flat fielding and background sky subtraction. Polarimetric calibration is performed by observing polarization standards available in the literature. The astrometry correction is performed by matching common stars with the Two Micron All Sky Survey. POLICAN's bright and limiting magnitudes are approximately 6th and 16th magnitude, which correspond to saturation and photon noise, respectively. POLICAN currently achieves a polarimetric accuracy about 3.0% and polarization angle uncertainties within 3°. Preliminary observations of star forming regions are being carried out in order to study their magnetic field properties.
Image Restoration in Cryo-electron Microscopy
Penczek, Pawel A.
2011-01-01
Image restoration techniques are used to obtain, given experimental measurements, the best possible approximation of the original object within the limits imposed by instrumental conditions and noise level in the data. In molecular electron microscopy, we are mainly interested in linear methods that preserve the respective relationships between mass densities within the restored map. Here, we describe the methodology of image restoration in structural electron microscopy, and more specifically, we will focus on the problem of the optimum recovery of Fourier amplitudes given electron microscope data collected under various defocus settings. We discuss in detail two classes of commonly used linear methods, the first of which consists of methods based on pseudoinverse restoration, and which is further subdivided into mean-square error, chi-square error, and constrained based restorations, where the methods in the latter two subclasses explicitly incorporates non-white distribution of noise in the data. The second class of methods is based on the Wiener filtration approach. We show that the Wiener filter-based methodology can be used to obtain a solution to the problem of amplitude correction (or “sharpening”) of the electron microscopy map that makes it visually comparable to maps determined by X-ray crystallography, and thus amenable to comparable interpretation. Finally, we present a semi-heuristic Wiener filter-based solution to the problem of image restoration given sets of heterogeneous solutions. We conclude the chapter with a discussion of image restoration protocols implemented in commonly used single particle software packages. PMID:20888957
Attitude Estimation for Large Field-of-View Sensors
NASA Technical Reports Server (NTRS)
Cheng, Yang; Crassidis, John L.; Markley, F. Landis
2005-01-01
The QUEST measurement noise model for unit vector observations has been widely used in spacecraft attitude estimation for more than twenty years. It was derived under the approximation that the noise lies in the tangent plane of the respective unit vector and is axially symmetrically distributed about the vector. For large field-of-view sensors, however, this approximation may be poor, especially when the measurement falls near the edge of the field of view. In this paper a new measurement noise model is derived based on a realistic noise distribution in the focal-plane of a large field-of-view sensor, which shows significant differences from the QUEST model for unit vector observations far away from the sensor boresight. An extended Kalman filter for attitude estimation is then designed with the new measurement noise model. Simulation results show that with the new measurement model the extended Kalman filter achieves better estimation performance using large field-of-view sensor observations.
The most likely voltage path and large deviations approximations for integrate-and-fire neurons.
Paninski, Liam
2006-08-01
We develop theory and numerical methods for computing the most likely subthreshold voltage path of a noisy integrate-and-fire (IF) neuron, given observations of the neuron's superthreshold spiking activity. This optimal voltage path satisfies a second-order ordinary differential (Euler-Lagrange) equation which may be solved analytically in a number of special cases, and which may be solved numerically in general via a simple "shooting" algorithm. Our results are applicable for both linear and nonlinear subthreshold dynamics, and in certain cases may be extended to correlated subthreshold noise sources. We also show how this optimal voltage may be used to obtain approximations to (1) the likelihood that an IF cell with a given set of parameters was responsible for the observed spike train; and (2) the instantaneous firing rate and interspike interval distribution of a given noisy IF cell. The latter probability approximations are based on the classical Freidlin-Wentzell theory of large deviations principles for stochastic differential equations. We close by comparing this most likely voltage path to the true observed subthreshold voltage trace in a case when intracellular voltage recordings are available in vitro.
Prevention and Treatment of Noise-Induced Tinnitus
2014-09-01
Tinnitus PRINCIPAL INVESTIGATOR: Dr. Richard A. Altschuler CONTRACTING ORGANIZATION: University of Michigan REPORT DATE: 2014...3 Ju 2014 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Prevention and Treatment of Noise-Induced Tinnitus 5b. GRANT NUMBER 5c. PROGRAM...prevent or treat noise induced tinnitus . Our studies showed a military relevant small arms fire-like noise will induce tinnitus in approximately 33
Development of Computational Aeroacoustics Code for Jet Noise and Flow Prediction
NASA Astrophysics Data System (ADS)
Keith, Theo G., Jr.; Hixon, Duane R.
2002-07-01
Accurate prediction of jet fan and exhaust plume flow and noise generation and propagation is very important in developing advanced aircraft engines that will pass current and future noise regulations. In jet fan flows as well as exhaust plumes, two major sources of noise are present: large-scale, coherent instabilities and small-scale turbulent eddies. In previous work for the NASA Glenn Research Center, three strategies have been explored in an effort to computationally predict the noise radiation from supersonic jet exhaust plumes. In order from the least expensive computationally to the most expensive computationally, these are: 1) Linearized Euler equations (LEE). 2) Very Large Eddy Simulations (VLES). 3) Large Eddy Simulations (LES). The first method solves the linearized Euler equations (LEE). These equations are obtained by linearizing about a given mean flow and the neglecting viscous effects. In this way, the noise from large-scale instabilities can be found for a given mean flow. The linearized Euler equations are computationally inexpensive, and have produced good noise results for supersonic jets where the large-scale instability noise dominates, as well as for the tone noise from a jet engine blade row. However, these linear equations do not predict the absolute magnitude of the noise; instead, only the relative magnitude is predicted. Also, the predicted disturbances do not modify the mean flow, removing a physical mechanism by which the amplitude of the disturbance may be controlled. Recent research for isolated airfoils' indicates that this may not affect the solution greatly at low frequencies. The second method addresses some of the concerns raised by the LEE method. In this approach, called Very Large Eddy Simulation (VLES), the unsteady Reynolds averaged Navier-Stokes equations are solved directly using a high-accuracy computational aeroacoustics numerical scheme. With the addition of a two-equation turbulence model and the use of a relatively coarse grid, the numerical solution is effectively filtered into a directly calculated mean flow with the small-scale turbulence being modeled, and an unsteady large-scale component that is also being directly calculated. In this way, the unsteady disturbances are calculated in a nonlinear way, with a direct effect on the mean flow. This method is not as fast as the LEE approach, but does have many advantages to recommend it; however, like the LEE approach, only the effect of the largest unsteady structures will be captured. An initial calculation was performed on a supersonic jet exhaust plume, with promising results, but the calculation was hampered by the explicit time marching scheme that was employed. This explicit scheme required a very small time step to resolve the nozzle boundary layer, which caused a long run time. Current work is focused on testing a lower-order implicit time marching method to combat this problem.
A Model for Jet-Surface Interaction Noise Using Physically Realizable Upstream Turbulence Conditions
NASA Technical Reports Server (NTRS)
Afsar, Mohammed Z.; Leib, Stewart J.; Bozak, Richard F.
2015-01-01
This paper is a continuation of previous work in which a generalized Rapid Distortion Theory (RDT) formulation was used to model low-frequency trailing-edge noise. The research was motivated by proposed next-generation aircraft configurations where the exhaust system is tightly integrated with the airframe. Data from recent experiments at NASA on the interaction between high-Reynolds-number subsonic jet flows and an external flat plate showed that the power spectral density (PSD) of the far-field pressure underwent considerable amplification at low frequencies. For example, at the 900 observation angle, the low-frequency noise could be as much as 10dB greater than the jet noise itself. In this paper, we present predictions of the noise generated by the interaction of a rectangular jet with the trailing edge of a semi-infinite flat plate. The calculations are based on a formula for the acoustic spectrum of this noise source derived from an exact formal solution of the linearized Euler equations involving (in this case) one arbitrary convected scalar quantity and a Rayleigh equation Green's function. A low-frequency asymptotic approximation for the Green's function based on a two-dimensional mean flow is used in the calculations along with a physically realizable upstream turbulence spectrum, which includes a finite de-correlation region. Numerical predictions, based on three-dimensional RANS solutions for a range of subsonic acoustic Mach number jets and nozzle aspect ratios are compared with experimental data. Comparisons of the RANS results with flow data are also presented for selected cases. We find that a finite decorrelation region increases the low-frequency algebraic decay (the low frequency "rolloff") of the acoustic spectrum with angular frequency thereby producing much closer agreement with noise data for Strouhal numbers less than 0.1. Secondly, the large-aspectratio theory is able to predict the low-frequency amplification due to the jet-edge interaction reasonably well, even for moderate aspect ratio nozzles. We show also that the noise predictions for smaller aspect ratio jets can be fine-tuned using the appropriate RANS-based mean flow and turbulence properties.
Noise Assessment of the Bay Area Rapid Transit System
DOT National Transportation Integrated Search
1978-10-01
The report describes the noise on and near the San Francisco Bay Area Rapid Transit System (BART). BART has approximately 75 miles of two-way revenue track (of which 19.7 miles are in subway) and 34 stations. Noise data is given for specific measurem...
GPS coordinate time series measurements in Ontario and Quebec, Canada
NASA Astrophysics Data System (ADS)
Samadi Alinia, Hadis; Tiampo, Kristy F.; James, Thomas S.
2017-06-01
New precise network solutions for continuous GPS (cGPS) stations distributed in eastern Ontario and western Québec provide constraints on the regional three-dimensional crustal velocity field. Five years of continuous observations at fourteen cGPS sites were analyzed using Bernese GPS processing software. Several different sub-networks were chosen from these stations, and the data were processed and compared to in order to select the optimal configuration to accurately estimate the vertical and horizontal station velocities and minimize the associated errors. The coordinate time series were then compared to the crustal motions from global solutions and the optimized solution is presented here. A noise analysis model with power-law and white noise, which best describes the noise characteristics of all three components, was employed for the GPS time series analysis. The linear trend, associated uncertainties, and the spectral index of the power-law noise were calculated using a maximum likelihood estimation approach. The residual horizontal velocities, after removal of rigid plate motion, have a magnitude consistent with expected glacial isostatic adjustment (GIA). The vertical velocities increase from subsidence of almost 1.9 mm/year south of the Great Lakes to uplift near Hudson Bay, where the highest rate is approximately 10.9 mm/year. The residual horizontal velocities range from approximately 0.5 mm/year, oriented south-southeastward, at the Great Lakes to nearly 1.5 mm/year directed toward the interior of Hudson Bay at stations adjacent to its shoreline. Here, the velocity uncertainties are estimated at less than 0.6 mm/year for the horizontal component and 1.1 mm/year for the vertical component. A comparison between the observed velocities and GIA model predictions, for a limited range of Earth models, shows a better fit to the observations for the Earth model with the smallest upper mantle viscosity and the largest lower mantle viscosity. However, the pattern of horizontal deformation is not well explained in the north, along Hudson Bay, suggesting that revisions to the ice thickness history are needed to improve the fit to observations.
High dynamic range pixel architecture for advanced diagnostic medical x-ray imaging applications
DOE Office of Scientific and Technical Information (OSTI.GOV)
Izadi, Mohammad Hadi; Karim, Karim S.
2006-05-15
The most widely used architecture in large-area amorphous silicon (a-Si) flat panel imagers is a passive pixel sensor (PPS), which consists of a detector and a readout switch. While the PPS has the advantage of being compact and amenable toward high-resolution imaging, small PPS output signals are swamped by external column charge amplifier and data line thermal noise, which reduce the minimum readable sensor input signal. In contrast to PPS circuits, on-pixel amplifiers in a-Si technology reduce readout noise to levels that can meet even the stringent requirements for low noise digital x-ray fluoroscopy (<1000 noise electrons). However, larger voltagesmore » at the pixel input cause the output of the amplified pixel to become nonlinear thus reducing the dynamic range. We reported a hybrid amplified pixel architecture based on a combination of PPS and amplified pixel designs that, in addition to low noise performance, also resulted in large-signal linearity and consequently higher dynamic range [K. S. Karim et al., Proc. SPIE 5368, 657 (2004)]. The additional benefit in large-signal linearity, however, came at the cost of an additional pixel transistor. We present an amplified pixel design that achieves the goals of low noise performance and large-signal linearity without the need for an additional pixel transistor. Theoretical calculations and simulation results for noise indicate the applicability of the amplified a-Si pixel architecture for high dynamic range, medical x-ray imaging applications that require switching between low exposure, real-time fluoroscopy and high-exposure radiography.« less
Parameter estimation using weighted total least squares in the two-compartment exchange model.
Garpebring, Anders; Löfstedt, Tommy
2018-01-01
The linear least squares (LLS) estimator provides a fast approach to parameter estimation in the linearized two-compartment exchange model. However, the LLS method may introduce a bias through correlated noise in the system matrix of the model. The purpose of this work is to present a new estimator for the linearized two-compartment exchange model that takes this noise into account. To account for the noise in the system matrix, we developed an estimator based on the weighted total least squares (WTLS) method. Using simulations, the proposed WTLS estimator was compared, in terms of accuracy and precision, to an LLS estimator and a nonlinear least squares (NLLS) estimator. The WTLS method improved the accuracy compared to the LLS method to levels comparable to the NLLS method. This improvement was at the expense of increased computational time; however, the WTLS was still faster than the NLLS method. At high signal-to-noise ratio all methods provided similar precisions while inconclusive results were observed at low signal-to-noise ratio. The proposed method provides improvements in accuracy compared to the LLS method, however, at an increased computational cost. Magn Reson Med 79:561-567, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.
King, E A; Murphy, E; Rice, H J
2011-03-01
The first phase of noise mapping and action planning in Ireland, in accordance with EU Directive 2002/49/EC, is now complete. In total this included one agglomeration, one airport and approximately 600 km of major roads outside the agglomeration. These noise maps describe the level of noise exposure of approximately 1.25 million people. The first phase of noise mapping was dealt with by five noise mapping bodies while 26 action planning authorities were involved in the development of the associated action plans. The second phase of noise mapping, due to be completed in 2012, sees a reduction in the defined thresholds describing the required agglomerations, roads and railways that have to be mapped. This will have a significant impact on the extent of mapping required. In Ireland this will result in an increased number of local authorities being required to develop strategic noise maps for their area along with the further development of associated action plans. It is appropriate at this point to review the work process and results from the first phase of noise mapping in Ireland in order to establish areas that could be improved, throughout the noise mapping project. In this paper a review of the implementation procedures focussing on (dominant) road traffic noise is presented. It is identified that more standardisation is needed and this could be achieved by the establishment of a national expert steering group. Copyright © 2010 Elsevier Ltd. All rights reserved.
Transition to turbulence and noise radiation in heated coaxial jet flows
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gloor, Michael, E-mail: gloor@ifd.mavt.ethz.ch; Bühler, Stefan; Kleiser, Leonhard
2016-04-15
Laminar-turbulent transition and noise radiation of a parametrized set of subsonic coaxial jet flows with a hot primary (core) stream are investigated numerically by Large-Eddy Simulation (LES) and direct noise computation. This study extends our previous research on local linear stability of heated coaxial jet flows by analyzing the nonlinear evolution of initially laminar flows disturbed by a superposition of small-amplitude unstable eigenmodes. First, a baseline configuration is studied to shed light on the flow dynamics of coaxial jet flows. Subsequently, LESs are performed for a range of Mach and Reynolds numbers to systematically analyze the influences of the temperaturemore » and the velocity ratios between the primary and the secondary (bypass) stream. The results provide a basis for a detailed analysis of fundamental flow-acoustic phenomena in the considered heated coaxial jet flows. Increasing the primary-jet temperature leads to an increase of fluctuation levels and to an amplification of far-field noise, especially at low frequencies. Strong mixing between the cold bypass stream and the hot primary stream as well as the intermittent character of the flow field at the end of the potential core lead to a pronounced noise radiation at an aft angle of approximately 35{sup ∘}. The velocity ratio strongly affects the shear-layer development and therefore also the noise generation mechanisms. Increasing the secondary-stream velocity amplifies the dominance of outer shear-layer perturbations while the disturbance growth rates in the inner shear layer decrease. Already for r{sub mic} > 40R{sub 1}, where r{sub mic} is the distance from the end of the potential core and R{sub 1} is the core-jet radius, a perfect 1/r{sub mic} decay of the sound pressure amplitudes is observed. The potential-core length increases for higher secondary-stream velocities which leads to a shift of the center of the dominant acoustic radiation in the downstream direction.« less
Optimizing the use of a sensor resource for opponent polarization coding
Heras, Francisco J.H.
2017-01-01
Flies use specialized photoreceptors R7 and R8 in the dorsal rim area (DRA) to detect skylight polarization. R7 and R8 form a tiered waveguide (central rhabdomere pair, CRP) with R7 on top, filtering light delivered to R8. We examine how the division of a given resource, CRP length, between R7 and R8 affects their ability to code polarization angle. We model optical absorption to show how the length fractions allotted to R7 and R8 determine the rates at which they transduce photons, and correct these rates for transduction unit saturation. The rates give polarization signal and photon noise in R7, and in R8. Their signals are combined in an opponent unit, intrinsic noise added, and the unit’s output analysed to extract two measures of coding ability, number of discriminable polarization angles and mutual information. A very long R7 maximizes opponent signal amplitude, but codes inefficiently due to photon noise in the very short R8. Discriminability and mutual information are optimized by maximizing signal to noise ratio, SNR. At lower light levels approximately equal lengths of R7 and R8 are optimal because photon noise dominates. At higher light levels intrinsic noise comes to dominate and a shorter R8 is optimum. The optimum R8 length fractions falls to one third. This intensity dependent range of optimal length fractions corresponds to the range observed in different fly species and is not affected by transduction unit saturation. We conclude that a limited resource, rhabdom length, can be divided between two polarization sensors, R7 and R8, to optimize opponent coding. We also find that coding ability increases sub-linearly with total rhabdom length, according to the law of diminishing returns. Consequently, the specialized shorter central rhabdom in the DRA codes polarization twice as efficiently with respect to rhabdom length than the longer rhabdom used in the rest of the eye. PMID:28316880
Noise Assessment of the Chicago Transit Authority Rail Rapid Transit System
DOT National Transportation Integrated Search
1979-01-01
The report describes the noise on and near the Chicago Transit Authority (CTA) urban rail transit lines. The CTA urban rail lines consist of approximately 86 miles of two-way revenue track (of which 9.6 miles are in subway) and 155 stations. Noise da...
Sigworth, F J
1985-05-01
The random passage of ions through an open channel is expected to result in shot noise fluctuations in the channel current. The patch-clamp technique now allows fluctuations of this size to be observed in single-channel currents. In the experiments reported here the acetylcholine-induced currents in cultured rat muscle cells were analyzed; fluctuations were found that were considerably larger than expected for shot noise. A low-frequency component, which was fitted with a Lorentzian, was examined in detail; it appears to arise from fluctuations in channel conductance of approximately 3% on a time scale of 1 ms. The characteristic relaxation time is voltage dependent and temperature dependent (Q10 approximately equal to 3) suggesting that the fluctuations arise from conformational fluctuations in the channel protein.
Understanding channel and contact effects on transport in 1-dimensional nanotransistors.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Swartzentruber, Brian S.; Delker, Collin James; Yoo, Jinkyoung
Nanowire transistors are generally formed by metal contacts to a uniformly doped nanowire. The transistor can be modeled as a series combination of resistances from both the channel and the contacts. In this study, a simple model is proposed consisting of a resistive channel in series with two Schottky metal-semiconductor contacts modeled using the WKB approximation. This model captures several phenomena commonly observed in nanowire transistor measurements, including the mobility as a function of gate potential, mobility reduction with respect to bulk mobility, and non-linearities in output characteristics. For example, the maximum measured mobility as a function of gate voltagemore » in a nanowire transistor can be predicted based on the semiconductor bulk mobility in addition to barrier height and other properties of the contact. The model is then extended to nanowires with axial p-n junctions having an inde- pendent gate over each wire segment by splitting the channel resistance into a series component for each doping segment. Finally, the contact-channel model is applied to low-frequency noise analysis in nanowire devices, where the noise can be generated in both the channel and the contacts. Because contacts play a major, yet often neglected, role in nanowire transistor operation, they must be accounted for in order to extract meaningful parameters from I-V and noise measurements.« less
1/f-Noise of open bacterial porin channels.
Wohnsland, F; Benz, R
1997-07-01
General diffusion pores and specific porin channels from outer membranes of gram-negative bacteria were reconstituted into lipid bilayer membranes. The current noise of the channels was investigated for the different porins in the open state and in the ligand-induced closed state using fast Fourier transformation. The open channel noise exhibited 1/f-noise for frequencies up to 200 Hz. The 1/f-noise was investigated using the Hooge formula (Hooge, Phys. Lett. 29A: 139-140 (1969)), and the Hooge parameter alpha was calculated for all bacterial porins used in this study. The 1/f-noise was in part caused by slow inactivation and activation of porin channels. However, when care was taken that during the noise measurement no opening or closing of porin channels occurred, the Hooge Parameter alpha was a meaningful number for a given channel. A linear relationship was observed between alpha and the single-channel conductance, g, of the different porins. This linear relation between single-channel conductance and the Hooge parameter alpha could be qualitatively explained by assuming that the passing of an ion through a bacterial porin channel is-to a certain extent-influenced by nonlinear effects between channel wall and passing ion.
Adaptive Noise Suppression Using Digital Signal Processing
NASA Technical Reports Server (NTRS)
Kozel, David; Nelson, Richard
1996-01-01
A signal to noise ratio dependent adaptive spectral subtraction algorithm is developed to eliminate noise from noise corrupted speech signals. The algorithm determines the signal to noise ratio and adjusts the spectral subtraction proportion appropriately. After spectra subtraction low amplitude signals are squelched. A single microphone is used to obtain both eh noise corrupted speech and the average noise estimate. This is done by determining if the frame of data being sampled is a voiced or unvoiced frame. During unvoice frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Applications include the emergency egress vehicle and the crawler transporter.
Effects of entanglement in an ideal optical amplifier
NASA Astrophysics Data System (ADS)
Franson, J. D.; Brewster, R. A.
2018-04-01
In an ideal linear amplifier, the output signal is linearly related to the input signal with an additive noise that is independent of the input. The decoherence of a quantum-mechanical state as a result of optical amplification is usually assumed to be due to the addition of quantum noise. Here we show that entanglement between the input signal and the amplifying medium can produce an exponentially-large amount of decoherence in an ideal optical amplifier even when the gain is arbitrarily close to unity and the added noise is negligible. These effects occur for macroscopic superposition states, where even a small amount of gain can leave a significant amount of which-path information in the environment. Our results show that the usual input/output relation of a linear amplifier does not provide a complete description of the output state when post-selection is used.
Preconditioned alternating direction method of multipliers for inverse problems with constraints
NASA Astrophysics Data System (ADS)
Jiao, Yuling; Jin, Qinian; Lu, Xiliang; Wang, Weijie
2017-02-01
We propose a preconditioned alternating direction method of multipliers (ADMM) to solve linear inverse problems in Hilbert spaces with constraints, where the feature of the sought solution under a linear transformation is captured by a possibly non-smooth convex function. During each iteration step, our method avoids solving large linear systems by choosing a suitable preconditioning operator. In case the data is given exactly, we prove the convergence of our preconditioned ADMM without assuming the existence of a Lagrange multiplier. In case the data is corrupted by noise, we propose a stopping rule using information on noise level and show that our preconditioned ADMM is a regularization method; we also propose a heuristic rule when the information on noise level is unavailable or unreliable and give its detailed analysis. Numerical examples are presented to test the performance of the proposed method.
NASA Technical Reports Server (NTRS)
Pain, Bedabrata; Yang, Guang; Ortiz, Monico; Wrigley, Christopher; Hancock, Bruce; Cunningham, Thomas
2000-01-01
Noise in photodiode-type CMOS active pixel sensors (APS) is primarily due to the reset (kTC) noise at the sense node, since it is difficult to implement in-pixel correlated double sampling for a 2-D array. Signal integrated on the photodiode sense node (SENSE) is calculated by measuring difference between the voltage on the column bus (COL) - before and after the reset (RST) is pulsed. Lower than kTC noise can be achieved with photodiode-type pixels by employing "softreset" technique. Soft-reset refers to resetting with both drain and gate of the n-channel reset transistor kept at the same potential, causing the sense node to be reset using sub-threshold MOSFET current. However, lowering of noise is achieved only at the expense higher image lag and low-light-level non-linearity. In this paper, we present an analysis to explain the noise behavior, show evidence of degraded performance under low-light levels, and describe new pixels that eliminate non-linearity and lag without compromising noise.
Synthesis and analysis of discriminators under influence of broadband non-Gaussian noise
NASA Astrophysics Data System (ADS)
Artyushenko, V. M.; Volovach, V. I.
2018-01-01
We considered the problems of the synthesis and analysis of discriminators, when the useful signal is exposed to non-Gaussian additive broadband noise. It is shown that in this case, the discriminator of the tracking meter should contain the nonlinear transformation unit, the characteristics of which are determined by the Fisher information relative to the probability density function of the mixture of non-Gaussian broadband noise and mismatch errors. The parameters of the discriminatory and phase characteristics of the discriminators working under the above conditions are obtained. It is shown that the efficiency of non-linear processing depends on the ratio of power of FM noise to the power of Gaussian noise. The analysis of the information loss of signal transformation caused by the linear section of discriminatory characteristics of the unit of nonlinear transformations of the discriminator is carried out. It is shown that the average slope of the nonlinear transformation characteristic is determined by the Fisher information relative to the probability density function of the mixture of non-Gaussian noise and mismatch errors.
How to characterize the nonlinear amplifier?
NASA Technical Reports Server (NTRS)
Kallistratova, Dmitri Kouznetsov; Cotera, Carlos Flores
1994-01-01
The conception of the amplification of the coherent field is formulated. The definition of the coefficient of the amplification as the relation between the mean value of the field at the output to the value at the input and the definition of the noise as the difference between the number of photons in the output mode and square of the modulus of the mean value of the output amplitude are considered. Using a simple example it is shown that by these definitions the noise of the nonlinear amplifier may be less than the noise of the ideal linear amplifier of the same amplification coefficient. Proposals to search another definition of basic parameters of the nonlinear amplifiers are discussed. This definition should enable us to formulate the universal fundamental lower limit of the noise which should be valid for linear quantum amplifiers as for nonlinear ones.
Computation of output feedback gains for linear stochastic systems using the Zangwill-Powell method
NASA Technical Reports Server (NTRS)
Kaufman, H.
1977-01-01
Because conventional optimal linear regulator theory results in a controller which requires the capability of measuring and/or estimating the entire state vector, it is of interest to consider procedures for computing controls which are restricted to be linear feedback functions of a lower dimensional output vector and which take into account the presence of measurement noise and process uncertainty. To this effect a stochastic linear model has been developed that accounts for process parameter and initial uncertainty, measurement noise, and a restricted number of measurable outputs. Optimization with respect to the corresponding output feedback gains was then performed for both finite and infinite time performance indices without gradient computation by using Zangwill's modification of a procedure originally proposed by Powell.
Remo, John L; Adams, Richard G; Jones, Michael C
2007-08-20
Generation and effects of atmospherically propagated electromagnetic pulses (EMPs) initiated by photoelectrons ejected by the high density and temperature target surface plasmas from multiterawatt laser pulses are analyzed. These laser radiation pulse interactions can significantly increase noise levels, thereby obscuring data (sometimes totally) and may even damage sensitive probe and detection instrumentation. Noise effects from high energy density (approximately multiterawatt) laser pulses (approximately 300-400 ps pulse widths) interacting with thick approximately 1 mm) metallic and dielectric solid targets and dielectric-metallic powder mixtures are interpreted as transient resonance radiation associated with surface charge fluctuations on the target chamber that functions as a radiating antenna. Effective solutions that minimize atmospheric EMP effects on internal and proximate electronic and electro-optical equipment external to the system based on systematic measurements using Moebius loop antennas, interpretations of signal periodicities, and dissipation indicators determining transient noise origin characteristics from target emissions are described. Analytic models for the effect of target chamber resonances and associated noise current and temperature in a probe diode laser are described.
Very High Current Density Nb/AlN/Nb Tunnel Junctions for Low-Noise Submillimeter Mixers
NASA Technical Reports Server (NTRS)
Kawamura, Jonathan; Miller, David; Chen, Jian; Zmuidzinas, Jonas; Bumble, Bruce; LeDuc, Henry G.; Stern, Jeff A.
2000-01-01
We have fabricated and tested submillimeter-wave superconductor-insulator-superconductor (SIS) mixers using very high current density Nb/AlN/Nb tunnel junctions (J(sub c) approximately equal 30 kA/sq cm) . The junctions have low resistance-area products (R(sub N)A approximately 5.6 Omega.sq micron), good subgap to normal resistance ratios R(sub sg)/R(sub N) approximately equal 10, and good run-to-run reproducibility. From Fourier transform spectrometer measurements, we infer that omega.R(sub N)C = 1 at 270 GHz. This is a factor of 2.5 improvement over what is generally available with Nb/AlO(x)/Nb junctions suitable for low-noise mixers. The AlN-barrier junctions are indeed capable of low-noise operation: we measure an uncorrected receiver noise temperature of T(sub RX) = 110 K (DSB) at 533 GHz for an unoptimized device. In addition to providing wider bandwidth operation at lower frequencies, the AlN-barrier junctions will considerably improve the performance of THz SIS mixers by reducing RF loss in the tuning circuits.
Matheson, Mark; Clark, Charlotte; Martin, Rocio; van Kempen, Elise; Haines, Mary; Barrio, Isabel Lopez; Hygge, Staffan; Stansfeld, Stephen
2010-01-01
Previous studies have found that chronic exposure to aircraft noise has a negative effect on children's performance on tests of episodic memory. The present study extended the design of earlier studies in three ways: firstly, by examining the effects of two noise sources, aircraft and road traffic, secondly, by examining exposure-effect relationships, and thirdly, by carrying out parallel field studies in three European countries, allowing cross-country comparisons to be made. A total of 2844 children aged between 8 years 10 months and 12 years 10 months (mean age 10 years 6 months) completed classroom-based tests of cued recall, recognition memory and prospective memory. Questionnaires were also completed by the children and their parents in order to provide information about socioeconomic context. Multilevel modeling analysis revealed aircraft noise to be associated with an impairment of recognition memory in a linear exposure-effect relationship. The analysis also found road traffic noise to be associated with improved performance on cued recall in a linear exposure-effect relationship. No significant association was found between exposure to aircraft noise and cued recall or prospective memory. Likewise, no significant association was found between road traffic noise and recognition or prospective memory. Taken together, these findings indicate that exposure to aircraft noise and road traffic noise can impact on certain aspects of children's episodic memory.
Effect of cessation of late-night landing noise on sleep electrophysiology in the home
NASA Technical Reports Server (NTRS)
Pearsons, K. S.; Fidell, S.; Bennett, R. L.; Friedman, J.; Globus, G.
1974-01-01
Simultaneous measurements of noise exposure and sleep electrophysiology were made in homes before and after cessation of nighttime aircraft landing noise. Six people were tested, all of whom had been exposed to intense aircraft noise for at least two years. Noise measurements indicated a large reduction in the hourly noise level during nighttime hours, but no charge during the daytime hours. Sleep measures indicated no dramatic changes in sleep patterns either immediately after a marked change in nocturnal noise exposure or approximately a month thereafter. No strong relationship was observed between noise level and sleep disturbances over the range from 60 to 90 db(A).
NASA Astrophysics Data System (ADS)
Motes, Keith R.; Olson, Jonathan P.; Rabeaux, Evan J.; Dowling, Jonathan P.; Olson, S. Jay; Rohde, Peter P.
2015-05-01
Quantum number-path entanglement is a resource for supersensitive quantum metrology and in particular provides for sub-shot-noise or even Heisenberg-limited sensitivity. However, such number-path entanglement has been thought to be resource intensive to create in the first place—typically requiring either very strong nonlinearities, or nondeterministic preparation schemes with feedforward, which are difficult to implement. Very recently, arising from the study of quantum random walks with multiphoton walkers, as well as the study of the computational complexity of passive linear optical interferometers fed with single-photon inputs, it has been shown that such passive linear optical devices generate a superexponentially large amount of number-path entanglement. A logical question to ask is whether this entanglement may be exploited for quantum metrology. We answer that question here in the affirmative by showing that a simple, passive, linear-optical interferometer—fed with only uncorrelated, single-photon inputs, coupled with simple, single-mode, disjoint photodetection—is capable of significantly beating the shot-noise limit. Our result implies a pathway forward to practical quantum metrology with readily available technology.
Contextual Multi-armed Bandits under Feature Uncertainty
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yun, Seyoung; Nam, Jun Hyun; Mo, Sangwoo
We study contextual multi-armed bandit problems under linear realizability on rewards and uncertainty (or noise) on features. For the case of identical noise on features across actions, we propose an algorithm, coined NLinRel, having O(T⁷/₈(log(dT)+K√d)) regret bound for T rounds, K actions, and d-dimensional feature vectors. Next, for the case of non-identical noise, we observe that popular linear hypotheses including NLinRel are impossible to achieve such sub-linear regret. Instead, under assumption of Gaussian feature vectors, we prove that a greedy algorithm has O(T²/₃√log d)regret bound with respect to the optimal linear hypothesis. Utilizing our theoretical understanding on the Gaussian case,more » we also design a practical variant of NLinRel, coined Universal-NLinRel, for arbitrary feature distributions. It first runs NLinRel for finding the ‘true’ coefficient vector using feature uncertainties and then adjust it to minimize its regret using the statistical feature information. We justify the performance of Universal-NLinRel on both synthetic and real-world datasets.« less
Motes, Keith R; Olson, Jonathan P; Rabeaux, Evan J; Dowling, Jonathan P; Olson, S Jay; Rohde, Peter P
2015-05-01
Quantum number-path entanglement is a resource for supersensitive quantum metrology and in particular provides for sub-shot-noise or even Heisenberg-limited sensitivity. However, such number-path entanglement has been thought to be resource intensive to create in the first place--typically requiring either very strong nonlinearities, or nondeterministic preparation schemes with feedforward, which are difficult to implement. Very recently, arising from the study of quantum random walks with multiphoton walkers, as well as the study of the computational complexity of passive linear optical interferometers fed with single-photon inputs, it has been shown that such passive linear optical devices generate a superexponentially large amount of number-path entanglement. A logical question to ask is whether this entanglement may be exploited for quantum metrology. We answer that question here in the affirmative by showing that a simple, passive, linear-optical interferometer--fed with only uncorrelated, single-photon inputs, coupled with simple, single-mode, disjoint photodetection--is capable of significantly beating the shot-noise limit. Our result implies a pathway forward to practical quantum metrology with readily available technology.
Piecewise linear approximation for hereditary control problems
NASA Technical Reports Server (NTRS)
Propst, Georg
1987-01-01
Finite dimensional approximations are presented for linear retarded functional differential equations by use of discontinuous piecewise linear functions. The approximation scheme is applied to optimal control problems when a quadratic cost integral has to be minimized subject to the controlled retarded system. It is shown that the approximate optimal feedback operators converge to the true ones both in case the cost integral ranges over a finite time interval as well as in the case it ranges over an infinite time interval. The arguments in the latter case rely on the fact that the piecewise linear approximations to stable systems are stable in a uniform sense. This feature is established using a vector-component stability criterion in the state space R(n) x L(2) and the favorable eigenvalue behavior of the piecewise linear approximations.
ORACLS- OPTIMAL REGULATOR ALGORITHMS FOR THE CONTROL OF LINEAR SYSTEMS (CDC VERSION)
NASA Technical Reports Server (NTRS)
Armstrong, E. S.
1994-01-01
This control theory design package, called Optimal Regulator Algorithms for the Control of Linear Systems (ORACLS), was developed to aid in the design of controllers and optimal filters for systems which can be modeled by linear, time-invariant differential and difference equations. Optimal linear quadratic regulator theory, currently referred to as the Linear-Quadratic-Gaussian (LQG) problem, has become the most widely accepted method of determining optimal control policy. Within this theory, the infinite duration time-invariant problems, which lead to constant gain feedback control laws and constant Kalman-Bucy filter gains for reconstruction of the system state, exhibit high tractability and potential ease of implementation. A variety of new and efficient methods in the field of numerical linear algebra have been combined into the ORACLS program, which provides for the solution to time-invariant continuous or discrete LQG problems. The ORACLS package is particularly attractive to the control system designer because it provides a rigorous tool for dealing with multi-input and multi-output dynamic systems in both continuous and discrete form. The ORACLS programming system is a collection of subroutines which can be used to formulate, manipulate, and solve various LQG design problems. The ORACLS program is constructed in a manner which permits the user to maintain considerable flexibility at each operational state. This flexibility is accomplished by providing primary operations, analysis of linear time-invariant systems, and control synthesis based on LQG methodology. The input-output routines handle the reading and writing of numerical matrices, printing heading information, and accumulating output information. The basic vector-matrix operations include addition, subtraction, multiplication, equation, norm construction, tracing, transposition, scaling, juxtaposition, and construction of null and identity matrices. The analysis routines provide for the following computations: the eigenvalues and eigenvectors of real matrices; the relative stability of a given matrix; matrix factorization; the solution of linear constant coefficient vector-matrix algebraic equations; the controllability properties of a linear time-invariant system; the steady-state covariance matrix of an open-loop stable system forced by white noise; and the transient response of continuous linear time-invariant systems. The control law design routines of ORACLS implement some of the more common techniques of time-invariant LQG methodology. For the finite-duration optimal linear regulator problem with noise-free measurements, continuous dynamics, and integral performance index, a routine is provided which implements the negative exponential method for finding both the transient and steady-state solutions to the matrix Riccati equation. For the discrete version of this problem, the method of backwards differencing is applied to find the solutions to the discrete Riccati equation. A routine is also included to solve the steady-state Riccati equation by the Newton algorithms described by Klein, for continuous problems, and by Hewer, for discrete problems. Another routine calculates the prefilter gain to eliminate control state cross-product terms in the quadratic performance index and the weighting matrices for the sampled data optimal linear regulator problem. For cases with measurement noise, duality theory and optimal regulator algorithms are used to calculate solutions to the continuous and discrete Kalman-Bucy filter problems. Finally, routines are included to implement the continuous and discrete forms of the explicit (model-in-the-system) and implicit (model-in-the-performance-index) model following theory. These routines generate linear control laws which cause the output of a dynamic time-invariant system to track the output of a prescribed model. In order to apply ORACLS, the user must write an executive (driver) program which inputs the problem coefficients, formulates and selects the routines to be used to solve the problem, and specifies the desired output. There are three versions of ORACLS source code available for implementation: CDC, IBM, and DEC. The CDC version has been implemented on a CDC 6000 series computer with a central memory of approximately 13K (octal) of 60 bit words. The CDC version is written in FORTRAN IV, was developed in 1978, and last updated in 1989. The IBM version has been implemented on an IBM 370 series computer with a central memory requirement of approximately 300K of 8 bit bytes. The IBM version is written in FORTRAN IV and was generated in 1981. The DEC version has been implemented on a VAX series computer operating under VMS. The VAX version is written in FORTRAN 77 and was generated in 1986.
ORACLS- OPTIMAL REGULATOR ALGORITHMS FOR THE CONTROL OF LINEAR SYSTEMS (DEC VAX VERSION)
NASA Technical Reports Server (NTRS)
Frisch, H.
1994-01-01
This control theory design package, called Optimal Regulator Algorithms for the Control of Linear Systems (ORACLS), was developed to aid in the design of controllers and optimal filters for systems which can be modeled by linear, time-invariant differential and difference equations. Optimal linear quadratic regulator theory, currently referred to as the Linear-Quadratic-Gaussian (LQG) problem, has become the most widely accepted method of determining optimal control policy. Within this theory, the infinite duration time-invariant problems, which lead to constant gain feedback control laws and constant Kalman-Bucy filter gains for reconstruction of the system state, exhibit high tractability and potential ease of implementation. A variety of new and efficient methods in the field of numerical linear algebra have been combined into the ORACLS program, which provides for the solution to time-invariant continuous or discrete LQG problems. The ORACLS package is particularly attractive to the control system designer because it provides a rigorous tool for dealing with multi-input and multi-output dynamic systems in both continuous and discrete form. The ORACLS programming system is a collection of subroutines which can be used to formulate, manipulate, and solve various LQG design problems. The ORACLS program is constructed in a manner which permits the user to maintain considerable flexibility at each operational state. This flexibility is accomplished by providing primary operations, analysis of linear time-invariant systems, and control synthesis based on LQG methodology. The input-output routines handle the reading and writing of numerical matrices, printing heading information, and accumulating output information. The basic vector-matrix operations include addition, subtraction, multiplication, equation, norm construction, tracing, transposition, scaling, juxtaposition, and construction of null and identity matrices. The analysis routines provide for the following computations: the eigenvalues and eigenvectors of real matrices; the relative stability of a given matrix; matrix factorization; the solution of linear constant coefficient vector-matrix algebraic equations; the controllability properties of a linear time-invariant system; the steady-state covariance matrix of an open-loop stable system forced by white noise; and the transient response of continuous linear time-invariant systems. The control law design routines of ORACLS implement some of the more common techniques of time-invariant LQG methodology. For the finite-duration optimal linear regulator problem with noise-free measurements, continuous dynamics, and integral performance index, a routine is provided which implements the negative exponential method for finding both the transient and steady-state solutions to the matrix Riccati equation. For the discrete version of this problem, the method of backwards differencing is applied to find the solutions to the discrete Riccati equation. A routine is also included to solve the steady-state Riccati equation by the Newton algorithms described by Klein, for continuous problems, and by Hewer, for discrete problems. Another routine calculates the prefilter gain to eliminate control state cross-product terms in the quadratic performance index and the weighting matrices for the sampled data optimal linear regulator problem. For cases with measurement noise, duality theory and optimal regulator algorithms are used to calculate solutions to the continuous and discrete Kalman-Bucy filter problems. Finally, routines are included to implement the continuous and discrete forms of the explicit (model-in-the-system) and implicit (model-in-the-performance-index) model following theory. These routines generate linear control laws which cause the output of a dynamic time-invariant system to track the output of a prescribed model. In order to apply ORACLS, the user must write an executive (driver) program which inputs the problem coefficients, formulates and selects the routines to be used to solve the problem, and specifies the desired output. There are three versions of ORACLS source code available for implementation: CDC, IBM, and DEC. The CDC version has been implemented on a CDC 6000 series computer with a central memory of approximately 13K (octal) of 60 bit words. The CDC version is written in FORTRAN IV, was developed in 1978, and last updated in 1986. The IBM version has been implemented on an IBM 370 series computer with a central memory requirement of approximately 300K of 8 bit bytes. The IBM version is written in FORTRAN IV and was generated in 1981. The DEC version has been implemented on a VAX series computer operating under VMS. The VAX version is written in FORTRAN 77 and was generated in 1986.
Visual recovery in cortical blindness is limited by high internal noise
Cavanaugh, Matthew R.; Zhang, Ruyuan; Melnick, Michael D.; Das, Anasuya; Roberts, Mariel; Tadin, Duje; Carrasco, Marisa; Huxlin, Krystel R.
2015-01-01
Damage to the primary visual cortex typically causes cortical blindness (CB) in the hemifield contralateral to the damaged hemisphere. Recent evidence indicates that visual training can partially reverse CB at trained locations. Whereas training induces near-complete recovery of coarse direction and orientation discriminations, deficits in fine motion processing remain. Here, we systematically disentangle components of the perceptual inefficiencies present in CB fields before and after coarse direction discrimination training. In seven human CB subjects, we measured threshold versus noise functions before and after coarse direction discrimination training in the blind field and at corresponding intact field locations. Threshold versus noise functions were analyzed within the framework of the linear amplifier model and the perceptual template model. Linear amplifier model analysis identified internal noise as a key factor differentiating motion processing across the tested areas, with visual training reducing internal noise in the blind field. Differences in internal noise also explained residual perceptual deficits at retrained locations. These findings were confirmed with perceptual template model analysis, which further revealed that the major residual deficits between retrained and intact field locations could be explained by differences in internal additive noise. There were no significant differences in multiplicative noise or the ability to process external noise. Together, these results highlight the critical role of altered internal noise processing in mediating training-induced visual recovery in CB fields, and may explain residual perceptual deficits relative to intact regions of the visual field. PMID:26389544
Effects of Background Noise on Cortical Encoding of Speech in Autism Spectrum Disorders
ERIC Educational Resources Information Center
Russo, Nicole; Zecker, Steven; Trommer, Barbara; Chen, Julia; Kraus, Nina
2009-01-01
This study provides new evidence of deficient auditory cortical processing of speech in noise in autism spectrum disorders (ASD). Speech-evoked responses (approximately 100-300 ms) in quiet and background noise were evaluated in typically-developing (TD) children and children with ASD. ASD responses showed delayed timing (both conditions) and…
NASA Astrophysics Data System (ADS)
Cotté, B.
2018-05-01
This study proposes to couple a source model based on Amiet's theory and a parabolic equation code in order to model wind turbine noise emission and propagation in an inhomogeneous atmosphere. Two broadband noise generation mechanisms are considered, namely trailing edge noise and turbulent inflow noise. The effects of wind shear and atmospheric turbulence are taken into account using the Monin-Obukhov similarity theory. The coupling approach, based on the backpropagation method to preserve the directivity of the aeroacoustic sources, is validated by comparison with an analytical solution for the propagation over a finite impedance ground in a homogeneous atmosphere. The influence of refraction effects is then analyzed for different directions of propagation. The spectrum modification related to the ground effect and the presence of a shadow zone for upwind receivers are emphasized. The validity of the point source approximation that is often used in wind turbine noise propagation models is finally assessed. This approximation exaggerates the interference dips in the spectra, and is not able to correctly predict the amplitude modulation.
Effects of background noise on total noise annoyance
NASA Technical Reports Server (NTRS)
Willshire, K. F.
1987-01-01
Two experiments were conducted to assess the effects of combined community noise sources on annoyance. The first experiment baseline relationships between annoyance and noise level for three community noise sources (jet aircraft flyovers, traffic and air conditioners) presented individually. Forty eight subjects evaluated the annoyance of each noise source presented at four different noise levels. Results indicated the slope of the linear relationship between annoyance and noise level for the traffic noise was significantly different from that of aircraft and of air conditioner noise, which had equal slopes. The second experiment investigated annoyance response to combined noise sources, with aircraft noise defined as the major noise source and traffic and air conditioner noise as background noise sources. Effects on annoyance of noise level differences between aircraft and background noise for three total noise levels and for both background noise sources were determined. A total of 216 subjects were required to make either total or source specific annoyance judgements, or a combination of the two, for a wide range of combined noise conditions.
EIT Intensity Noise Spectroscopy
NASA Astrophysics Data System (ADS)
Crescimanno, Michael; Xiao, Yanhong; Baryakhtar, Maria; Hohensee, Michael; Phillips, David; Walsworth, Ron
2008-10-01
Intensity noise correlations in coherently-prepared media can reveal underlying spectroscopic detail, such as power broadening-free resonances. We analyze recent experimental results using very simple theory: The intensity noise correlation spectra can be quantitatively understood entirely in terms of static ensemble averages of the medium's steady state response. This is significantly simpler than stochastic integration of the Bloch equations, and leads to physical insights we apply to non-linear Faraday rotation and noise spectra in optically thick media.
Performance of a commercial transport under typical MLS noise environment
NASA Technical Reports Server (NTRS)
Ho, J. K.
1986-01-01
The performance of a 747-200 automatic flight control system (AFCS) subjected to typical Microwave Landing System (MLS) noise is discussed. The performance is then compared with the results from a previous study which had a B747 AFCS subjected to the MLS standards and recommended practices (SARPS) maximum allowable noise. A glide slope control run with Instrument Landing System (ILS) noise is also conducted. Finally, a linear covariance analysis is presented.
Yumba, Wycliffe Kabaywe
2017-01-01
Previous studies have demonstrated that successful listening with advanced signal processing in digital hearing aids is associated with individual cognitive capacity, particularly working memory capacity (WMC). This study aimed to examine the relationship between cognitive abilities (cognitive processing speed and WMC) and individual listeners’ responses to digital signal processing settings in adverse listening conditions. A total of 194 native Swedish speakers (83 women and 111 men), aged 33–80 years (mean = 60.75 years, SD = 8.89), with bilateral, symmetrical mild to moderate sensorineural hearing loss who had completed a lexical decision speed test (measuring cognitive processing speed) and semantic word-pair span test (SWPST, capturing WMC) participated in this study. The Hagerman test (capturing speech recognition in noise) was conducted using an experimental hearing aid with three digital signal processing settings: (1) linear amplification without noise reduction (NoP), (2) linear amplification with noise reduction (NR), and (3) non-linear amplification without NR (“fast-acting compression”). The results showed that cognitive processing speed was a better predictor of speech intelligibility in noise, regardless of the types of signal processing algorithms used. That is, there was a stronger association between cognitive processing speed and NR outcomes and fast-acting compression outcomes (in steady state noise). We observed a weaker relationship between working memory and NR, but WMC did not relate to fast-acting compression. WMC was a relatively weaker predictor of speech intelligibility in noise. These findings might have been different if the participants had been provided with training and or allowed to acclimatize to binary masking noise reduction or fast-acting compression. PMID:28861009
Analysis of the iteratively regularized Gauss-Newton method under a heuristic rule
NASA Astrophysics Data System (ADS)
Jin, Qinian; Wang, Wei
2018-03-01
The iteratively regularized Gauss-Newton method is one of the most prominent regularization methods for solving nonlinear ill-posed inverse problems when the data is corrupted by noise. In order to produce a useful approximate solution, this iterative method should be terminated properly. The existing a priori and a posteriori stopping rules require accurate information on the noise level, which may not be available or reliable in practical applications. In this paper we propose a heuristic selection rule for this regularization method, which requires no information on the noise level. By imposing certain conditions on the noise, we derive a posteriori error estimates on the approximate solutions under various source conditions. Furthermore, we establish a convergence result without using any source condition. Numerical results are presented to illustrate the performance of our heuristic selection rule.
Estimation of Noise Properties for TV-regularized Image Reconstruction in Computed Tomography
Sánchez, Adrian A.
2016-01-01
A method for predicting the image covariance resulting from total-variation-penalized iterative image reconstruction (TV-penalized IIR) is presented and demonstrated in a variety of contexts. The method is validated against the sample covariance from statistical noise realizations for a small image using a variety of comparison metrics. Potential applications for the covariance approximation include investigation of image properties such as object- and signal-dependence of noise, and noise stationarity. These applications are demonstrated, along with the construction of image pixel variance maps for two-dimensional 128 × 128 pixel images. Methods for extending the proposed covariance approximation to larger images and improving computational efficiency are discussed. Future work will apply the developed methodology to the construction of task-based image quality metrics such as the Hotelling observer detectability for TV-based IIR. PMID:26308968
Estimation of noise properties for TV-regularized image reconstruction in computed tomography.
Sánchez, Adrian A
2015-09-21
A method for predicting the image covariance resulting from total-variation-penalized iterative image reconstruction (TV-penalized IIR) is presented and demonstrated in a variety of contexts. The method is validated against the sample covariance from statistical noise realizations for a small image using a variety of comparison metrics. Potential applications for the covariance approximation include investigation of image properties such as object- and signal-dependence of noise, and noise stationarity. These applications are demonstrated, along with the construction of image pixel variance maps for two-dimensional 128 × 128 pixel images. Methods for extending the proposed covariance approximation to larger images and improving computational efficiency are discussed. Future work will apply the developed methodology to the construction of task-based image quality metrics such as the Hotelling observer detectability for TV-based IIR.
Estimation of noise properties for TV-regularized image reconstruction in computed tomography
NASA Astrophysics Data System (ADS)
Sánchez, Adrian A.
2015-09-01
A method for predicting the image covariance resulting from total-variation-penalized iterative image reconstruction (TV-penalized IIR) is presented and demonstrated in a variety of contexts. The method is validated against the sample covariance from statistical noise realizations for a small image using a variety of comparison metrics. Potential applications for the covariance approximation include investigation of image properties such as object- and signal-dependence of noise, and noise stationarity. These applications are demonstrated, along with the construction of image pixel variance maps for two-dimensional 128× 128 pixel images. Methods for extending the proposed covariance approximation to larger images and improving computational efficiency are discussed. Future work will apply the developed methodology to the construction of task-based image quality metrics such as the Hotelling observer detectability for TV-based IIR.
Contrast-enhanced spectral mammography with a photon-counting detector.
Fredenberg, Erik; Hemmendorff, Magnus; Cederström, Björn; Aslund, Magnus; Danielsson, Mats
2010-05-01
Spectral imaging is a method in medical x-ray imaging to extract information about the object constituents by the material-specific energy dependence of x-ray attenuation. The authors have investigated a photon-counting spectral imaging system with two energy bins for contrast-enhanced mammography. System optimization and the potential benefit compared to conventional non-energy-resolved absorption imaging was studied. A framework for system characterization was set up that included quantum and anatomical noise and a theoretical model of the system was benchmarked to phantom measurements. Optimal combination of the energy-resolved images corresponded approximately to minimization of the anatomical noise, which is commonly referred to as energy subtraction. In that case, an ideal-observer detectability index could be improved close to 50% compared to absorption imaging in the phantom study. Optimization with respect to the signal-to-quantum-noise ratio, commonly referred to as energy weighting, yielded only a minute improvement. In a simulation of a clinically more realistic case, spectral imaging was predicted to perform approximately 30% better than absorption imaging for an average glandularity breast with an average level of anatomical noise. For dense breast tissue and a high level of anatomical noise, however, a rise in detectability by a factor of 6 was predicted. Another approximately 70%-90% improvement was found to be within reach for an optimized system. Contrast-enhanced spectral mammography is feasible and beneficial with the current system, and there is room for additional improvements. Inclusion of anatomical noise is essential for optimizing spectral imaging systems.
Single-Photon-Sensitive HgCdTe Avalanche Photodiode Detector
NASA Technical Reports Server (NTRS)
Huntington, Andrew
2013-01-01
The purpose of this program was to develop single-photon-sensitive short-wavelength infrared (SWIR) and mid-wavelength infrared (MWIR) avalanche photodiode (APD) receivers based on linear-mode HgCdTe APDs, for application by NASA in light detection and ranging (lidar) sensors. Linear-mode photon-counting APDs are desired for lidar because they have a shorter pixel dead time than Geiger APDs, and can detect sequential pulse returns from multiple objects that are closely spaced in range. Linear-mode APDs can also measure photon number, which Geiger APDs cannot, adding an extra dimension to lidar scene data for multi-photon returns. High-gain APDs with low multiplication noise are required for efficient linear-mode detection of single photons because of APD gain statistics -- a low-excess-noise APD will generate detectible current pulses from single photon input at a much higher rate of occurrence than will a noisy APD operated at the same average gain. MWIR and LWIR electron-avalanche HgCdTe APDs have been shown to operate in linear mode at high average avalanche gain (M > 1000) without excess multiplication noise (F = 1), and are therefore very good candidates for linear-mode photon counting. However, detectors fashioned from these narrow-bandgap alloys require aggressive cooling to control thermal dark current. Wider-bandgap SWIR HgCdTe APDs were investigated in this program as a strategy to reduce detector cooling requirements.
Weak-noise limit of a piecewise-smooth stochastic differential equation.
Chen, Yaming; Baule, Adrian; Touchette, Hugo; Just, Wolfram
2013-11-01
We investigate the validity and accuracy of weak-noise (saddle-point or instanton) approximations for piecewise-smooth stochastic differential equations (SDEs), taking as an illustrative example a piecewise-constant SDE, which serves as a simple model of Brownian motion with solid friction. For this model, we show that the weak-noise approximation of the path integral correctly reproduces the known propagator of the SDE at lowest order in the noise power, as well as the main features of the exact propagator with higher-order corrections, provided the singularity of the path integral associated with the nonsmooth SDE is treated with some heuristics. We also show that, as in the case of smooth SDEs, the deterministic paths of the noiseless system correctly describe the behavior of the nonsmooth SDE in the low-noise limit. Finally, we consider a smooth regularization of the piecewise-constant SDE and study to what extent this regularization can rectify some of the problems encountered when dealing with discontinuous drifts and singularities in SDEs.
Extracting Time-Accurate Acceleration Vectors From Nontrivial Accelerometer Arrangements.
Franck, Jennifer A; Blume, Janet; Crisco, Joseph J; Franck, Christian
2015-09-01
Sports-related concussions are of significant concern in many impact sports, and their detection relies on accurate measurements of the head kinematics during impact. Among the most prevalent recording technologies are videography, and more recently, the use of single-axis accelerometers mounted in a helmet, such as the HIT system. Successful extraction of the linear and angular impact accelerations depends on an accurate analysis methodology governed by the equations of motion. Current algorithms are able to estimate the magnitude of acceleration and hit location, but make assumptions about the hit orientation and are often limited in the position and/or orientation of the accelerometers. The newly formulated algorithm presented in this manuscript accurately extracts the full linear and rotational acceleration vectors from a broad arrangement of six single-axis accelerometers directly from the governing set of kinematic equations. The new formulation linearizes the nonlinear centripetal acceleration term with a finite-difference approximation and provides a fast and accurate solution for all six components of acceleration over long time periods (>250 ms). The approximation of the nonlinear centripetal acceleration term provides an accurate computation of the rotational velocity as a function of time and allows for reconstruction of a multiple-impact signal. Furthermore, the algorithm determines the impact location and orientation and can distinguish between glancing, high rotational velocity impacts, or direct impacts through the center of mass. Results are shown for ten simulated impact locations on a headform geometry computed with three different accelerometer configurations in varying degrees of signal noise. Since the algorithm does not require simplifications of the actual impacted geometry, the impact vector, or a specific arrangement of accelerometer orientations, it can be easily applied to many impact investigations in which accurate kinematics need to be extracted from single-axis accelerometer data.
Multi-channel Analysis of Passive Surface Waves (MAPS)
NASA Astrophysics Data System (ADS)
Xia, J.; Cheng, F. Mr; Xu, Z.; Wang, L.; Shen, C.; Liu, R.; Pan, Y.; Mi, B.; Hu, Y.
2017-12-01
Urbanization is an inevitable trend in modernization of human society. In the end of 2013 the Chinese Central Government launched a national urbanization plan—"Three 100 Million People", which aggressively and steadily pushes forward urbanization. Based on the plan, by 2020, approximately 100 million people from rural areas will permanently settle in towns, dwelling conditions of about 100 million people in towns and villages will be improved, and about 100 million people in the central and western China will permanently settle in towns. China's urbanization process will run at the highest speed in the urbanization history of China. Environmentally friendly, non-destructive and non-invasive geophysical assessment method has played an important role in the urbanization process in China. Because human noise and electromagnetic field due to industrial life, geophysical methods already used in urban environments (gravity, magnetics, electricity, seismic) face great challenges. But humanity activity provides an effective source of passive seismic methods. Claerbout pointed out that wavefileds that are received at one point with excitation at the other point can be reconstructed by calculating the cross-correlation of noise records at two surface points. Based on this idea (cross-correlation of two noise records) and the virtual source method, we proposed Multi-channel Analysis of Passive Surface Waves (MAPS). MAPS mainly uses traffic noise recorded with a linear receiver array. Because Multi-channel Analysis of Surface Waves can produces a shear (S) wave velocity model with high resolution in shallow part of the model, MPAS combines acquisition and processing of active source and passive source data in a same flow, which does not require to distinguish them. MAPS is also of ability of real-time quality control of noise recording that is important for near-surface applications in urban environment. The numerical and real-world examples demonstrated that MAPS can be used for accurate and fast imaging of high-frequency surface wave energy, and some examples also show that high quality imaging similar to those with active sources can be generated only by the use of a few minutes of noise. The use of cultural noise in town, MAPS can image S-wave velocity structure from the ground surface to hundreds of meters depth.
Voice tracking and spoken word recognition in the presence of other voices
NASA Astrophysics Data System (ADS)
Litong-Palima, Marisciel; Violanda, Renante; Saloma, Caesar
2004-12-01
We study the human hearing process by modeling the hair cell as a thresholded Hopf bifurcator and compare our calculations with experimental results involving human subjects in two different multi-source listening tasks of voice tracking and spoken-word recognition. In the model, we observed noise suppression by destructive interference between noise sources which weakens the effective noise strength acting on the hair cell. Different success rate characteristics were observed for the two tasks. Hair cell performance at low threshold levels agree well with results from voice-tracking experiments while those of word-recognition experiments are consistent with a linear model of the hearing process. The ability of humans to track a target voice is robust against cross-talk interference unlike word-recognition performance which deteriorates quickly with the number of uncorrelated noise sources in the environment which is a response behavior that is associated with linear systems.
NASA Technical Reports Server (NTRS)
Stankiewicz, N.
1982-01-01
The multiple channel input signal to a soft limiter amplifier as a traveling wave tube is represented as a finite, linear sum of Gaussian functions in the frequency domain. Linear regression is used to fit the channel shapes to a least squares residual error. Distortions in output signal, namely intermodulation products, are produced by the nonlinear gain characteristic of the amplifier and constitute the principal noise analyzed in this study. The signal to noise ratios are calculated for various input powers from saturation to 10 dB below saturation for two specific distributions of channels. A criterion for the truncation of the series expansion of the nonlinear transfer characteristic is given. It is found that he signal to noise ratios are very sensitive to the coefficients used in this expansion. Improper or incorrect truncation of the series leads to ambiguous results in the signal to noise ratios.
Antenna Calibration and Measurement Equipment
NASA Technical Reports Server (NTRS)
Rochblatt, David J.; Cortes, Manuel Vazquez
2012-01-01
A document describes the Antenna Calibration & Measurement Equipment (ACME) system that will provide the Deep Space Network (DSN) with instrumentation enabling a trained RF engineer at each complex to perform antenna calibration measurements and to generate antenna calibration data. This data includes continuous-scan auto-bore-based data acquisition with all-sky data gathering in support of 4th order pointing model generation requirements. Other data includes antenna subreflector focus, system noise temperature and tipping curves, antenna efficiency, reports system linearity, and instrument calibration. The ACME system design is based on the on-the-fly (OTF) mapping technique and architecture. ACME has contributed to the improved RF performance of the DSN by approximately a factor of two. It improved the pointing performances of the DSN antennas and productivity of its personnel and calibration engineers.
Nishizawa, N; Chen, Y; Hsiung, P; Ippen, E P; Fujimoto, J G
2004-12-15
Real-time, ultrahigh-resolution optical coherence tomography (OCT) is demonstrated in the 1.4-1.7-microm wavelength region with a stretched-pulse, passively mode-locked, Er-doped fiber laser and highly nonlinear fiber. The fiber laser generates 100-mW, linearly chirped pulses at a 51-MHz repetition rate. The pulses are compressed and then coupled into a normally dispersive highly nonlinear fiber to generate a low-noise supercontinuum with a 180-nm FWHM bandwidth and 38 mW of output power. This light source is stable, compact, and broadband, permitting high-speed, real-time, high-resolution OCT imaging. In vivo high-speed OCT imaging of human skin with approximately 5.5-microm resolution and 99-dB sensitivity is demonstrated.
Tsujino, Kenji; Akiba, Makoto; Sasaki, Masahide
2007-03-01
The charge-integration readout circuit was fabricated to achieve an ultralow-noise preamplifier for photoelectrons generated in an avalanche photodiode with linear mode operation at 77 K. To reduce the various kinds of noise, the capacitive transimpedance amplifier was used and consisted of low-capacitance circuit elements that were cooled with liquid nitrogen. As a result, the readout noise is equal to 3.0 electrons averaged for a period of 40 ms. We discuss the requirements for avalanche photodiodes to achieve photon-number-resolving detectors below this noise level.
Model Parameterization and P-wave AVA Direct Inversion for Young's Impedance
NASA Astrophysics Data System (ADS)
Zong, Zhaoyun; Yin, Xingyao
2017-05-01
AVA inversion is an important tool for elastic parameters estimation to guide the lithology prediction and "sweet spot" identification of hydrocarbon reservoirs. The product of the Young's modulus and density (named as Young's impedance in this study) is known as an effective lithology and brittleness indicator of unconventional hydrocarbon reservoirs. Density is difficult to predict from seismic data, which renders the estimation of the Young's impedance inaccurate in conventional approaches. In this study, a pragmatic seismic AVA inversion approach with only P-wave pre-stack seismic data is proposed to estimate the Young's impedance to avoid the uncertainty brought by density. First, based on the linearized P-wave approximate reflectivity equation in terms of P-wave and S-wave moduli, the P-wave approximate reflectivity equation in terms of the Young's impedance is derived according to the relationship between P-wave modulus, S-wave modulus, Young's modulus and Poisson ratio. This equation is further compared to the exact Zoeppritz equation and the linearized P-wave approximate reflectivity equation in terms of P- and S-wave velocities and density, which illustrates that this equation is accurate enough to be used for AVA inversion when the incident angle is within the critical angle. Parameter sensitivity analysis illustrates that the high correlation between the Young's impedance and density render the estimation of the Young's impedance difficult. Therefore, a de-correlation scheme is used in the pragmatic AVA inversion with Bayesian inference to estimate Young's impedance only with pre-stack P-wave seismic data. Synthetic examples demonstrate that the proposed approach is able to predict the Young's impedance stably even with moderate noise and the field data examples verify the effectiveness of the proposed approach in Young's impedance estimation and "sweet spots" evaluation.
A comparative robustness evaluation of feedforward neurofilters
NASA Technical Reports Server (NTRS)
Troudet, Terry; Merrill, Walter
1993-01-01
A comparative performance and robustness analysis is provided for feedforward neurofilters trained with back propagation to filter additive white noise. The signals used in this analysis are simulated pitch rate responses to typical pilot command inputs for a modern fighter aircraft model. Various configurations of nonlinear and linear neurofilters are trained to estimate exact signal values from input sequences of noisy sampled signal values. In this application, nonlinear neurofiltering is found to be more efficient than linear neurofiltering in removing the noise from responses of the nominal vehicle model, whereas linear neurofiltering is found to be more robust in the presence of changes in the vehicle dynamics. The possibility of enhancing neurofiltering through hybrid architectures based on linear and nonlinear neuroprocessing is therefore suggested as a way of taking advantage of the robustness of linear neurofiltering, while maintaining the nominal performance advantage of nonlinear neurofiltering.
NASA Astrophysics Data System (ADS)
Meng, Fanwei; Liu, Chengying; Li, Zhijun; Wang, Liping
2013-01-01
Due to low damping ratio, flat permanent magnet linear synchronous motor's vibration is difficult to be damped and the accuracy is limited. The vibration suppressing results are not good enough in the existing research because only the longitudinal direction vibration is considered while the normal direction vibration is neglected. The parameters of the direct-axis current controller are set to be the same as those of the quadrature-axis current controller commonly. This causes contradiction between signal noise and response. To suppress the vibration, the electromagnetic force model of the flat permanent magnet synchronous linear motor is formulated first. Through the analysis of the effect that direct-axis current noise and quadrature-axis current noise have on both direction vibration, it can be declared that the conclusion that longitudinal direction vibration is only related to the quadrature-axis current noise while the normal direction vibration is related to both the quadrature-axis current noise and direct-axis current noise. Then, the simulation test on current loop with a low-pass filter is conducted and the results show that the low-pass filter can not suppress the vibration but makes the vibration more severe. So a vibration suppressing strategy that the proportional gain of direct-axis current controller adapted according to quadrature-axis reference current is proposed. This control strategy can suppress motor vibration by suppressing direct-axis current noise. The experiments results about the effect of K p and T i on normal direction vibration, longitudinal vibration and the position step response show that this strategy suppresses vibration effectively while the motor's motion performance is not affected. The maximum reduction of vibration can be up to 40%. In addition, current test under rated load condition is also conducted and the results show that the control strategy can avoid the conflict between the direct-axis current and the quadrature-axis current under typical load. Adaptive PI control strategy can effectively suppress the flat permanent magnet linear synchronous motor's vibration without affecting the motor's performance.
Masking of sounds by a background noise--cochlear mechanical correlates.
Recio-Spinoso, Alberto; Cooper, Nigel P
2013-05-15
In the search for cochlear correlates of auditory masking by noise stimuli, we recorded basilar membrane (BM) vibrations evoked by either tone or click signals in the presence of varying levels of background noise. The BM vibrations were recorded from basal regions in healthy cochleae of anaesthetized chinchilla and gerbil. Non-linear interactions that could underpin various aspects of psychophysical masking data, including both compression and suppression at the BM level, were observed. The suppression effects, whereby the amplitude of the responses to each stimulus component could be reduced, depended on the relative intensities of the noise and the tones or clicks. Only stimulus components whose frequencies fell inside the non-linear region of the recording site, i.e. around its characteristic frequency (CF), were affected by presentation of the 'suppressing' stimulus (which could be either the tone or the noise). Mutual suppression, the simultaneous reduction of the responses to both tones and noise components, was observed under some conditions, but overall reductions of BM vibration were rarely observed. Moderate- to high-intensity tones suppressed BM responses to low-intensity Gaussian stimuli, including both broadband and narrowband noise. Suppression effects were larger for spectral components of the noise response that were closer to the CF. In this regime, the tone and noise stimuli became the suppressor and probe signals, respectively. This study provides the first detailed observations of cochlear mechanical correlates of the masking effects of noise. Mechanical detection thresholds for tone signals, which were arbitrarily defined using three criteria, are shown to increase in almost direct proportion to the noise level for low and moderately high noise levels, in a manner that resembles the findings of numerous psychophysical observations.
Masking of sounds by a background noise – cochlear mechanical correlates
Recio-Spinoso, Alberto; Cooper, Nigel P
2013-01-01
In the search for cochlear correlates of auditory masking by noise stimuli, we recorded basilar membrane (BM) vibrations evoked by either tone or click signals in the presence of varying levels of background noise. The BM vibrations were recorded from basal regions in healthy cochleae of anaesthetized chinchilla and gerbil. Non-linear interactions that could underpin various aspects of psychophysical masking data, including both compression and suppression at the BM level, were observed. The suppression effects, whereby the amplitude of the responses to each stimulus component could be reduced, depended on the relative intensities of the noise and the tones or clicks. Only stimulus components whose frequencies fell inside the non-linear region of the recording site, i.e. around its characteristic frequency (CF), were affected by presentation of the ‘suppressing’ stimulus (which could be either the tone or the noise). Mutual suppression, the simultaneous reduction of the responses to both tones and noise components, was observed under some conditions, but overall reductions of BM vibration were rarely observed. Moderate- to high-intensity tones suppressed BM responses to low-intensity Gaussian stimuli, including both broadband and narrowband noise. Suppression effects were larger for spectral components of the noise response that were closer to the CF. In this regime, the tone and noise stimuli became the suppressor and probe signals, respectively. This study provides the first detailed observations of cochlear mechanical correlates of the masking effects of noise. Mechanical detection thresholds for tone signals, which were arbitrarily defined using three criteria, are shown to increase in almost direct proportion to the noise level for low and moderately high noise levels, in a manner that resembles the findings of numerous psychophysical observations. PMID:23478137
Thresholding of auditory cortical representation by background noise
Liang, Feixue; Bai, Lin; Tao, Huizhong W.; Zhang, Li I.; Xiao, Zhongju
2014-01-01
It is generally thought that background noise can mask auditory information. However, how the noise specifically transforms neuronal auditory processing in a level-dependent manner remains to be carefully determined. Here, with in vivo loose-patch cell-attached recordings in layer 4 of the rat primary auditory cortex (A1), we systematically examined how continuous wideband noise of different levels affected receptive field properties of individual neurons. We found that the background noise, when above a certain critical/effective level, resulted in an elevation of intensity threshold for tone-evoked responses. This increase of threshold was linearly dependent on the noise intensity above the critical level. As such, the tonal receptive field (TRF) of individual neurons was translated upward as an entirety toward high intensities along the intensity domain. This resulted in preserved preferred characteristic frequency (CF) and the overall shape of TRF, but reduced frequency responding range and an enhanced frequency selectivity for the same stimulus intensity. Such translational effects on intensity threshold were observed in both excitatory and fast-spiking inhibitory neurons, as well as in both monotonic and nonmonotonic (intensity-tuned) A1 neurons. Our results suggest that in a noise background, fundamental auditory representations are modulated through a background level-dependent linear shifting along intensity domain, which is equivalent to reducing stimulus intensity. PMID:25426029
Logging truck noise near nesting northern goshawks
Teryl G. Grubb; Larry L. Pater; David K. Delaney
1998-01-01
We measured noise levels of four logging trucks as the trucks passed within approximately 500 m of two active northern goshawk (Accipiter gentilis) nests on the Kaibab Plateau in northern Arizona in 1997. Neither a brooding adult female nor a lone juvenile exhibited any discernable behavioral response to logging truck noise, which peaked at 53.4 and...
Multicategory nets of single-layer perceptrons: complexity and sample-size issues.
Raudys, Sarunas; Kybartas, Rimantas; Zavadskas, Edmundas Kazimieras
2010-05-01
The standard cost function of multicategory single-layer perceptrons (SLPs) does not minimize the classification error rate. In order to reduce classification error, it is necessary to: 1) refuse the traditional cost function, 2) obtain near to optimal pairwise linear classifiers by specially organized SLP training and optimal stopping, and 3) fuse their decisions properly. To obtain better classification in unbalanced training set situations, we introduce the unbalance correcting term. It was found that fusion based on the Kulback-Leibler (K-L) distance and the Wu-Lin-Weng (WLW) method result in approximately the same performance in situations where sample sizes are relatively small. The explanation for this observation is by theoretically known verity that an excessive minimization of inexact criteria becomes harmful at times. Comprehensive comparative investigations of six real-world pattern recognition (PR) problems demonstrated that employment of SLP-based pairwise classifiers is comparable and as often as not outperforming the linear support vector (SV) classifiers in moderate dimensional situations. The colored noise injection used to design pseudovalidation sets proves to be a powerful tool for facilitating finite sample problems in moderate-dimensional PR tasks.
Nanoscale linear permittivity imaging based on scanning nonlinear dielectric microscopy
NASA Astrophysics Data System (ADS)
Hiranaga, Yoshiomi; Chinone, Norimichi; Cho, Yasuo
2018-05-01
A nanoscale linear permittivity imaging method based on scanning nonlinear dielectric microscopy (SNDM) was developed. The ∂C/∂z-mode SNDM (∂C/∂z-SNDM) technique described herein employs probe-height modulation to suppress disturbances originating from stray capacitance and to improve measurement stability. This method allows local permittivity distributions to be examined with extremely low noise levels (approximately 0.01 aF) by virtue of the highly sensitive probe. A cross-section of a multilayer oxide film was visualized using ∂C/∂z-SNDM as a demonstration, and numerical simulations of the response signals were conducted to gain additional insights. The experimental signal intensities were found to be in a good agreement with the theoretical values, with the exception of the background components, demonstrating that absolute sample permittivity values could be determined. The signal profiles near the boundaries between different dielectrics were calculated using various vibration amplitudes and the boundary transition widths were obtained. The beneficial aspects of higher-harmonic response imaging are discussed herein, taking into account assessments of spatial resolution and quantitation.
Uncertainty based pressure reconstruction from velocity measurement with generalized least squares
NASA Astrophysics Data System (ADS)
Zhang, Jiacheng; Scalo, Carlo; Vlachos, Pavlos
2017-11-01
A method using generalized least squares reconstruction of instantaneous pressure field from velocity measurement and velocity uncertainty is introduced and applied to both planar and volumetric flow data. Pressure gradients are computed on a staggered grid from flow acceleration. The variance-covariance matrix of the pressure gradients is evaluated from the velocity uncertainty by approximating the pressure gradient error to a linear combination of velocity errors. An overdetermined system of linear equations which relates the pressure and the computed pressure gradients is formulated and then solved using generalized least squares with the variance-covariance matrix of the pressure gradients. By comparing the reconstructed pressure field against other methods such as solving the pressure Poisson equation, the omni-directional integration, and the ordinary least squares reconstruction, generalized least squares method is found to be more robust to the noise in velocity measurement. The improvement on pressure result becomes more remarkable when the velocity measurement becomes less accurate and more heteroscedastic. The uncertainty of the reconstructed pressure field is also quantified and compared across the different methods.
Nanoscale linear permittivity imaging based on scanning nonlinear dielectric microscopy.
Hiranaga, Yoshiomi; Chinone, Norimichi; Cho, Yasuo
2018-05-18
A nanoscale linear permittivity imaging method based on scanning nonlinear dielectric microscopy (SNDM) was developed. The ∂C/∂z-mode SNDM (∂C/∂z-SNDM) technique described herein employs probe-height modulation to suppress disturbances originating from stray capacitance and to improve measurement stability. This method allows local permittivity distributions to be examined with extremely low noise levels (approximately 0.01 aF) by virtue of the highly sensitive probe. A cross-section of a multilayer oxide film was visualized using ∂C/∂z-SNDM as a demonstration, and numerical simulations of the response signals were conducted to gain additional insights. The experimental signal intensities were found to be in a good agreement with the theoretical values, with the exception of the background components, demonstrating that absolute sample permittivity values could be determined. The signal profiles near the boundaries between different dielectrics were calculated using various vibration amplitudes and the boundary transition widths were obtained. The beneficial aspects of higher-harmonic response imaging are discussed herein, taking into account assessments of spatial resolution and quantitation.
White-Light Optical Information Processing and Holography.
1984-06-22
Processing, Image Deblurring , Source Encoding, Signal Sampling, Coherence Measurement, Noise Performance, / Pseudocolor Encoding. , ’ ’ * .~ 10.ASS!RACT...o 2.1 Broad Spectral Band Color Image Deblurring .. . 4 2.2 Noise Performance ...... ...... .. . 4 2.3 Pseudocolor Encoding with Three Primary...spectra. This technique is particularly suitable for linear smeared color image deblurring . 2.2 Noise Performance In this period, we have also
Information's role in the estimation of chaotic signals
NASA Astrophysics Data System (ADS)
Drake, Daniel Fred
1998-11-01
Researchers have proposed several methods designed to recover chaotic signals from noise-corrupted observations. While the methods vary, their qualitative performance does not: in low levels of noise all methods effectively recover the underlying signal; in high levels of noise no method can recover the underlying signal to any meaningful degree of accuracy. Of the methods proposed to date, all represent sub-optimal estimators. So: Is the inability to recover the signal in high noise levels simply a consequence of estimator sub-optimality? Or is estimator failure actually a manifestation of some intrinsic property of chaos itself? These questions are answered by deriving an optimal estimator for a class of chaotic systems and noting that it, too, fails in high levels of noise. An exact, closed- form expression for the estimator is obtained for a class of chaotic systems whose signals are solutions to a set of linear (but noncausal) difference equations. The existence of this linear description circumvents the difficulties normally encountered when manipulating the nonlinear (but causal) expressions that govern. chaotic behavior. The reason why even the optimal estimator fails to recover underlying chaotic signals in high levels of noise has its roots in information theory. At such noise levels, the mutual information linking the corrupted observations to the underlying signal is essentially nil, reducing the estimator to a simple guessing strategy based solely on a priori statistics. Entropy, long the common bond between information theory and dynamical systems, is actually one aspect of a far more complete characterization of information sources: the rate distortion function. Determining the rate distortion function associated with the class of chaotic systems considered in this work provides bounds on estimator performance in high levels of noise. Finally, a slight modification of the linear description leads to a method of synthesizing on limited precision platforms ``pseudo-chaotic'' sequences that mimic true chaotic behavior to any finite degree of precision and duration. The use of such a technique in spread-spectrum communications is considered.
Restoration and analysis of amateur movies from the Kennedy assassination
DOE Office of Scientific and Technical Information (OSTI.GOV)
Breedlove, J.R.; Cannon, T.M.; Janney, D.H.
1980-01-01
Much of the evidence concerning the assassination of President Kennedy comes from amateur movies of the presidential motorcade. Two of the most revealing movies are those taken by the photographers Zapruder and Nix. Approximately 180 frames of the Zapruder film clearly show the general relation of persons in the presidential limousine. Many of the frames of interest were blurred by focus problems or by linear motion. The method of cepstral analysis was used to quantitatively measure the blur, followed by maximum a posteriori (MAP) restoration. Descriptions of these methods, complete with before-and-after examples from selected frames are given. The framesmore » were then available for studies of facial expressions, hand motions, etc. Numerous allegations charge that multiple gunmen played a role in an assassination plot. Multispectral analyses, adapted from studies of satellite imagery, show no evidence of an alleged rifle in the Zapruder film. Lastly, frame-averaging is used to reduce the noise in the Nix movie prior to MAP restoration. The restoration of the reduced-noise average frame more clearly shows that at least one of the alleged gunmen is only the light-and-shadow pattern beneath the trees.« less
Li, Jing; Mahmoodi, Alireza; Joseph, Dileepan
2015-10-16
An important class of complementary metal-oxide-semiconductor (CMOS) image sensors are those where pixel responses are monotonic nonlinear functions of light stimuli. This class includes various logarithmic architectures, which are easily capable of wide dynamic range imaging, at video rates, but which are vulnerable to image quality issues. To minimize fixed pattern noise (FPN) and maximize photometric accuracy, pixel responses must be calibrated and corrected due to mismatch and process variation during fabrication. Unlike literature approaches, which employ circuit-based models of varying complexity, this paper introduces a novel approach based on low-degree polynomials. Although each pixel may have a highly nonlinear response, an approximately-linear FPN calibration is possible by exploiting the monotonic nature of imaging. Moreover, FPN correction requires only arithmetic, and an optimal fixed-point implementation is readily derived, subject to a user-specified number of bits per pixel. Using a monotonic spline, involving cubic polynomials, photometric calibration is also possible without a circuit-based model, and fixed-point photometric correction requires only a look-up table. The approach is experimentally validated with a logarithmic CMOS image sensor and is compared to a leading approach from the literature. The novel approach proves effective and efficient.
Signatures of filamentary superconductivity in antiferromagnetic BaFe 2As 2 single crystals
Moseley, D. A.; Yates, K. A.; Branford, W. R.; ...
2015-08-24
In this paper, we present ac susceptibility and magnetotransport measurements on aged single crystals of the ferropnictide parent compound, BaFe 2As 2 with a paramagnetic-to-antiferromagnetic transition temperature of 134 K. The ac susceptibility shows the clear onset of a partial diamagnetic response with an onset temperature, commensurate with a subtle downturn in resistivity at approximately 20 K. Below 20 K the magnetotransport shows in-plane anisotropy, magnetic-field history dependence and a hysteretic signature. Above 20 K the crystals show the widely reported high-field linear magnetoresistance. An enhanced noise signature in ac susceptibility is observed above 20 K, which varies in character with amplitude and frequency of the ac signal. The hysteresis in magnetoresistance and the observed sensitivity of the superconducting phase to the amplitude of the ac signal are indicative characteristics of granular or weakly linked filamentary superconductivity. Furthermore, these features taken together with the observed noise signature abovemore » $$T_{\\mathrm{c}}$$ suggests a link between the formation of the superconducting filamentary phase and the freezing of antiphase domain walls, known to exist in these materials.« less
An embedded system for face classification in infrared video using sparse representation
NASA Astrophysics Data System (ADS)
Saavedra M., Antonio; Pezoa, Jorge E.; Zarkesh-Ha, Payman; Figueroa, Miguel
2017-09-01
We propose a platform for robust face recognition in Infrared (IR) images using Compressive Sensing (CS). In line with CS theory, the classification problem is solved using a sparse representation framework, where test images are modeled by means of a linear combination of the training set. Because the training set constitutes an over-complete dictionary, we identify new images by finding their sparsest representation based on the training set, using standard l1-minimization algorithms. Unlike conventional face-recognition algorithms, we feature extraction is performed using random projections with a precomputed binary matrix, as proposed in the CS literature. This random sampling reduces the effects of noise and occlusions such as facial hair, eyeglasses, and disguises, which are notoriously challenging in IR images. Thus, the performance of our framework is robust to these noise and occlusion factors, achieving an average accuracy of approximately 90% when the UCHThermalFace database is used for training and testing purposes. We implemented our framework on a high-performance embedded digital system, where the computation of the sparse representation of IR images was performed by a dedicated hardware using a deeply pipelined architecture on an Field-Programmable Gate Array (FPGA).
Towards a better understanding of helicopter external noise
NASA Astrophysics Data System (ADS)
Damongeot, A.; Dambra, F.; Masure, B.
The problem of helicopter external noise generation is studied taking into consideration simultaneously the multiple noise sources: rotor rotational-, rotor broadband -, and engine noise. The main data are obtained during flight tests of the rather quiet AS 332 Super Puma. The flight procedures settled by ICAO for noise regulations are used: horizontal flyover at 90 percent of the maximum speed, approach at minimum power velocity, take-off at best rate of climb. Noise source levels are assessed through narrow band analysis of ground microphone recordings, ground measurements of engine noise and theoretical means. With the perceived noise level unit used throughout the study, relative magnitude of noise sources is shown to be different from that obtained with linear noise unit. A parametric study of the influence of some helicopter parameters on external noise has shown that thickness-tapered, chord-tapered, and swept-back blade tips are good means to reduce the overall noise level in flyover and approach.
Robotic magnetic mapping with the Kapvik planetary micro-rover
NASA Astrophysics Data System (ADS)
Hay, A.; Samson, C.
2018-07-01
Geomagnetic data gathering by micro-rovers is gaining momentum both for future planetary exploration missions and for terrestrial applications in extreme environments. This paper presents research into the integration of a planetary micro-rover with a potassium total-field magnetometer. The 40 kg Kapvik micro-rover is an ideal platform due to an aluminium construction and a rocker-bogie mobility system, which provides good manoeuvrability and terrainability. A light-weight GSMP 35U (uninhabited aerial vehicle) magnetometer, comprised of a 0.65 kg sensor and 0.63 kg electronics module, was mounted to the chassis via a custom 1.21 m composite boom. The boom dimensions were optimized to be an effective compromise between noise mitigation and mechanical practicality. An analysis using the fourth difference method was performed estimating the magnetic noise envelope at +/-0.03 nT at 10 Hz sampling frequency from the integrated systems during robotic operations. A robotic magnetic survey captured the total magnetic intensity along three parallel 40 m long lines and a perpendicular 15 m long tie line over the course of 3.75 h. The total magnetic intensity data were corrected for diurnal variations, levelled by linear interpolation of tie-line intersection points, corrected for a regional gradient, and then interpolated using Delaunay triangulation to lead a residual magnetic intensity map. This map exhibited an anomalous linear feature corresponding to a magnetic dipole 650 nT in amplitude. This feature coincides with a storm sewer buried approximately 2 m in the subsurface. This work provides benchmark methodologies and data to guide future integration of magnetometers on board planetary micro-rovers.
Computer program to predict aircraft noise levels
NASA Technical Reports Server (NTRS)
Clark, B. J.
1981-01-01
Methods developed at the NASA Lewis Research Center for predicting the noise contributions from various aircraft noise sources were programmed to predict aircraft noise levels either in flight or in ground tests. The noise sources include fan inlet and exhaust, jet, flap (for powered lift), core (combustor), turbine, and airframe. Noise propagation corrections are available for atmospheric attenuation, ground reflections, extra ground attenuation, and shielding. Outputs can include spectra, overall sound pressure level, perceived noise level, tone-weighted perceived noise level, and effective perceived noise level at locations specified by the user. Footprint contour coordinates and approximate footprint areas can also be calculated. Inputs and outputs can be in either System International or U.S. customary units. The subroutines for each noise source and propagation correction are described. A complete listing is given.
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.
Origins of 1/f noise in nanostructure inclusion polymorphous silicon films
2011-01-01
In this article, we report that the origins of 1/f noise in pm-Si:H film resistors are inhomogeneity and defective structure. The results obtained are consistent with Hooge's formula, where the noise parameter, αH, is independent of doping ratio. The 1/f noise power spectral density and noise parameter αH are proportional to the squared value of temperature coefficient of resistance (TCR). The resistivity and TCR of pm-Si:H film resistor were obtained through linear current-voltage measurement. The 1/f noise, measured by a custom-built noise spectroscopy system, shows that the power spectral density is a function of both doping ratio and temperature. PMID:21711802
Comparison of two weighted integration models for the cueing task: linear and likelihood
NASA Technical Reports Server (NTRS)
Shimozaki, Steven S.; Eckstein, Miguel P.; Abbey, Craig K.
2003-01-01
In a task in which the observer must detect a signal at two locations, presenting a precue that predicts the location of a signal leads to improved performance with a valid cue (signal location matches the cue), compared to an invalid cue (signal location does not match the cue). The cue validity effect has often been explained with a limited capacity attentional mechanism improving the perceptual quality at the cued location. Alternatively, the cueing effect can also be explained by unlimited capacity models that assume a weighted combination of noisy responses across the two locations. We compare two weighted integration models, a linear model and a sum of weighted likelihoods model based on a Bayesian observer. While qualitatively these models are similar, quantitatively they predict different cue validity effects as the signal-to-noise ratios (SNR) increase. To test these models, 3 observers performed in a cued discrimination task of Gaussian targets with an 80% valid precue across a broad range of SNR's. Analysis of a limited capacity attentional switching model was also included and rejected. The sum of weighted likelihoods model best described the psychophysical results, suggesting that human observers approximate a weighted combination of likelihoods, and not a weighted linear combination.
Empirical Models for the Shielding and Reflection of Jet Mixing Noise by a Surface
NASA Technical Reports Server (NTRS)
Brown, Cliff
2015-01-01
Empirical models for the shielding and refection of jet mixing noise by a nearby surface are described and the resulting models evaluated. The flow variables are used to non-dimensionalize the surface position variables, reducing the variable space and producing models that are linear function of non-dimensional surface position and logarithmic in Strouhal frequency. A separate set of coefficients are determined at each observer angle in the dataset and linear interpolation is used to for the intermediate observer angles. The shielding and rejection models are then combined with existing empirical models for the jet mixing and jet-surface interaction noise sources to produce predicted spectra for a jet operating near a surface. These predictions are then evaluated against experimental data.
Empirical Models for the Shielding and Reflection of Jet Mixing Noise by a Surface
NASA Technical Reports Server (NTRS)
Brown, Clifford A.
2016-01-01
Empirical models for the shielding and reflection of jet mixing noise by a nearby surface are described and the resulting models evaluated. The flow variables are used to non-dimensionalize the surface position variables, reducing the variable space and producing models that are linear function of non-dimensional surface position and logarithmic in Strouhal frequency. A separate set of coefficients are determined at each observer angle in the dataset and linear interpolation is used to for the intermediate observer angles. The shielding and reflection models are then combined with existing empirical models for the jet mixing and jet-surface interaction noise sources to produce predicted spectra for a jet operating near a surface. These predictions are then evaluated against experimental data.
Critical phenomena in active matter
NASA Astrophysics Data System (ADS)
Paoluzzi, M.; Maggi, C.; Marini Bettolo Marconi, U.; Gnan, N.
2016-11-01
We investigate the effect of self-propulsion on a mean-field order-disorder transition. Starting from a φ4 scalar field theory subject to an exponentially correlated noise, we exploit the unified colored-noise approximation to map the nonequilibrium active dynamics onto an effective equilibrium one. This allows us to follow the evolution of the second-order critical point as a function of the noise parameters: the correlation time τ and the noise strength D . Our results suggest that the universality class of the model remains unchanged. We also estimate the effect of Gaussian fluctuations on the mean-field approximation finding an Ornstein-Zernike-like expression for the static structure factor at long wavelengths. Finally, to assess the validity of our predictions, we compare the mean-field theoretical results with numerical simulations of active Lennard-Jones particles in two and three dimensions, finding good qualitative agreement at small τ values.
Effects of aircraft noises on the sleep of women
NASA Technical Reports Server (NTRS)
Lukas, J. S.; Dobbs, M. E.
1972-01-01
The electroencephalographic and behavioral responses during sleep of eight women subjects, aged 29 to 49 years, to subsonic jet flyover noise and simulated sonic booms were tested over 14 consecutive nights. Stimulus intensities were 101, 113, and 119 PNdB (as if measured out-of-doors) for the subsonic jet flyover and 0.67, 2.50, and 5.0 psf (as if measured out-of-doors) for the simulated sonic booms. It was found that the women were awakened, on the average, by approximately 42 percent of the flyover noises and by approximately 15 percent of the simulated sonic booms. Comparison of the results of this study with those of a similar study using men as subjects revealed that women were awakened more frequently by the subsonic jet flyover noise then were the men, while men were awakened more frequently by the simulated sonic boom.
NASA Astrophysics Data System (ADS)
Riah, Zoheir; Sommet, Raphael; Nallatamby, Jean C.; Prigent, Michel; Obregon, Juan
2004-05-01
We present in this paper a set of coherent tools for noise characterization and physics-based analysis of noise in semiconductor devices. This noise toolbox relies on a low frequency noise measurement setup with special high current capabilities thanks to an accurate and original calibration. It relies also on a simulation tool based on the drift diffusion equations and the linear perturbation theory, associated with the Green's function technique. This physics-based noise simulator has been implemented successfully in the Scilab environment and is specifically dedicated to HBTs. Some results are given and compared to those existing in the literature.
Noise characteristics of passive components for phased array applications
NASA Technical Reports Server (NTRS)
Sonmez, M. Kemal; Trew, Robert J.
1991-01-01
The results of a comparative study on noise characteristics of basic power combining/dividing and phase shifting schemes are presented. The theoretical basics of thermal noise in a passive linear multiport are discussed. A new formalism is presented to describe the noise behavior of the passive circuits, and it is shown that the fundamental results are conveniently achieved using this description. The results of analyses concerning the noise behavior of basic power combining/dividing structures (the Wilkinson combiner, 90 deg hybrid coupler, hybrid ring coupler, and the Lange coupler) are presented. Three types of PIN-diode switch phase shifters are analyzed in terms of noise performance.
NASA Astrophysics Data System (ADS)
Saha, Surajit; Ghosh, Manas
2016-02-01
We perform a rigorous analysis of the profiles of a few diagonal and off-diagonal components of linear ( α xx , α yy , α xy , and α yx ), first nonlinear ( β xxx , β yyy , β xyy , and β yxx ), and second nonlinear ( γ xxxx , γ yyyy , γ xxyy , and γ yyxx ) polarizabilities of quantum dots exposed to an external pulsed field. Simultaneous presence of multiplicative white noise has also been taken into account. The quantum dot contains a dopant represented by a Gaussian potential. The number of pulse and the dopant location have been found to fabricate the said profiles through their interplay. Moreover, a variation in the noise strength also contributes evidently in designing the profiles of above polarizability components. In general, the off-diagonal components have been found to be somewhat more responsive to a variation of noise strength. However, we have found some exception to the above fact for the off-diagonal β yxx component. The study projects some pathways of achieving stable, enhanced, and often maximized output of linear and nonlinear polarizabilities of doped quantum dots driven by multiplicative noise.
Resonant activation in piecewise linear asymmetric potentials.
Fiasconaro, Alessandro; Spagnolo, Bernardo
2011-04-01
This work analyzes numerically the role played by the asymmetry of a piecewise linear potential, in the presence of both a Gaussian white noise and a dichotomous noise, on the resonant activation phenomenon. The features of the asymmetry of the potential barrier arise by investigating the stochastic transitions far behind the potential maximum, from the initial well to the bottom of the adjacent potential well. Because of the asymmetry of the potential profile together with the random external force uniform in space, we find, for the different asymmetries: (1) an inversion of the curves of the mean first passage time in the resonant region of the correlation time τ of the dichotomous noise, for low thermal noise intensities; (2) a maximum of the mean velocity of the Brownian particle as a function of τ; and (3) an inversion of the curves of the mean velocity and a very weak current reversal in the miniratchet system obtained with the asymmetrical potential profiles investigated. An inversion of the mean first passage time curves is also observed by varying the amplitude of the dichotomous noise, behavior confirmed by recent experiments. ©2011 American Physical Society
Deep Cryogenic Low Power 24 Bits Analog to Digital Converter with Active Reverse Cryostat
NASA Astrophysics Data System (ADS)
Turqueti, Marcos; Prestemon, Soren; Albright, Robert
LBNL is developing an innovative data acquisition module for superconductive magnets where the front-end electronics and digitizer resides inside the cryostat. This electronic package allows conventional electronic technologies such as enhanced metal-oxide-semiconductor to work inside cryostats at temperatures as low as 4.2 K. This is achieved by careful management of heat inside the module that keeps the electronic envelop at approximately 85 K. This approach avoids all the difficulties that arise from changes in carrier mobility that occur in semiconductors at deep cryogenic temperatures. There are several advantages in utilizing this system. A significant reduction in electrical noise from signals captured inside the cryostat occurs due to the low temperature that the electronics is immersed in, reducing the thermal noise. The shorter distance that signals are transmitted before digitalization reduces pickup and cross-talk between channels. This improved performance in signal-to-noise rate by itself is a significant advantage. Another important advantage is the simplification of the feedthrough interface on the cryostat head. Data coming out of the cryostat is digital and serial, dramatically reducing the number of lines going through the cryostat feedthrough interface. It is important to notice that all lines coming out of the cryostat are digital and low voltage, reducing the possibility of electric breakdown inside the cryostat. This paper will explain in details the architecture and inner workings of this data acquisition system. It will also provide the performance of the analog to digital converter when the system is immersed in liquid helium, and in liquid nitrogen. Parameters such as power dissipation, integral non-linearity, effective number of bits, signal-to-noise and distortion, will be presented for both temperatures.
Deep Cryogenic Low Power 24 Bits Analog to Digital Converter with Active Reverse Cryostat
Turqueti, Marcos; Prestemon, Soren; Albright, Robert
2015-07-15
LBNL is developing an innovative data acquisition module for superconductive magnets where the front-end electronics and digitizer resides inside the cryostat. This electronic package allows conventional electronic technologies such as enhanced metal–oxide–semiconductor to work inside cryostats at temperatures as low as 4.2 K. This is achieved by careful management of heat inside the module that keeps the electronic envelop at approximately 85 K. This approach avoids all the difficulties that arise from changes in carrier mobility that occur in semiconductors at deep cryogenic temperatures. There are several advantages in utilizing this system. A significant reduction in electrical noise from signalsmore » captured inside the cryostat occurs due to the low temperature that the electronics is immersed in, reducing the thermal noise. The shorter distance that signals are transmitted before digitalization reduces pickup and cross-talk between channels. This improved performance in signal-to-noise rate by itself is a significant advantage. Another important advantage is the simplification of the feedthrough interface on the cryostat head. Data coming out of the cryostat is digital and serial, dramatically reducing the number of lines going through the cryostat feedthrough interface. It is important to notice that all lines coming out of the cryostat are digital and low voltage, reducing the possibility of electric breakdown inside the cryostat. This paper will explain in details the architecture and inner workings of this data acquisition system. It will also provide the performance of the analog to digital converter when the system is immersed in liquid helium, and in liquid nitrogen. Parameters such as power dissipation, integral non-linearity, effective number of bits, signal-to-noise and distortion, will be presented for both temperatures.« less
NASA Astrophysics Data System (ADS)
Ahmed, S. A.; Hassebo, Y. Y.; Gross, B.; Oo, M.; Moshary, F.
2006-09-01
We examine the potential, range of application, and limiting factors of a polarization selection technique, recently devised by us, which takes advantage of naturally occurring polarization properties of scattered sky light to minimize the detected sky background signal and which can be used in conjunction with linearly polarized elastic backscatter lidars to maximize lidar receiver SNR. In this approach, a polarization selective lidar receiver is aligned to minimize detected skylight, while the polarization of the transmitted lidar signal is rotated to maintain maximum lidar backscatter signal throughput to the receiver detector, consequently maximizing detected signal to noise ratio. Results presented include lidar elastic backscatter measurements, at 532 nm which show as much as a factor of √10 improvement in signal-to-noise ratio over conventional un-polarized schemes. For vertically pointing lidars, the largest improvements are limited to symmetric early morning and late afternoon hours. For non-vertical scanning lidars, significant improvements are achievable over much more extended time periods, depending on the specific angle between the lidar and solar axes. A theoretical model that simulates the background skylight within the single scattering approximation showed good agreement with measured SNR improvement factors. Diurnally asymmetric improvement factors, sometimes observed, are explained by measured increases in PWV and subsequent modification of aerosol optical depth by dehydration from morning to afternoon. Finally, since the polarization axis follows the solar azimuth angle even for high aerosol loading, as demonstrated using radiative transfer simulations, it is possible to conceive automation of the technique. In addition, it is shown that while multiple scattering reduces the SNR improvement, the orientation of the minimum noise state remains the same.
Backside illuminated CMOS-TDI line scanner for space applications
NASA Astrophysics Data System (ADS)
Cohen, O.; Ben-Ari, N.; Nevo, I.; Shiloah, N.; Zohar, G.; Kahanov, E.; Brumer, M.; Gershon, G.; Ofer, O.
2017-09-01
A new multi-spectral line scanner CMOS image sensor is reported. The backside illuminated (BSI) image sensor was designed for continuous scanning Low Earth Orbit (LEO) space applications including A custom high quality CMOS Active Pixels, Time Delayed Integration (TDI) mechanism that increases the SNR, 2-phase exposure mechanism that increases the dynamic Modulation Transfer Function (MTF), very low power internal Analog to Digital Converters (ADC) with resolution of 12 bit per pixel and on chip controller. The sensor has 4 independent arrays of pixels where each array is arranged in 2600 TDI columns with controllable TDI depth from 8 up to 64 TDI levels. A multispectral optical filter with specific spectral response per array is assembled at the package level. In this paper we briefly describe the sensor design and present some electrical and electro-optical recent measurements of the first prototypes including high Quantum Efficiency (QE), high MTF, wide range selectable Full Well Capacity (FWC), excellent linearity of approximately 1.3% in a signal range of 5-85% and approximately 1.75% in a signal range of 2-95% out of the signal span, readout noise of approximately 95 electrons with 64 TDI levels, negligible dark current and power consumption of less than 1.5W total for 4 bands sensor at all operation conditions .
Implications of Pulser Voltage Ripple
DOE Office of Scientific and Technical Information (OSTI.GOV)
Barnard, J J
In a recent set of measurements obtained by G. Kamin, W. Manning, A. Molvik, and J. Sullivan, the voltage waveform of the diode pulser had a ripple of approximately {+-}1.3% of the 65 kV flattop voltage, and the beam current had a larger corresponding ripple of approximately {+-}8.4% of the 1.5 mA average current at the location of the second Faraday cup, approximately 1.9 m downstream from the ion source. The period of the ripple was about 1 {mu}s. It was initially unclear whether this large current ripple was in fact a true measurement of the current or a spuriousmore » measurement of noise produced by the pulser electronics. The purpose of this note is to provide simulations which closely match the experimental results and thereby corroborate the physical nature of those measurements, and to provide predictions of the amplitude of the current ripples as they propagate to the end of linear transport section. Additionally analytic estimates are obtained which lend some insight into the nature of the current fluctuations and to provide an estimate of what the maximum amplitude of the current fluctuations are expected to be, and conversely what initial ripple in the voltage source is allowed, given a smaller acceptable tolerance on the line charge density.« less
An implementation problem for boson fields and quantum Girsanov transform
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ji, Un Cig, E-mail: uncigji@chungbuk.ac.kr; Obata, Nobuaki, E-mail: obata@math.is.tohoku.ac.jp
2016-08-15
We study an implementation problem for quadratic functions of annihilation and creation operators on a boson field in terms of quantum white noise calculus. The implementation problem is shown to be equivalent to a linear differential equation for white noise operators containing quantum white noise derivatives. The solution is explicitly obtained and turns out to form a class of white noise operators including generalized Fourier–Gauss and Fourier–Mehler transforms, Bogoliubov transform, and a quantum extension of the Girsanov transform.
Interior car noise created by textured pavement surfaces : final report.
DOT National Transportation Integrated Search
1975-01-01
Because of widespread concern about the effect of textured pavement surfaces on interior car noise, sound pressure levels (SPL) were measured inside a test vehicle as it traversed 21 pavements with various textures. A linear regression analysis run o...
Adikaram, K K L B; Hussein, M A; Effenberger, M; Becker, T
2015-01-01
Data processing requires a robust linear fit identification method. In this paper, we introduce a non-parametric robust linear fit identification method for time series. The method uses an indicator 2/n to identify linear fit, where n is number of terms in a series. The ratio Rmax of amax - amin and Sn - amin*n and that of Rmin of amax - amin and amax*n - Sn are always equal to 2/n, where amax is the maximum element, amin is the minimum element and Sn is the sum of all elements. If any series expected to follow y = c consists of data that do not agree with y = c form, Rmax > 2/n and Rmin > 2/n imply that the maximum and minimum elements, respectively, do not agree with linear fit. We define threshold values for outliers and noise detection as 2/n * (1 + k1) and 2/n * (1 + k2), respectively, where k1 > k2 and 0 ≤ k1 ≤ n/2 - 1. Given this relation and transformation technique, which transforms data into the form y = c, we show that removing all data that do not agree with linear fit is possible. Furthermore, the method is independent of the number of data points, missing data, removed data points and nature of distribution (Gaussian or non-Gaussian) of outliers, noise and clean data. These are major advantages over the existing linear fit methods. Since having a perfect linear relation between two variables in the real world is impossible, we used artificial data sets with extreme conditions to verify the method. The method detects the correct linear fit when the percentage of data agreeing with linear fit is less than 50%, and the deviation of data that do not agree with linear fit is very small, of the order of ±10-4%. The method results in incorrect detections only when numerical accuracy is insufficient in the calculation process.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hu, Y; Rottmann, J; Myronakis, M
2016-06-15
Purpose: The purpose of this study was to validate the use of a cascaded linear system model for MV cone-beam CT (CBCT) using a multi-layer (MLI) electronic portal imaging device (EPID) and provide experimental insight into image formation. A validated 3D model provides insight into salient factors affecting reconstructed image quality, allowing potential for optimizing detector design for CBCT applications. Methods: A cascaded linear system model was developed to investigate the potential improvement in reconstructed image quality for MV CBCT using an MLI EPID. Inputs to the three-dimensional (3D) model include projection space MTF and NPS. Experimental validation was performedmore » on a prototype MLI detector installed on the portal imaging arm of a Varian TrueBeam radiotherapy system. CBCT scans of up to 898 projections over 360 degrees were acquired at exposures of 16 and 64 MU. Image volumes were reconstructed using a Feldkamp-type (FDK) filtered backprojection (FBP) algorithm. Flat field images and scans of a Catphan model 604 phantom were acquired. The effect of 2×2 and 4×4 detector binning was also examined. Results: Using projection flat fields as an input, examination of the modeled and measured NPS in the axial plane exhibits good agreement. Binning projection images was shown to improve axial slice SDNR by a factor of approximately 1.4. This improvement is largely driven by a decrease in image noise of roughly 20%. However, this effect is accompanied by a subsequent loss in image resolution. Conclusion: The measured axial NPS shows good agreement with the theoretical calculation using a linear system model. Binning of projection images improves SNR of large objects on the Catphan phantom by decreasing noise. Specific imaging tasks will dictate the implementation image binning to two-dimensional projection images. The project was partially supported by a grant from Varian Medical Systems, Inc. and grant No. R01CA188446-01 from the National Cancer Institute.« less
Self-Nulling Lock-in Detection Electronics for Capacitance Probe Electrometer
NASA Technical Reports Server (NTRS)
Blaes, Brent R.; Schaefer, Rembrandt T.
2012-01-01
A multi-channel electrometer voltmeter that employs self-nulling lock-in detection electronics in conjunction with a mechanical resonator with noncontact voltage sensing electrodes has been developed for space-based measurement of an Internal Electrostatic Discharge Monitor (IESDM). The IESDM is new sensor technology targeted for integration into a Space Environmental Monitor (SEM) subsystem used for the characterization and monitoring of deep dielectric charging on spacecraft. Use of an AC-coupled lock-in amplifier with closed-loop sense-signal nulling via generation of an active guard-driving feedback voltage provides the resolution, accuracy, linearity and stability needed for long-term space-based measurement of the IESDM. This implementation relies on adjusting the feedback voltage to drive the sense current received from the resonator s variable-capacitance-probe voltage transducer to approximately zero, as limited by the signal-to-noise performance of the loop electronics. The magnitude of the sense current is proportional to the difference between the input voltage being measured and the feedback voltage, which matches the input voltage when the sense current is zero. High signal-to-noise-ratio (SNR) is achieved by synchronous detection of the sense signal using the correlated reference signal derived from the oscillator circuit that drives the mechanical resonator. The magnitude of the feedback voltage, while the loop is in a settled state with essentially zero sense current, is an accurate estimate of the input voltage being measured. This technique has many beneficial attributes including immunity to drift, high linearity, high SNR from synchronous detection of a single-frequency carrier selected to avoid potentially noisy 1/f low-frequency spectrum of the signal-chain electronics, and high accuracy provided through the benefits of a driven shield encasing the capacitance- probe transducer and guarded input triaxial lead-in. Measurements obtained from a 2- channel prototype electrometer have demonstrated good accuracy (|error| < 0.2 V) and high stability. Twenty-four-hour tests have been performed with virtually no drift. Additionally, 5,500 repeated one-second measurements of 100 V input were shown to be approximately normally distributed with a standard deviation of 140 mV.
NASA Astrophysics Data System (ADS)
Soares, Edward J.; Gifford, Howard C.; Glick, Stephen J.
2003-05-01
We investigated the estimation of the ensemble channelized Hotelling observer (CHO) signal-to-noise ratio (SNR) for ordered-subset (OS) image reconstruction using noisy projection data. Previously, we computed the ensemble CHO SNR using a method for approximating the channelized covariance of OS reconstruction, which requires knowledge of the noise-free projection data. Here, we use a "plug-in" approach, in which noisy data is used in place of the noise-free data in the aforementioned channelized covariance approximation. Additionally, we evaluated the use of smoothing of the noisy projections before use in the covariance approximation. Additionally, we evaluated the use of smoothing of the noisy projections before use in the covariance calculation. The task was detection of a 10% contrast Gaussian signal within a slice of the MCAT phantom. Simulated projections of the MCAT phantom were scaled and Poisson noise was added to create 100 noisy signal-absent data sets. Simulated projections of the scaled signal were then added to the noisy background projections to create 100 noisy signal-present data set. These noisy data sets were then used to generate 100 estimates of the ensemble CHO SNR for reconstructions at various iterates. For comparison purposes, the same calculation was repeated with the noise-free data. The results, reported as plots of the average CHO SNR generated in this fashion, along with 95% confidence intervals, demonstrate that this approach works very well, and would allow optimization of imaging systems and reconstruction methods using a more accurate object model (i.e., real patient data).
1985-01-01
Noise analysis of the Na+ channels of the apical membranes of frog skin bathed symmetrically in a Cl-HCO3 Ringer solution was done with amiloride and CGS 4270. Tissues were studied in their control states and after inhibition of transepithelial Na+ transport (Isc) by addition of quinine or quinidine to the apical solution. A critical examination of the amiloride-induced noise indicated that the single channel Na+ currents (iNa) were decreased by quinine and quinidine, probably because of depolarization of apical membrane voltage. Despite considerable statistical uncertainty in the methods of estimation of the Na+ channel density with amiloride-induced noise (NA, see text), the striking observation was a large increase of NA with amiloride inhibition of the rate of Na+ entry into the cells. NA was increased to 406% of control, whereas Isc was inhibited to 8.6% of control by 6 microM amiloride. Studies were done also with the Na+ channel blocker CGS 4270. Noise analysis with this compound was advantageous, permitting iCGSNa and NCGS to be measured in individual tissues with a relatively small inhibition of Isc. As with amiloride, inhibition of Isc with CGS 4270 caused large increases of the Na+ channel density (approximately 200% at approximately 35% inhibition of the Isc). Quinine and quinidine caused an approximately 50% increase of Na+ channel density while inhibiting iNa by approximately 60-70%. As inhibition of Na+ entry leads to an increase of Na+ channel density, a mechanism of autoregulation appears to be a major factor in adjusting the apical membrane Na+ permeability of the cells. PMID:2409219
Viking S-band Doppler RMS phase fluctuations used to calibrate the mean 1976 equatorial corona
NASA Technical Reports Server (NTRS)
Berman, A. L.; Wackley, J. A.
1977-01-01
Viking S-band Doppler RMS phase fluctuations (noise) and comparisons of Viking Doppler noise to Viking differenced S-X range measurements are used to construct a mean equatorial electron density model for 1976. Using Pioneer Doppler noise results (at high heliographic latitudes, also from 1976), an equivalent nonequatorial electron density model is approximated.
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.
New methods of data calibration for high power-aperture lidar.
Guan, Sai; Yang, Guotao; Chang, Qihai; Cheng, Xuewu; Yang, Yong; Gong, Shaohua; Wang, Jihong
2013-03-25
For high power-aperture lidar sounding of wide atmospheric dynamic ranges, as in middle-upper atmospheric probing, photomultiplier tubes' (PMT) pulse pile-up effects and signal-induced noise (SIN) complicates the extraction of information from lidar return signal, especially from metal layers' fluorescence signal. Pursuit for sophisticated description of metal layers' characteristics at far range (80~130km) with one PMT of high quantum efficiency (QE) and good SNR, contradicts the requirements for signals of wide linear dynamic range (i.e. from approximate 10(2) to 10(8) counts/s). In this article, Substantial improvements on experimental simulation of Lidar signals affected by PMT are reported to evaluate the PMTs' distortions in our High Power-Aperture Sodium LIDAR system. A new method for pile-up calibration is proposed by taking into account PMT and High Speed Data Acquisition Card as an Integrated Black-Box, as well as a new experimental method for identifying and removing SIN from the raw Lidar signals. Contradiction between the limited linear dynamic range of raw signal (55~80km) and requirements for wider acceptable linearity has been effectively solved, without complicating the current lidar system. Validity of these methods was demonstrated by applying calibrated data to retrieve atmospheric parameters (i.e. atmospheric density, temperature and sodium absolutely number density), in comparison with measurements of TIMED satellite and atmosphere model. Good agreements are obtained between results derived from calibrated signal and reference measurements where differences of atmosphere density, temperature are less than 5% in the stratosphere and less than 10K from 30km to mesosphere, respectively. Additionally, approximate 30% changes are shown in sodium concentration at its peak value. By means of the proposed methods to revert the true signal independent of detectors, authors approach a new balance between maintaining the linearity of adequate signal (20-110km) and guaranteeing good SNR (i.e. 10(4):1 around 90km) without debasing QE, in one single detecting channel. For the first time, PMT in photon-counting mode is independently applied to subtract reliable information of atmospheric parameters with wide acceptable linearity over an altitude range from stratosphere up to lower thermosphere (20-110km).
NASA Astrophysics Data System (ADS)
Hsieh, Scott S.; Pelc, Norbert J.
2014-06-01
Photon counting x-ray detectors (PCXDs) offer several advantages compared to standard energy-integrating x-ray detectors, but also face significant challenges. One key challenge is the high count rates required in CT. At high count rates, PCXDs exhibit count rate loss and show reduced detective quantum efficiency in signal-rich (or high flux) measurements. In order to reduce count rate requirements, a dynamic beam-shaping filter can be used to redistribute flux incident on the patient. We study the piecewise-linear attenuator in conjunction with PCXDs without energy discrimination capabilities. We examined three detector models: the classic nonparalyzable and paralyzable detector models, and a ‘hybrid’ detector model which is a weighted average of the two which approximates an existing, real detector (Taguchi et al 2011 Med. Phys. 38 1089-102 ). We derive analytic expressions for the variance of the CT measurements for these detectors. These expressions are used with raw data estimated from DICOM image files of an abdomen and a thorax to estimate variance in reconstructed images for both the dynamic attenuator and a static beam-shaping (‘bowtie’) filter. By redistributing flux, the dynamic attenuator reduces dose by 40% without increasing peak variance for the ideal detector. For non-ideal PCXDs, the impact of count rate loss is also reduced. The nonparalyzable detector shows little impact from count rate loss, but with the paralyzable model, count rate loss leads to noise streaks that can be controlled with the dynamic attenuator. With the hybrid model, the characteristic count rates required before noise streaks dominate the reconstruction are reduced by a factor of 2 to 3. We conclude that the piecewise-linear attenuator can reduce the count rate requirements of the PCXD in addition to improving dose efficiency. The magnitude of this reduction depends on the detector, with paralyzable detectors showing much greater benefit than nonparalyzable detectors.
Comparison of Aircraft Models and Integration Schemes for Interval Management in the TRACON
NASA Technical Reports Server (NTRS)
Neogi, Natasha; Hagen, George E.; Herencia-Zapana, Heber
2012-01-01
Reusable models of common elements for communication, computation, decision and control in air traffic management are necessary in order to enable simulation, analysis and assurance of emergent properties, such as safety and stability, for a given operational concept. Uncertainties due to faults, such as dropped messages, along with non-linearities and sensor noise are an integral part of these models, and impact emergent system behavior. Flight control algorithms designed using a linearized version of the flight mechanics will exhibit error due to model uncertainty, and may not be stable outside a neighborhood of the given point of linearization. Moreover, the communication mechanism by which the sensed state of an aircraft is fed back to a flight control system (such as an ADS-B message) impacts the overall system behavior; both due to sensor noise as well as dropped messages (vacant samples). Additionally simulation of the flight controller system can exhibit further numerical instability, due to selection of the integration scheme and approximations made in the flight dynamics. We examine the theoretical and numerical stability of a speed controller under the Euler and Runge-Kutta schemes of integration, for the Maintain phase for a Mid-Term (2035-2045) Interval Management (IM) Operational Concept for descent and landing operations. We model uncertainties in communication due to missed ADS-B messages by vacant samples in the integration schemes, and compare the emergent behavior of the system, in terms of stability, via the boundedness of the final system state. Any bound on the errors incurred by these uncertainties will play an essential part in a composable assurance argument required for real-time, flight-deck guidance and control systems,. Thus, we believe that the creation of reusable models, which possess property guarantees, such as safety and stability, is an innovative and essential requirement to assessing the emergent properties of novel airspace concepts of operation.
Linear response and correlation of a self-propelled particle in the presence of external fields
NASA Astrophysics Data System (ADS)
Caprini, Lorenzo; Marini Bettolo Marconi, Umberto; Vulpiani, Angelo
2018-03-01
We study the non-equilibrium properties of non interacting active Ornstein-Uhlenbeck particles (AOUP) subject to an external nonuniform field using a Fokker-Planck approach with a focus on the linear response and time-correlation functions. In particular, we compare different methods to compute these functions including the unified colored noise approximation (UCNA). The AOUP model, described by the position of the particle and the active force acting on it, is usually mapped into a Markovian process, describing the motion of a fictitious passive particle in terms of its position and velocity, where the effect of the activity is transferred into a position-dependent friction. We show that the form of the response function of the AOUP depends on whether we put the perturbation on the position and keep unperturbed the active force in the original variables or perturb the position and maintain unperturbed the velocity in the transformed variables. Indeed, as a result of the change of variables the perturbation on the position becomes a perturbation both on the position and on the fictitious velocity. We test these predictions by considering the response for three types of convex potentials: quadratic, quartic and double-well potential. Moreover, by comparing the response of the AOUP model with the corresponding response of the UCNA model we conclude that although the stationary properties are fairly well approximated by the UCNA, the non equilibrium properties are not, an effect which is not negligible when the persistence time is large.
VUV Testing of Science Cameras at MSFC: QE Measurement of the CLASP Flight Cameras
NASA Technical Reports Server (NTRS)
Champey, Patrick; Kobayashi, Ken; Winebarger, Amy; Cirtain, Jonathan; Hyde, David; Robertson, Bryan; Beabout, Brent; Beabout, Dyana; Stewart, Mike
2015-01-01
The NASA Marshall Space Flight Center (MSFC) has developed a science camera suitable for sub-orbital missions for observations in the UV, EUV and soft X-ray. Six cameras were built and tested for the Chromospheric Lyman-Alpha Spectro-Polarimeter (CLASP), a joint National Astronomical Observatory of Japan (NAOJ) and MSFC sounding rocket mission. The CLASP camera design includes a frame-transfer e2v CCD57-10 512x512 detector, dual channel analog readout electronics and an internally mounted cold block. At the flight operating temperature of -20 C, the CLASP cameras achieved the low-noise performance requirements (less than or equal to 25 e- read noise and greater than or equal to 10 e-/sec/pix dark current), in addition to maintaining a stable gain of approximately equal to 2.0 e-/DN. The e2v CCD57-10 detectors were coated with Lumogen-E to improve quantum efficiency (QE) at the Lyman- wavelength. A vacuum ultra-violet (VUV) monochromator and a NIST calibrated photodiode were employed to measure the QE of each camera. Four flight-like cameras were tested in a high-vacuum chamber, which was configured to operate several tests intended to verify the QE, gain, read noise, dark current and residual non-linearity of the CCD. We present and discuss the QE measurements performed on the CLASP cameras. We also discuss the high-vacuum system outfitted for testing of UV and EUV science cameras at MSFC.
Computation of output feedback gains for linear stochastic systems using the Zangnill-Powell Method
NASA Technical Reports Server (NTRS)
Kaufman, H.
1975-01-01
Because conventional optimal linear regulator theory results in a controller which requires the capability of measuring and/or estimating the entire state vector, it is of interest to consider procedures for computing controls which are restricted to be linear feedback functions of a lower dimensional output vector and which take into account the presence of measurement noise and process uncertainty. To this effect a stochastic linear model has been developed that accounts for process parameter and initial uncertainty, measurement noise, and a restricted number of measurable outputs. Optimization with respect to the corresponding output feedback gains was then performed for both finite and infinite time performance indices without gradient computation by using Zangwill's modification of a procedure originally proposed by Powell. Results using a seventh order process show the proposed procedures to be very effective.
Role of the nature of noise in the thermal conductance of mechanical systems.
Morgado, Welles A M; Duarte Queirós, Sílvio M
2012-10-01
Focusing on a paradigmatic small system consisting of two coupled damped oscillators, we survey the role of the Lévy-Itô nature of the noise in the thermal conductance. For white noises, we prove that the Lévy-Itô composition (Lebesgue measure) of the noise is irrelevant for the thermal conductance of a nonequilibrium linearly coupled chain, which signals the independence of mechanical and thermodynamical properties. In contrast, for the nonlinearly coupled case, the two types of properties mix and the explicit definition of the noise plays a central role.
A Model for Jet-Surface Interaction Noise Using Physically Realizable Upstream Turbulence Conditions
NASA Technical Reports Server (NTRS)
Afsar, Mohammed Z.; Leib, Stewart J.; Bozak, Richard F.
2016-01-01
This paper is a continuation of previous work in which a generalized Rapid Distortion Theory (RDT) formulation was used to model low-frequency trailing-edge noise. The research was motivated by proposed next-generation aircraft configurations where the exhaust system is tightly integrated with the airframe. Data from recent experiments at NASA on the interaction between high-Reynolds-number subsonic jet flows and an external flat plate showed that the power spectral density (PSD) of the far-field pressure underwent considerable amplification at low frequencies. For example, at the 90deg observation angle, the low-frequency noise could be as much as 10 dB greater than the jet noise itself. In this paper, we present predictions of the noise generated by the interaction of a rectangular jet with the trailing edge of a semi-infinite flat plate. The calculations are based on a formula for the acoustic spectrum of this noise source derived from an exact formal solution of the linearized Euler equations involving (in this case) one arbitrary convected scalar quantity and a Rayleigh equation Green's function. A low-frequency asymptotic approximation for the Green's function based on a two-dimensional mean flow is used in the calculations along with a physically realizable upstream turbulence spectrum, which includes a finite decorrelation region. Numerical predictions of the sound field, based on three-dimensional RANS solutions to determine the mean flow, turbulent kinetic energy and turbulence length and time scales, for a range of subsonic acoustic Mach number jets and nozzle aspect ratios are compared with experimental data. Comparisons of the RANS results with flow data are also presented for selected cases. We find that a finite decorrelation region in the turbulence spectrum increases the low-frequency algebraic decay (the low frequency "roll-off") of the acoustic spectrum with angular frequency thereby producing much closer agreement with noise data for Strouhal numbers less than 0.1. Secondly, the large-aspect-ratio theory is able to predict the low-frequency amplification due to the jet-edge interaction reasonably well, even for moderate aspect ratio nozzles. We show also that the noise predictions for smaller aspect ratio jets can be fine-tuned using the appropriate RANS-based mean flow and turbulence properties.
Tanaka, Tagayasu; Inaba, Ryoichi; Aoyama, Atsuhito
2016-01-01
Objectives: This study investigated the actual situation of noise and low-frequency sounds in firework events and their impact on pyrotechnicians. Methods: Data on firework noise and low-frequency sounds were obtained at a point located approximately 100 m away from the launch site of a firework display held in "A" City in 2013. We obtained the data by continuously measuring and analyzing the equivalent continuous sound level (Leq) and the one-third octave band of the noise and low-frequency sounds emanating from the major firework detonations, and predicted sound levels at the original launch site. Results: Sound levels of 100-115 dB and low-frequency sounds of 100-125 dB were observed at night. The maximum and mean Leq values were 97 and 95 dB, respectively. The launching noise level predicted from the sounds (85 dB) at the noise measurement point was 133 dB. Occupational exposure to noise for pyrotechnicians at the remote operation point (located 20-30 m away from the launch site) was estimated to be below 100 dB. Conclusions: Pyrotechnicians are exposed to very loud noise (>100 dB) at the launch point. We believe that it is necessary to implement measures such as fixing earplugs or earmuffs, posting a warning at the workplace, and executing a remote launching operation to prevent hearing loss caused by occupational exposure of pyrotechnicians to noise. It is predicted that both sound levels and low-frequency sounds would be reduced by approximately 35 dB at the remote operation site. PMID:27725489
Tanaka, Tagayasu; Inaba, Ryoichi; Aoyama, Atsuhito
2016-11-29
This study investigated the actual situation of noise and low-frequency sounds in firework events and their impact on pyrotechnicians. Data on firework noise and low-frequency sounds were obtained at a point located approximately 100 m away from the launch site of a firework display held in "A" City in 2013. We obtained the data by continuously measuring and analyzing the equivalent continuous sound level (Leq) and the one-third octave band of the noise and low-frequency sounds emanating from the major firework detonations, and predicted sound levels at the original launch site. Sound levels of 100-115 dB and low-frequency sounds of 100-125 dB were observed at night. The maximum and mean Leq values were 97 and 95 dB, respectively. The launching noise level predicted from the sounds (85 dB) at the noise measurement point was 133 dB. Occupational exposure to noise for pyrotechnicians at the remote operation point (located 20-30 m away from the launch site) was estimated to be below 100 dB. Pyrotechnicians are exposed to very loud noise (>100 dB) at the launch point. We believe that it is necessary to implement measures such as fixing earplugs or earmuffs, posting a warning at the workplace, and executing a remote launching operation to prevent hearing loss caused by occupational exposure of pyrotechnicians to noise. It is predicted that both sound levels and low-frequency sounds would be reduced by approximately 35 dB at the remote operation site.
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.
Measurement-noise maximum as a signature of a phase transition.
Chen, Zhi; Yu, Clare C
2007-02-02
We propose that a maximum in measurement noise can be used as a signature of a phase transition. As an example, we study the energy and magnetization noise spectra associated with first- and second-order phase transitions by using Monte Carlo simulations of the Ising model and 5-state Potts model in two dimensions. For a finite size system, the total noise power and the low frequency white noise S(f
Internal additive noise effects in stochastic resonance using organic field effect transistor
DOE Office of Scientific and Technical Information (OSTI.GOV)
Suzuki, Yoshiharu; Asakawa, Naoki; Matsubara, Kiyohiko
Stochastic resonance phenomenon was observed in organic field effect transistor using poly(3-hexylthiophene), which enhances performance of signal transmission with application of noise. The enhancement of correlation coefficient between the input and output signals was low, and the variation of correlation coefficient was not remarkable with respect to the intensity of external noise, which was due to the existence of internal additive noise following the nonlinear threshold response. In other words, internal additive noise plays a positive role on the capability of approximately constant signal transmission regardless of noise intensity, which can be said “homeostatic” behavior or “noise robustness” against externalmore » noise. Furthermore, internal additive noise causes emergence of the stochastic resonance effect even on the threshold unit without internal additive noise on which the correlation coefficient usually decreases monotonically.« less
Nagare, Mukund B; Patil, Bhushan D; Holambe, Raghunath S
2017-02-01
B-Mode ultrasound images are degraded by inherent noise called Speckle, which creates a considerable impact on image quality. This noise reduces the accuracy of image analysis and interpretation. Therefore, reduction of speckle noise is an essential task which improves the accuracy of the clinical diagnostics. In this paper, a Multi-directional perfect-reconstruction (PR) filter bank is proposed based on 2-D eigenfilter approach. The proposed method used for the design of two-dimensional (2-D) two-channel linear-phase FIR perfect-reconstruction filter bank. In this method, the fan shaped, diamond shaped and checkerboard shaped filters are designed. The quadratic measure of the error function between the passband and stopband of the filter has been used an objective function. First, the low-pass analysis filter is designed and then the PR condition has been expressed as a set of linear constraints on the corresponding synthesis low-pass filter. Subsequently, the corresponding synthesis filter is designed using the eigenfilter design method with linear constraints. The newly designed 2-D filters are used in translation invariant pyramidal directional filter bank (TIPDFB) for reduction of speckle noise in ultrasound images. The proposed 2-D filters give better symmetry, regularity and frequency selectivity of the filters in comparison to existing design methods. The proposed method is validated on synthetic and real ultrasound data which ensures improvement in the quality of ultrasound images and efficiently suppresses the speckle noise compared to existing methods.
Del Prete, Valeria; Treves, Alessandro
2002-04-01
In a previous paper we have evaluated analytically the mutual information between the firing rates of N independent units and a set of multidimensional continuous and discrete stimuli, for a finite population size and in the limit of large noise. Here, we extend the analysis to the case of two interconnected populations, where input units activate output ones via Gaussian weights and a threshold linear transfer function. We evaluate the information carried by a population of M output units, again about continuous and discrete correlates. The mutual information is evaluated solving saddle-point equations under the assumption of replica symmetry, a method that, by taking into account only the term linear in N of the input information, is equivalent to assuming the noise to be large. Within this limitation, we analyze the dependence of the information on the ratio M/N, on the selectivity of the input units and on the level of the output noise. We show analytically, and confirm numerically, that in the limit of a linear transfer function and of a small ratio between output and input noise, the output information approaches asymptotically the information carried in input. Finally, we show that the information loss in output does not depend much on the structure of the stimulus, whether purely continuous, purely discrete or mixed, but only on the position of the threshold nonlinearity, and on the ratio between input and output noise.
Feasibility study on the least square method for fitting non-Gaussian noise data
NASA Astrophysics Data System (ADS)
Xu, Wei; Chen, Wen; Liang, Yingjie
2018-02-01
This study is to investigate the feasibility of least square method in fitting non-Gaussian noise data. We add different levels of the two typical non-Gaussian noises, Lévy and stretched Gaussian noises, to exact value of the selected functions including linear equations, polynomial and exponential equations, and the maximum absolute and the mean square errors are calculated for the different cases. Lévy and stretched Gaussian distributions have many applications in fractional and fractal calculus. It is observed that the non-Gaussian noises are less accurately fitted than the Gaussian noise, but the stretched Gaussian cases appear to perform better than the Lévy noise cases. It is stressed that the least-squares method is inapplicable to the non-Gaussian noise cases when the noise level is larger than 5%.
Signal-to-noise ratios in coherent soft limiters
NASA Technical Reports Server (NTRS)
Lesh, J. R.
1973-01-01
Expressions for the output signal-to-noise power ratio of a bandpass soft limiter followed by a coherent detection device are presented and discussed. It is found that a significant improvement in the output signal-to-noise ratio at low input SNRs can be achieved by such soft limiters as compared to hard limiters. This indicates that the soft limiter may be of some use in the area of threshold extension. Approximation methods for determining output signal-to-noise spectral densities are also presented.
Planets as background noise sources in free space optical communications
NASA Technical Reports Server (NTRS)
Katz, J.
1986-01-01
Background noise generated by planets is the dominant noise source in most deep space direct detection optical communications systems. Earlier approximate analyses of this problem are based on simplified blackbody calculations and can yield results that may be inaccurate by up to an order of magnitude. Various other factors that need to be taken into consideration, such as the phase angle and the actual spectral dependence of the planet albedo, in order to obtain a more accurate estimate of the noise magnitude are examined.
Spectral Structure Of Phase-Induced Intensity Noise In Recirculating Delay Lines
NASA Astrophysics Data System (ADS)
Tur, M.; Moslehi, B.; Bowers, J. E.; Newton, S. A.; Jackson, K. P.; Goodman, J. W.; Cutler, C. C.; Shaw, H. J.
1983-09-01
The dynamic range of fiber optic signal processors driven by relatively incoherent multimode semiconductor lasers is shown to be severely limited by laser phase-induced noise. It is experimentally demonstrated that while the noise power spectrum of differential length fiber filters is approximately flat, processors with recirculating loops exhibit noise with a periodically structured power spectrum with notches at zero frequency as well as at all other multiples of 1/(loop delay). The experimental results are aug-mented by a theoretical analysis.
NASA Technical Reports Server (NTRS)
Hilton, D. A.; Pegg, R. J.
1974-01-01
Noise measurements under controlled conditions have been made inside and outside of a school building during flyover operations of four different helicopters. The helicopters were operated at a condition considered typical for a police patrol mission. Flyovers were made at an altitude of 500 ft and an airspeed of 45 miles per hour. During these operations acoustic measurements were made inside and outside of the school building with the windows closed and then open. The outside noise measurements during helicopter flyovers indicate that the outside db(A) levels were approximately the same for all test helicopters. For the windows closed case, significant reductions for the inside measured db(A) values were noted for all overflights. These reductions were approximately 20 db(A); similar reductions were noted in other subjective measuring units. The measured internal db(A) levels with the windows open exceeded published classroom noise criteria values; however, for the windows-closed case they are in general agreement with the criteria values.
Design and Development of 256x256 Linear Mode Low-Noise Avalanche Photodiode Arrays
NASA Technical Reports Server (NTRS)
Yuan, Ping; Sudharsanan, Rengarajan; Bai, Xiaogang; Boisvert, Joseph; McDonald, Paul; Chang, James
2011-01-01
A larger format photodiode array is always desirable for many LADAR imaging applications. However, as the array format increases, the laser power or the lens aperture has to increase to maintain the same flux per pixel thus increasing the size, weight and power of the imaging system. In order to avoid this negative impact, it is essential to improve the pixel sensitivity. The sensitivity of a short wavelength infrared linear-mode avalanche photodiode (APD) is a delicate balance of quantum efficiency, usable gain, excess noise factor, capacitance, and dark current of APD as well as the input equivalent noise of the amplifier. By using InA1As as a multiplication layer in an InP-based APD, the ionization coefficient ratio, k, is reduced from 0.40 (lnP) to 0.22, and the excess noise is reduced by about 50%. An additional improvement in excess noise of 25% was achieved by employing an impact-ionization-engineering structure with a k value of 0.15. Compared with the traditional InP structure, about 30% reduction in the noise-equivalent power with the following amplifier can be achieved. Spectrolab demonstrated 30-um mesa APD pixels with a dark current less than 10 nA and a capacitance of 60 fF at gain of 10. APD gain uninformity determines the usable gain of most pixels in an array, which is critical to focal plane array sensitivity. By fine tuning the material growth and device process, a break-down-voltage standard deviation of 0.1 V and gain of 30 on individual pixels were demonstrated in our 256x256 linear-mode APD arrays.
Linear Covariance Analysis and Epoch State Estimators
NASA Technical Reports Server (NTRS)
Markley, F. Landis; Carpenter, J. Russell
2014-01-01
This paper extends in two directions the results of prior work on generalized linear covariance analysis of both batch least-squares and sequential estimators. The first is an improved treatment of process noise in the batch, or epoch state, estimator with an epoch time that may be later than some or all of the measurements in the batch. The second is to account for process noise in specifying the gains in the epoch state estimator. We establish the conditions under which the latter estimator is equivalent to the Kalman filter.
Linear Covariance Analysis and Epoch State Estimators
NASA Technical Reports Server (NTRS)
Markley, F. Landis; Carpenter, J. Russell
2012-01-01
This paper extends in two directions the results of prior work on generalized linear covariance analysis of both batch least-squares and sequential estimators. The first is an improved treatment of process noise in the batch, or epoch state, estimator with an epoch time that may be later than some or all of the measurements in the batch. The second is to account for process noise in specifying the gains in the epoch state estimator. We establish the conditions under which the latter estimator is equivalent to the Kalman filter.
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.
Noise Characteristics of a Four-Jet Impingement Device Inside a Broadband Engine Noise Simulator
NASA Technical Reports Server (NTRS)
Brehm, Christoph; Housman, Jeffrey A.; Kiris, Cetin C.; Hutcheson, Florence V.
2015-01-01
The noise generation mechanisms for four directly impinging supersonic jets are investigated employing implicit large eddy simulations with a higher-order accurate weighted essentially non-oscillatory shock-capturing scheme. Impinging jet devices are often used as an experimental apparatus to emulate a broadband noise source. Although such devices have been used in many experiments, a detailed investigation of the noise generation mechanisms has not been conducted before. Thus, the underlying physical mechanisms that are responsible for the generation of sound waves are not well understood. The flow field is highly complex and contains a wide range of temporal and spatial scales relevant for noise generation. Proper orthogonal decomposition of the flow field is utilized to characterize the unsteady nature of the flow field involving unsteady shock oscillations, large coherent turbulent flow structures, and the sporadic appearance of vortex tubes in the center of the impingement region. The causality method based on Lighthill's acoustic analogy is applied to link fluctuations of flow quantities inside the source region to the acoustic pressure in the far field. It will be demonstrated that the entropy fluctuation term in the Lighthill's stress tensor plays a vital role in the noise generation process. Consequently, the understanding of the noise generation mechanisms is employed to develop a reduced-order linear acoustic model of the four-jet impingement device. Finally, three linear acoustic FJID models are used as broadband noise sources inside an engine nacelle and the acoustic scattering results are validated against far-field acoustic experimental data.
A refinement of the combination equations for evaporation
Milly, P.C.D.
1991-01-01
Most combination equations for evaporation rely on a linear expansion of the saturation vapor-pressure curve around the air temperature. Because the temperature at the surface may differ from this temperature by several degrees, and because the saturation vapor-pressure curve is nonlinear, this approximation leads to a certain degree of error in those evaporation equations. It is possible, however, to introduce higher-order polynomial approximations for the saturation vapor-pressure curve and to derive a family of explicit equations for evaporation, having any desired degree of accuracy. Under the linear approximation, the new family of equations for evaporation reduces, in particular cases, to the combination equations of H. L. Penman (Natural evaporation from open water, bare soil and grass, Proc. R. Soc. London, Ser. A193, 120-145, 1948) and of subsequent workers. Comparison of the linear and quadratic approximations leads to a simple approximate expression for the error associated with the linear case. Equations based on the conventional linear approximation consistently underestimate evaporation, sometimes by a substantial amount. ?? 1991 Kluwer Academic Publishers.
Bonny, Jean Marie; Boespflug-Tanguly, Odile; Zanca, Michel; Renou, Jean Pierre
2003-03-01
A solution for discrete multi-exponential analysis of T(2) relaxation decay curves obtained in current multi-echo imaging protocol conditions is described. We propose a preprocessing step to improve the signal-to-noise ratio and thus lower the signal-to-noise ratio threshold from which a high percentage of true multi-exponential detection is detected. It consists of a multispectral nonlinear edge-preserving filter that takes into account the signal-dependent Rician distribution of noise affecting magnitude MR images. Discrete multi-exponential decomposition, which requires no a priori knowledge, is performed by a non-linear least-squares procedure initialized with estimates obtained from a total least-squares linear prediction algorithm. This approach was validated and optimized experimentally on simulated data sets of normal human brains.
Dichotomous-noise-induced pattern formation in a reaction-diffusion system
NASA Astrophysics Data System (ADS)
Das, Debojyoti; Ray, Deb Shankar
2013-06-01
We consider a generic reaction-diffusion system in which one of the parameters is subjected to dichotomous noise by controlling the flow of one of the reacting species in a continuous-flow-stirred-tank reactor (CSTR) -membrane reactor. The linear stability analysis in an extended phase space is carried out by invoking Furutzu-Novikov procedure for exponentially correlated multiplicative noise to derive the instability condition in the plane of the noise parameters (correlation time and strength of the noise). We demonstrate that depending on the correlation time an optimal strength of noise governs the self-organization. Our theoretical analysis is corroborated by numerical simulations on pattern formation in a chlorine-dioxide-iodine-malonic acid reaction-diffusion system.
Calculation and observation of thermal electrostatic noise in solar wind plasma
NASA Technical Reports Server (NTRS)
Kellogg, P. J.
1981-01-01
Calculations, both approximate algebraic and numerical, have been carried out for the noise due to electrostatic waves incident on a dipole antenna. The noise is calculated both for a thermal equilibrium plasma, and one having several components at different temperatures. The results are compared with measurements from the IMP-6 satellite. In various frequency ranges, the noise power is dominated by Langmuir oscillations, by electron acoustic waves and by ion acoustic waves. The measurements are consistent with all of these, although the ion waves are not definitely observed, due to interference from shot noise.
Radio astronomy ultra-low-noise amplifier for operation at 91 cm wavelength in high RFI environment
NASA Astrophysics Data System (ADS)
Korolev, A. M.; Zakharenko, V. V.; Ulyanov, O. M.
2016-02-01
An ultra-low-noise input amplifier intended for a use in a radio telescope operating at 91 cm wavelength is presented. The amplifier noise temperatures are 12.8 ± 1.5 and 10.0 ± 1.5 K at ambient temperatures of 293 and 263 K respectively. The amplifier does not require cryogenic cooling. It can be quickly put in operation thus shortening losses in the telescope observation time. High linearity of the amplifier (output power at 1 dB gain compression P1dB ≥ 22 dBm, output third order intercept point OIP3 ≥ 37 dBm) enables the telescope operation in highly urbanized and industrialized regions. To obtain low noise characteristics along with high linearity, high-electron-mobility field-effect transistors were used in parallel in the circuit developed. The transistors used in the amplifier are cost-effective and commercially available. The circuit solution is recommended for similar devices working in ultra-high frequency band.
Signal and noise extraction from analog memory elements for neuromorphic computing.
Gong, N; Idé, T; Kim, S; Boybat, I; Sebastian, A; Narayanan, V; Ando, T
2018-05-29
Dense crossbar arrays of non-volatile memory (NVM) can potentially enable massively parallel and highly energy-efficient neuromorphic computing systems. The key requirements for the NVM elements are continuous (analog-like) conductance tuning capability and switching symmetry with acceptable noise levels. However, most NVM devices show non-linear and asymmetric switching behaviors. Such non-linear behaviors render separation of signal and noise extremely difficult with conventional characterization techniques. In this study, we establish a practical methodology based on Gaussian process regression to address this issue. The methodology is agnostic to switching mechanisms and applicable to various NVM devices. We show tradeoff between switching symmetry and signal-to-noise ratio for HfO 2 -based resistive random access memory. Then, we characterize 1000 phase-change memory devices based on Ge 2 Sb 2 Te 5 and separate total variability into device-to-device variability and inherent randomness from individual devices. These results highlight the usefulness of our methodology to realize ideal NVM devices for neuromorphic computing.
Advanced turbo-prop airplane interior noise reduction-source definition
NASA Technical Reports Server (NTRS)
Magliozzi, B.; Brooks, B. M.
1979-01-01
Acoustic pressure amplitudes and phases were measured in model scale on the surface of a rigid semicylinder mounted in an acoustically treated wind tunnel near a prop-fan (an advanced turboprop with many swept blades) model. Operating conditions during the test simulated those of a prop-fan at 0.8 Mach number cruise. Acoustic pressure amplitude and phase contours were defined on the semicylinder surface. Measurements obtained without the semi-cylinder in place were used to establish the magnitude of pressure doubling for an aircraft fuselage located near a prop-fan. Pressure doubling effects were found to be 6dB at 90 deg incidence decreasing to no effect at grazing incidence. Comparisons of measurements with predictions made using a recently developed prop-fan noise prediction theory which includes linear and non-linear source terms showed good agreement in phase and in peak noise amplitude. Predictions of noise amplitude and phase contours, including pressure doubling effects derived from test, are included for a full scale prop-fan installation.
Wavelet-Based Blind Superresolution from Video Sequence and in MRI
2005-12-31
in Fig. 4(e) and (f), respectively. The PSNR- based optimal threshold gives better noise filtering but poor deblurring [see Fig. 4(c) and (e)] while...that ultimately produces the deblurred , noise filtered, superresolved image. Finite support linear shift invariant blurs are reasonable to assume... Deblurred and Noise Filtered HR Image Cameras with different PSFs Figure 1: Multichannel Blind Superresolution Model condition [11] on the zeros of the
Multiple pure tone noise prediction
NASA Astrophysics Data System (ADS)
Han, Fei; Sharma, Anupam; Paliath, Umesh; Shieh, Chingwei
2014-12-01
This paper presents a fully numerical method for predicting multiple pure tones, also known as “Buzzsaw” noise. It consists of three steps that account for noise source generation, nonlinear acoustic propagation with hard as well as lined walls inside the nacelle, and linear acoustic propagation outside the engine. Noise generation is modeled by steady, part-annulus computational fluid dynamics (CFD) simulations. A linear superposition algorithm is used to construct full-annulus shock/pressure pattern just upstream of the fan from part-annulus CFD results. Nonlinear wave propagation is carried out inside the duct using a pseudo-two-dimensional solution of Burgers' equation. Scattering from nacelle lip as well as radiation to farfield is performed using the commercial solver ACTRAN/TM. The proposed prediction process is verified by comparing against full-annulus CFD simulations as well as against static engine test data for a typical high bypass ratio aircraft engine with hardwall as well as lined inlets. Comparisons are drawn against nacelle unsteady pressure transducer measurements at two axial locations as well as against near- and far-field microphone array measurements outside the duct. This is the first fully numerical approach (no experimental or empirical input is required) to predict multiple pure tone noise generation, in-duct propagation and far-field radiation. It uses measured blade coordinates to calculate MPT noise.
LLSURE: local linear SURE-based edge-preserving image filtering.
Qiu, Tianshuang; Wang, Aiqi; Yu, Nannan; Song, Aimin
2013-01-01
In this paper, we propose a novel approach for performing high-quality edge-preserving image filtering. Based on a local linear model and using the principle of Stein's unbiased risk estimate as an estimator for the mean squared error from the noisy image only, we derive a simple explicit image filter which can filter out noise while preserving edges and fine-scale details. Moreover, this filter has a fast and exact linear-time algorithm whose computational complexity is independent of the filtering kernel size; thus, it can be applied to real time image processing tasks. The experimental results demonstrate the effectiveness of the new filter for various computer vision applications, including noise reduction, detail smoothing and enhancement, high dynamic range compression, and flash/no-flash denoising.
A multiscale filter for noise reduction of low-dose cone beam projections.
Yao, Weiguang; Farr, Jonathan B
2015-08-21
The Poisson or compound Poisson process governs the randomness of photon fluence in cone beam computed tomography (CBCT) imaging systems. The probability density function depends on the mean (noiseless) of the fluence at a certain detector. This dependence indicates the natural requirement of multiscale filters to smooth noise while preserving structures of the imaged object on the low-dose cone beam projection. In this work, we used a Gaussian filter, exp(-x2/2σ(2)(f)) as the multiscale filter to de-noise the low-dose cone beam projections. We analytically obtained the expression of σ(f), which represents the scale of the filter, by minimizing local noise-to-signal ratio. We analytically derived the variance of residual noise from the Poisson or compound Poisson processes after Gaussian filtering. From the derived analytical form of the variance of residual noise, optimal σ(2)(f)) is proved to be proportional to the noiseless fluence and modulated by local structure strength expressed as the linear fitting error of the structure. A strategy was used to obtain the reliable linear fitting error: smoothing the projection along the longitudinal direction to calculate the linear fitting error along the lateral direction and vice versa. The performance of our multiscale filter was examined on low-dose cone beam projections of a Catphan phantom and a head-and-neck patient. After performing the filter on the Catphan phantom projections scanned with pulse time 4 ms, the number of visible line pairs was similar to that scanned with 16 ms, and the contrast-to-noise ratio of the inserts was higher than that scanned with 16 ms about 64% in average. For the simulated head-and-neck patient projections with pulse time 4 ms, the visibility of soft tissue structures in the patient was comparable to that scanned with 20 ms. The image processing took less than 0.5 s per projection with 1024 × 768 pixels.
Fourier-based linear systems description of free-breathing pulmonary magnetic resonance imaging
NASA Astrophysics Data System (ADS)
Capaldi, D. P. I.; Svenningsen, S.; Cunningham, I. A.; Parraga, G.
2015-03-01
Fourier-decomposition of free-breathing pulmonary magnetic resonance imaging (FDMRI) was recently piloted as a way to provide rapid quantitative pulmonary maps of ventilation and perfusion without the use of exogenous contrast agents. This method exploits fast pulmonary MRI acquisition of free-breathing proton (1H) pulmonary images and non-rigid registration to compensate for changes in position and shape of the thorax associated with breathing. In this way, ventilation imaging using conventional MRI systems can be undertaken but there has been no systematic evaluation of fundamental image quality measurements based on linear systems theory. We investigated the performance of free-breathing pulmonary ventilation imaging using a Fourier-based linear system description of each operation required to generate FDMRI ventilation maps. Twelve subjects with chronic obstructive pulmonary disease (COPD) or bronchiectasis underwent pulmonary function tests and MRI. Non-rigid registration was used to co-register the temporal series of pulmonary images. Pulmonary voxel intensities were aligned along a time axis and discrete Fourier transforms were performed on the periodic signal intensity pattern to generate frequency spectra. We determined the signal-to-noise ratio (SNR) of the FDMRI ventilation maps using a conventional approach (SNRC) and using the Fourier-based description (SNRF). Mean SNR was 4.7 ± 1.3 for subjects with bronchiectasis and 3.4 ± 1.8, for COPD subjects (p>.05). SNRF was significantly different than SNRC (p<.01). SNRF was approximately 50% of SNRC suggesting that the linear system model well-estimates the current approach.
Dynamic imperfections and optimized feedback design in the Compact Linear Collider main linac
NASA Astrophysics Data System (ADS)
Eliasson, Peder
2008-05-01
The Compact Linear Collider (CLIC) main linac is sensitive to dynamic imperfections such as element jitter, injected beam jitter, and ground motion. These effects cause emittance growth that, in case of ground motion, has to be counteracted by a trajectory feedback system. The feedback system itself will, due to jitter effects and imperfect beam position monitors (BPMs), indirectly cause emittance growth. Fast and accurate simulations of both the direct and indirect effects are desirable, but due to the many elements of the CLIC main linac, simulations may become very time consuming. In this paper, an efficient way of simulating linear (or nearly linear) dynamic effects is described. The method is also shown to facilitate the analytic determination of emittance growth caused by the different dynamic imperfections while using a trajectory feedback system. Emittance growth expressions are derived for quadrupole, accelerating structure, and beam jitter, for ground motion, and for noise in the feedback BPMs. Finally, it is shown how the method can be used to design a feedback system that is optimized for the optics of the machine and the ground motion spectrum of the particular site. This feedback system gives an emittance growth rate that is approximately 10 times lower than that of traditional trajectory feedbacks. The robustness of the optimized feedback system is studied for a number of additional imperfections, e.g., dipole corrector imperfections and faulty knowledge about the machine optics, with promising results.
Varadarajan, Divya; Haldar, Justin P
2017-11-01
The data measured in diffusion MRI can be modeled as the Fourier transform of the Ensemble Average Propagator (EAP), a probability distribution that summarizes the molecular diffusion behavior of the spins within each voxel. This Fourier relationship is potentially advantageous because of the extensive theory that has been developed to characterize the sampling requirements, accuracy, and stability of linear Fourier reconstruction methods. However, existing diffusion MRI data sampling and signal estimation methods have largely been developed and tuned without the benefit of such theory, instead relying on approximations, intuition, and extensive empirical evaluation. This paper aims to address this discrepancy by introducing a novel theoretical signal processing framework for diffusion MRI. The new framework can be used to characterize arbitrary linear diffusion estimation methods with arbitrary q-space sampling, and can be used to theoretically evaluate and compare the accuracy, resolution, and noise-resilience of different data acquisition and parameter estimation techniques. The framework is based on the EAP, and makes very limited modeling assumptions. As a result, the approach can even provide new insight into the behavior of model-based linear diffusion estimation methods in contexts where the modeling assumptions are inaccurate. The practical usefulness of the proposed framework is illustrated using both simulated and real diffusion MRI data in applications such as choosing between different parameter estimation methods and choosing between different q-space sampling schemes. Copyright © 2017 Elsevier Inc. All rights reserved.
Time and Memory Efficient Online Piecewise Linear Approximation of Sensor Signals.
Grützmacher, Florian; Beichler, Benjamin; Hein, Albert; Kirste, Thomas; Haubelt, Christian
2018-05-23
Piecewise linear approximation of sensor signals is a well-known technique in the fields of Data Mining and Activity Recognition. In this context, several algorithms have been developed, some of them with the purpose to be performed on resource constrained microcontroller architectures of wireless sensor nodes. While microcontrollers are usually constrained in computational power and memory resources, all state-of-the-art piecewise linear approximation techniques either need to buffer sensor data or have an execution time depending on the segment’s length. In the paper at hand, we propose a novel piecewise linear approximation algorithm, with a constant computational complexity as well as a constant memory complexity. Our proposed algorithm’s worst-case execution time is one to three orders of magnitude smaller and its average execution time is three to seventy times smaller compared to the state-of-the-art Piecewise Linear Approximation (PLA) algorithms in our experiments. In our evaluations, we show that our algorithm is time and memory efficient without sacrificing the approximation quality compared to other state-of-the-art piecewise linear approximation techniques, while providing a maximum error guarantee per segment, a small parameter space of only one parameter, and a maximum latency of one sample period plus its worst-case execution time.
NASA Technical Reports Server (NTRS)
Fields, J. M.; Powell, C. A.
1985-01-01
Reactions to low numbers of helicopter noise events (less than 50 per day) were studied in a community setting. Community residents were repeatedly interviewed about daily noise annoyance reactions on days when helicopter noise exposures were, without the residents' knowledge, controlled. The effects of maximum noise level and number of noise events on helicopter noise annoyance are consistent with the principles contained in LEQ-based noise indices. The effect of the duration of noise events is also consistent with LEQ-based indices. After removing the effect of differences in noise levels (LEQ) there is not an important difference between reactions to impulsive and nonimpulsive types of helicopters. EPNL, where corrected for number of overflights, and LEQ are approximately equally successful in representing the characteristics of noise which are related to human response. The new type of design provided estimates of the parameters in a noise reaction model which would not obtained with a similar degree of precision from conventional study designs.
Communication system with adaptive noise suppression
NASA Technical Reports Server (NTRS)
Kozel, David (Inventor); Devault, James A. (Inventor); Birr, Richard B. (Inventor)
2007-01-01
A signal-to-noise ratio dependent adaptive spectral subtraction process eliminates noise from noise-corrupted speech signals. The process first pre-emphasizes the frequency components of the input sound signal which contain the consonant information in human speech. Next, a signal-to-noise ratio is determined and a spectral subtraction proportion adjusted appropriately. After spectral subtraction, low amplitude signals can be squelched. A single microphone is used to obtain both the noise-corrupted speech and the average noise estimate. This is done by determining if the frame of data being sampled is a voiced or unvoiced frame. During unvoiced frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Spectral subtraction may be performed on a composite noise-corrupted signal, or upon individual sub-bands of the noise-corrupted signal. Pre-averaging of the input signal's magnitude spectrum over multiple time frames may be performed to reduce musical noise.
Noise Assessment of the Southeastern Pennsylvania Transportation Authority Heavy Rail Transit System
DOT National Transportation Integrated Search
1978-10-01
The report describes the noise climate on and near the Southeastern Pennsylvania Transportation Authority, (SEPTA), Broad Street Subway and Market-Frankford Elevated Line. The two SEPTA urban rail transit lines have approximately 22.6 miles of two-wa...
Aircraft and background noise annoyance effects
NASA Technical Reports Server (NTRS)
Willshire, K. F.
1984-01-01
To investigate annoyance of multiple noise sources, two experiments were conducted. The first experiment, which used 48 subjects, was designed to establish annoyance-noise level functions for three community noise sources presented individually: jet aircraft flyovers, air conditioner, and traffic. The second experiment, which used 216 subjects, investigated the effects of background noise on aircraft annoyance as a function of noise level and spectrum shape; and the differences between overall, aircraft, and background noise annoyance. In both experiments, rated annoyance was the dependent measure. Results indicate that the slope of the linear relationship between annoyance and noise level for traffic is significantly different from that of flyover and air conditioner noise and that further research was justified to determine the influence of the two background noises on overall, aircraft, and background noise annoyance (e.g., experiment two). In experiment two, total noise exposure, signal-to-noise ratio, and background source type were found to have effects on all three types of annoyance. Thus, both signal-to-noise ratio, and the background source must be considered when trying to determine community response to combined noise sources.
Sources of signal-dependent noise during isometric force production.
Jones, Kelvin E; Hamilton, Antonia F; Wolpert, Daniel M
2002-09-01
It has been proposed that the invariant kinematics observed during goal-directed movements result from reducing the consequences of signal-dependent noise (SDN) on motor output. The purpose of this study was to investigate the presence of SDN during isometric force production and determine how central and peripheral components contribute to this feature of motor control. Peripheral and central components were distinguished experimentally by comparing voluntary contractions to those elicited by electrical stimulation of the extensor pollicis longus muscle. To determine other factors of motor-unit physiology that may contribute to SDN, a model was constructed and its output compared with the empirical data. SDN was evident in voluntary isometric contractions as a linear scaling of force variability (SD) with respect to the mean force level. However, during electrically stimulated contractions to the same force levels, the variability remained constant over the same range of mean forces. When the subjects were asked to combine voluntary with stimulation-induced contractions, the linear scaling relationship between the SD and mean force returned. The modeling results highlight that much of the basic physiological organization of the motor-unit pool, such as range of twitch amplitudes and range of recruitment thresholds, biases force output to exhibit linearly scaled SDN. This is in contrast to the square root scaling of variability with mean force present in any individual motor-unit of the pool. Orderly recruitment by twitch amplitude was a necessary condition for producing linearly scaled SDN. Surprisingly, the scaling of SDN was independent of the variability of motoneuron firing and therefore by inference, independent of presynaptic noise in the motor command. We conclude that the linear scaling of SDN during voluntary isometric contractions is a natural by-product of the organization of the motor-unit pool that does not depend on signal-dependent noise in the motor command. Synaptic noise in the motor command and common drive, which give rise to the variability and synchronization of motoneuron spiking, determine the magnitude of the force variability at a given level of mean force output.
On the Scaling Law for Broadband Shock Noise Intensity in Supersonic Jets
NASA Technical Reports Server (NTRS)
Kanudula, Max
2009-01-01
A theoretical model for the scaling of broadband shock noise intensity in supersonic jets was formulated on the basis of linear shock-shear wave interaction. An hypothesis has been postulated that the peak angle of incidence (closer to the critical angle) for the shear wave primarily governs the generation of sound in the interaction process rather than the noise generation contribution from off-peak incident angles. The proposed theory satisfactorily explains the well-known scaling law for the broadband shock -associated noise in supersonic jets.
Apparent volume dependence of 1/f noise in thin film structures: role of contacts.
Barone, C; Pagano, S; Méchin, L; Routoure, J-M; Orgiani, P; Maritato, L
2008-05-01
The experimental investigation of low-frequency noise properties in new materials is very useful for the understanding of the involved physical transport mechanisms. In this paper it is shown that, when contact noise is present, the experimental values of the normalized Hooge parameter show a fictitious linear dependence on the volume of the analyzed samples. Experimental data on noise measurements of La0.7Sr0.3MnO3 thin films are reported to demonstrate the validity of the analysis performed.
Breadboard linear array scan imager using LSI solid-state technology
NASA Technical Reports Server (NTRS)
Tracy, R. A.; Brennan, J. A.; Frankel, D. G.; Noll, R. E.
1976-01-01
The performance of large scale integration photodiode arrays in a linear array scan (pushbroom) breadboard was evaluated for application to multispectral remote sensing of the earth's resources. The technical approach, implementation, and test results of the program are described. Several self scanned linear array visible photodetector focal plane arrays were fabricated and evaluated in an optical bench configuration. A 1728-detector array operating in four bands (0.5 - 1.1 micrometer) was evaluated for noise, spectral response, dynamic range, crosstalk, MTF, noise equivalent irradiance, linearity, and image quality. Other results include image artifact data, temporal characteristics, radiometric accuracy, calibration experience, chip alignment, and array fabrication experience. Special studies and experimentation were included in long array fabrication and real-time image processing for low-cost ground stations, including the use of computer image processing. High quality images were produced and all objectives of the program were attained.
Technology evaluation of man-rated acceleration test equipment for vestibular research
NASA Technical Reports Server (NTRS)
Taback, I.; Kenimer, R. L.; Butterfield, A. J.
1983-01-01
The considerations for eliminating acceleration noise cues in horizontal, linear, cyclic-motion sleds intended for both ground and shuttle-flight applications are addressed. the principal concerns are the acceleration transients associated with change in direction-of-motion for the carriage. The study presents a design limit for acceleration cues or transients based upon published measurements for thresholds of human perception to linear cyclic motion. The sources and levels for motion transients are presented based upon measurements obtained from existing sled systems. The approaches to a noise-free system recommends the use of air bearings for the carriage support and moving-coil linear induction motors operating at low frequency as the drive system. Metal belts running on air bearing pulleys provide an alternate approach to the driving system. The appendix presents a discussion of alternate testing techniques intended to provide preliminary type data by means of pendulums, linear motion devices and commercial air bearing tables.
A general moment expansion method for stochastic kinetic models
NASA Astrophysics Data System (ADS)
Ale, Angelique; Kirk, Paul; Stumpf, Michael P. H.
2013-05-01
Moment approximation methods are gaining increasing attention for their use in the approximation of the stochastic kinetics of chemical reaction systems. In this paper we derive a general moment expansion method for any type of propensities and which allows expansion up to any number of moments. For some chemical reaction systems, more than two moments are necessary to describe the dynamic properties of the system, which the linear noise approximation is unable to provide. Moreover, also for systems for which the mean does not have a strong dependence on higher order moments, moment approximation methods give information about higher order moments of the underlying probability distribution. We demonstrate the method using a dimerisation reaction, Michaelis-Menten kinetics and a model of an oscillating p53 system. We show that for the dimerisation reaction and Michaelis-Menten enzyme kinetics system higher order moments have limited influence on the estimation of the mean, while for the p53 system, the solution for the mean can require several moments to converge to the average obtained from many stochastic simulations. We also find that agreement between lower order moments does not guarantee that higher moments will agree. Compared to stochastic simulations, our approach is numerically highly efficient at capturing the behaviour of stochastic systems in terms of the average and higher moments, and we provide expressions for the computational cost for different system sizes and orders of approximation. We show how the moment expansion method can be employed to efficiently quantify parameter sensitivity. Finally we investigate the effects of using too few moments on parameter estimation, and provide guidance on how to estimate if the distribution can be accurately approximated using only a few moments.
NASA Astrophysics Data System (ADS)
Tischenko, Oleg; Hoeschen, Christoph; Effenberger, Olaf; Reissberg, Steffen; Buhr, Egbert; Doehring, Wilfried
2003-06-01
There are many aspects that influence and deteriorate the detection of pathologies in X-ray images. Some of those are due to effects taking place in the stage of forming the X-ray intensity pattern in front of the x-ray detector. These can be described as motion blurring, depth blurring, anatomical background, scatter noise and structural noise. Structural noise results from an overlapping of fine irrelevant anatomical structures. A method for measuring the combined effect of structural noise and scatter noise was developed and will be presented in this paper. This method is based on the consideration that within a pair of projections created after rotation of the object with a small angle (which is within the typical uncertainty in positioning the patient) both images would show the same relevant structures whereas the projection of the fine overlapping structures will appear quite differently in the two images. To demonstrate the method two X-ray radiographs of a lung phantom were produced. The second radiograph was achieved after rotating the lung by an angle of about 3. Dyadic wavelet representations of both images were regarded. For each value of the wavelet scale parameter the corresponding pair of approximations was matched using the cross correlation matching technique. The homologous regions of approximations were extracted. The image containing only those structures that appear in both images simultaneously was then reconstructed from the wavelet coefficients corresponding to the homologous regions. The difference between one of the original images and the noise-reduced image contains the structural noise and the scatter noise.