Oblivious Transfer from the Additive White Gaussian Noise Channel
NASA Astrophysics Data System (ADS)
Isaka, Motohiko
We consider the use of the additive white Gaussian noise channel to achieve information theoretically secure oblivious transfer. A protocol for this primitive that ensures the correctness and privacy for players is presented together with the signal design. We also study the information theoretic efficiency of the protocol, and some more practical issues where the parameter of the channel is unknown to the players.
Gaussian capacity of the quantum bosonic memory channel with additive correlated Gaussian noise
Schaefer, Joachim; Karpov, Evgueni; Cerf, Nicolas J.
2011-09-15
We present an algorithm for calculation of the Gaussian classical capacity of a quantum bosonic memory channel with additive Gaussian noise. The algorithm, restricted to Gaussian input states, is applicable to all channels with noise correlations obeying certain conditions and works in the full input energy domain, beyond previous treatments of this problem. As an illustration, we study the optimal input states and capacity of a quantum memory channel with Gauss-Markov noise [J. Schaefer, Phys. Rev. A 80, 062313 (2009)]. We evaluate the enhancement of the transmission rate when using these optimal entangled input states by comparison with a product coherent-state encoding and find out that such a simple coherent-state encoding achieves not less than 90% of the capacity.
Bag, Bidhan Chandra; Hu, Chin-Kun
2007-04-01
In a previous paper [Bag and Hu, Phys. Rev. E 73, 061107 (2006)], we studied the mean lifetime (MLT) for the escape of a Brownian particle through an unstable limit cycle driven by multiplicative colored Gaussian and additive Gaussian white noises and found resonant activation (RA) behavior. In the present paper we switch from Gaussian to non-Gaussian multiplicative colored noise. We find that in the RA phenomenon, the minimum appears at a smaller noise correlation time (tau) for non-Gaussian noises compared to Gaussian noises in the plot of MLT vs tau for a fixed noise variance; the same plot for a given noise strength increases linearly and the increasing rate is smaller for non-Gaussian noises than for the Gaussian noises; the plot of logarithm of inverse of MLT vs inverse of the strength of additive noise is Arrhenius-like for Gaussian colored noise and it becomes similar to the quantum-Kramers rate if the multiplicative noise is non-Gaussian.
NASA Astrophysics Data System (ADS)
Guo, Yongfeng; Shen, Yajun; Tan, Jianguo
2016-09-01
The phenomenon of stochastic resonance (SR) in a piecewise nonlinear model driven by a periodic signal and correlated noises for the cases of a multiplicative non-Gaussian noise and an additive Gaussian white noise is investigated. Applying the path integral approach, the unified colored noise approximation and the two-state model theory, the analytical expression of the signal-to-noise ratio (SNR) is derived. It is found that conventional stochastic resonance exists in this system. From numerical computations we obtain that: (i) As a function of the non-Gaussian noise intensity, the SNR is increased when the non-Gaussian noise deviation parameter q is increased. (ii) As a function of the Gaussian noise intensity, the SNR is decreased when q is increased. This demonstrates that the effect of the non-Gaussian noise on SNR is different from that of the Gaussian noise in this system. Moreover, we further discuss the effect of the correlation time of the non-Gaussian noise, cross-correlation strength, the amplitude and frequency of the periodic signal on SR.
Matsuoka, A J; Abbas, P J; Rubinstein, J T; Miller, C A
2000-11-01
Experimental results from humans and animals show that electrically evoked compound action potential (EAP) responses to constant-amplitude pulse train stimulation can demonstrate an alternating pattern, due to the combined effects of highly synchronized responses to electrical stimulation and refractory effects (Wilson et al., 1994). One way to improve signal representation is to reduce the level of across-fiber synchrony and hence, the level of the amplitude alternation. To accomplish this goal, we have examined EAP responses in the presence of Gaussian noise added to the pulse train stimulus. Addition of Gaussian noise at a level approximately -30 dB relative to EAP threshold to the pulse trains decreased the amount of alternation, indicating that stochastic resonance may be induced in the auditory nerve. The use of some type of conditioning stimulus such as Gaussian noise may provide a more 'normal' neural response pattern.
On estimating the phase of a periodic waveform in additive Gaussian noise, part 3
NASA Technical Reports Server (NTRS)
Rauch, L. L.
1991-01-01
Motivated by advances in signal processing technology that support more complex algorithms, researchers have taken a new look at the problem of estimating the phase and other parameters of a nearly periodic waveform in additive Gaussian noise, based on observation during a given time interval. Parts 1 and 2 are very briefly reviewed. In part 3, the actual performances of some of the highly nonlinear estimation algorithms of parts 1 and 2 are evaluated by numerical simulation using Monte Carlo techniques.
Additive white Gaussian noise level estimation in SVD domain for images.
Liu, Wei; Lin, Weisi
2013-03-01
Accurate estimation of Gaussian noise level is of fundamental interest in a wide variety of vision and image processing applications as it is critical to the processing techniques that follow. In this paper, a new effective noise level estimation method is proposed on the basis of the study of singular values of noise-corrupted images. Two novel aspects of this paper address the major challenges in noise estimation: 1) the use of the tail of singular values for noise estimation to alleviate the influence of the signal on the data basis for the noise estimation process and 2) the addition of known noise to estimate the content-dependent parameter, so that the proposed scheme is adaptive to visual signals, thereby enabling a wider application scope of the proposed scheme. The analysis and experiment results demonstrate that the proposed algorithm can reliably infer noise levels and show robust behavior over a wide range of visual content and noise conditions, and that is outperforms relevant existing methods.
On estimating the phase of periodic waveform in additive Gaussian noise, part 2
NASA Astrophysics Data System (ADS)
Rauch, L. L.
1984-11-01
Motivated by advances in signal processing technology that support more complex algorithms, a new look is taken at the problem of estimating the phase and other parameters of a periodic waveform in additive Gaussian noise. The general problem was introduced and the maximum a posteriori probability criterion with signal space interpretation was used to obtain the structures of optimum and some suboptimum phase estimators for known constant frequency and unknown constant phase with an a priori distribution. Optimal algorithms are obtained for some cases where the frequency is a parameterized function of time with the unknown parameters and phase having a joint a priori distribution. In the last section, the intrinsic and extrinsic geometry of hypersurfaces is introduced to provide insight to the estimation problem for the small noise and large noise cases.
Smolin, John A; Gambetta, Jay M; Smith, Graeme
2012-02-17
We provide an efficient method for computing the maximum-likelihood mixed quantum state (with density matrix ρ) given a set of measurement outcomes in a complete orthonormal operator basis subject to Gaussian noise. Our method works by first changing basis yielding a candidate density matrix μ which may have nonphysical (negative) eigenvalues, and then finding the nearest physical state under the 2-norm. Our algorithm takes at worst O(d(4)) for the basis change plus O(d(3)) for finding ρ where d is the dimension of the quantum state. In the special case where the measurement basis is strings of Pauli operators, the basis change takes only O(d(3)) as well. The workhorse of the algorithm is a new linear-time method for finding the closest probability distribution (in Euclidean distance) to a set of real numbers summing to one.
Performance of peaky template matching under additive white Gaussian noise and uniform quantization
NASA Astrophysics Data System (ADS)
Horvath, Matthew S.; Rigling, Brian D.
2015-05-01
Peaky template matching (PTM) is a special case of a general algorithm known as multinomial pattern matching originally developed for automatic target recognition of synthetic aperture radar data. The algorithm is a model- based approach that first quantizes pixel values into Nq = 2 discrete values yielding generative Beta-Bernoulli models as class-conditional templates. Here, we consider the case of classification of target chips in AWGN and develop approximations to image-to-template classification performance as a function of the noise power. We focus specifically on the case of a uniform quantization" scheme, where a fixed number of the largest pixels are quantized high as opposed to using a fixed threshold. This quantization method reduces sensitivity to the scaling of pixel intensities and quantization in general reduces sensitivity to various nuisance parameters difficult to account for a priori. Our performance expressions are verified using forward-looking infrared imagery from the Army Research Laboratory Comanche dataset.
1994-03-01
normalized cross- correlation coefficient ; the modified normalized cross- correlation coefficient , and; the divergence and the Bhattacharyya distance. Noise was...added to the signals to create signal to noise ratios of 0 dB to -20 dB. Results show that as noise levels increase, the modified normalized cross- correlation coefficient spectral measure remains the most robust scheme.
NASA Astrophysics Data System (ADS)
Ranjha, Bilal; Zhou, Zhou; Kavehrad, Mohsen
2014-08-01
We have compared the bit error rate (BER) performance of precoding-based asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) and pulse amplitude modulated discrete multitone (PAM-DMT) optical wireless (OW) systems in additive white Gaussian noise (AWGN) and indoor multipath frequency selective channel. Simulation and analytical results show that precoding schemes such as discrete Fourier transform, discrete cosine transform, and Zadoff-Chu sequences do not affect the performance of the OW systems in the AWGN channel while they do reduce the peak-to-average power ratio (PAPR) of the OFDM output signal. However, in a multipath indoor channel, using zero forcing frequency domain equalization precoding-based systems give better BER performance than their conventional counterparts. With additional clipping to further reduce the PAPR, precoding-based systems also show better BER performance compared to nonprecoded systems when clipped relative to the peak of nonprecoded systems. Therefore, precoding-based ACO-OFDM and PAM-DMT systems offer better BER performance, zero signaling overhead, and low PAPR compared to conventional systems.
Gaussian white noise as a resource for work extraction
NASA Astrophysics Data System (ADS)
Dechant, Andreas; Baule, Adrian; Sasa, Shin-ichi
2017-03-01
We show that uncorrelated Gaussian noise can drive a system out of equilibrium and can serve as a resource from which work can be extracted. We consider an overdamped particle in a periodic potential with an internal degree of freedom and a state-dependent friction, coupled to an equilibrium bath. Applying additional Gaussian white noise drives the system into a nonequilibrium steady state and causes a finite current if the potential is spatially asymmetric. The model thus operates as a Brownian ratchet, whose current we calculate explicitly in three complementary limits. Since the particle current is driven solely by additive Gaussian white noise, this shows that the latter can potentially perform work against an external load. By comparing the extracted power to the energy injection due to the noise, we discuss the efficiency of such a ratchet.
Multiqubit spectroscopy of Gaussian quantum noise
NASA Astrophysics Data System (ADS)
Paz-Silva, Gerardo A.; Norris, Leigh M.; Viola, Lorenza
2017-02-01
We introduce multipulse quantum noise spectroscopy protocols for spectral estimation of the noise affecting multiple qubits coupled to Gaussian dephasing environments including both classical and quantum sources. Our protocols are capable of reconstructing all the noise auto- and cross-correlation spectra entering the multiqubit dynamics, providing access, in particular, to the asymmetric spectra associated with nonclassical environments. Our result relies on (i) an exact analytic solution for the reduced multiqubit dynamics that holds in the presence of an arbitrary Gaussian environment and dephasing-preserving control; (ii) the use of specific timing symmetries, which allow for a frequency comb to be engineered for all filter functions of interest, and for the spectra to be related to experimentally accessible observables. We show that quantum spectra have distinctive dynamical signatures, which we explore in two paradigmatic open-system models describing spin and charge qubits coupled to bosonic environments. Complete noise spectroscopy is demonstrated numerically in a realistic setting consisting of two-exciton qubits coupled to a phonon bath. The estimated spectra allow us to accurately predict the exciton dynamics as well as extract the temperature and spectral density of the quantum environment.
NASA Astrophysics Data System (ADS)
Kenfack, Lionel Tenemeza; Tchoffo, Martin; Fai, Lukong Cornelius; Fouokeng, Georges Collince
2017-04-01
We address the entanglement dynamics of a three-qubit system interacting with a classical fluctuating environment described either by a Gaussian or non-Gaussian noise in three different configurations namely: common, independent and mixed environments. Specifically, we focus on the Ornstein-Uhlenbeck (OU) noise and the random telegraph noise (RTN). The qubits are prepared in a state composed of a Greenberger-Horne-Zeilinger (GHZ) and a W state. With the help of the tripartite negativity, we show that the entanglement evolution is not only affected by the type of system-environment coupling but also by the kind and the memory properties of the considered noise. We also compared the dynamics induced by the two kinds of noise and we find that even if both noises have a Lorentzian spectrum, the effects of the OU noise cannot be in a simple way deduced from those of the RTN and vice-versa. In addition, we show that the entanglement can be indefinitely preserved when the qubits are coupled to the environmental noise in a common environment (CE). Finally, the presence or absence of peculiar phenomena such as entanglement revivals (ER) and entanglement sudden death (ESD) is observed.
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.
Switching Exponent Scaling near Bifurcation Points for Non-Gaussian Noise
2010-04-07
REPORT Switching Exponent Scaling near Bifurcation Points for Non-Gaussian Noise 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: We study noise-induced...which gives the logarithm of the switching rate, displays a non-power-law dependence on the distance to the bifurcation point . This dependence is...found for Poisson noise. Even weak additional Gaussian noise dominates switching sufficiently close to the bifurcation point , leading to a crossover in
Spatial pattern formation induced by Gaussian white noise.
Scarsoglio, Stefania; Laio, Francesco; D'Odorico, Paolo; Ridolfi, Luca
2011-02-01
The ability of Gaussian noise to induce ordered states in dynamical systems is here presented in an overview of the main stochastic mechanisms able to generate spatial patterns. These mechanisms involve: (i) a deterministic local dynamics term, accounting for the local rate of variation of the field variable, (ii) a noise component (additive or multiplicative) accounting for the unavoidable environmental disturbances, and (iii) a linear spatial coupling component, which provides spatial coherence and takes into account diffusion mechanisms. We investigate these dynamics using analytical tools, such as mean-field theory, linear stability analysis and structure function analysis, and use numerical simulations to confirm these analytical results.
Methods to characterize non-Gaussian noise in TAMA
NASA Astrophysics Data System (ADS)
Ando, Masaki; Arai, K.; Takahashi, R.; Tatsumi, D.; Beyersdorf, P.; Kawamura, S.; Miyoki, S.; Mio, N.; Moriwaki, S.; Numata, K.; Kanda, N.; Aso, Y.; Fujimoto, M.-K.; Tsubono, K.; Kuroda, K.; TAMA Collaboration
2003-09-01
We present a data characterization method for the main output signal of the interferometric gravitational-wave detector, in particular targetting at effective detection of burst gravitational waves from stellar core collapse. The time scale of non-Gaussian events is evaluated in this method, and events with longer time scale than real signals are rejected as non-Gaussian noises. As a result of data analysis using 1000 h of real data with the interferometric gravitational-wave detector TAMA300, the false-alarm rate was improved 103 times with this non-Gaussian noise evaluation and rejection method.
Continuous-variable quantum key distribution with Gaussian source noise
Shen Yujie; Peng Xiang; Yang Jian; Guo Hong
2011-05-15
Source noise affects the security of continuous-variable quantum key distribution (CV QKD) and is difficult to analyze. We propose a model to characterize Gaussian source noise through introducing a neutral party (Fred) who induces the noise with a general unitary transformation. Without knowing Fred's exact state, we derive the security bounds for both reverse and direct reconciliations and show that the bound for reverse reconciliation is tight.
Receiver design for SPAD-based VLC systems under Poisson-Gaussian mixed noise model.
Mao, Tianqi; Wang, Zhaocheng; Wang, Qi
2017-01-23
Single-photon avalanche diode (SPAD) is a promising photosensor because of its high sensitivity to optical signals in weak illuminance environment. Recently, it has drawn much attention from researchers in visible light communications (VLC). However, existing literature only deals with the simplified channel model, which only considers the effects of Poisson noise introduced by SPAD, but neglects other noise sources. Specifically, when an analog SPAD detector is applied, there exists Gaussian thermal noise generated by the transimpedance amplifier (TIA) and the digital-to-analog converter (D/A). Therefore, in this paper, we propose an SPAD-based VLC system with pulse-amplitude-modulation (PAM) under Poisson-Gaussian mixed noise model, where Gaussian-distributed thermal noise at the receiver is also investigated. The closed-form conditional likelihood of received signals is derived using the Laplace transform and the saddle-point approximation method, and the corresponding quasi-maximum-likelihood (quasi-ML) detector is proposed. Furthermore, the Poisson-Gaussian-distributed signals are converted to Gaussian variables with the aid of the generalized Anscombe transform (GAT), leading to an equivalent additive white Gaussian noise (AWGN) channel, and a hard-decision-based detector is invoked. Simulation results demonstrate that, the proposed GAT-based detector can reduce the computational complexity with marginal performance loss compared with the proposed quasi-ML detector, and both detectors are capable of accurately demodulating the SPAD-based PAM signals.
Making tensor factorizations robust to non-gaussian noise.
Chi, Eric C.; Kolda, Tamara Gibson
2011-03-01
Tensors are multi-way arrays, and the CANDECOMP/PARAFAC (CP) tensor factorization has found application in many different domains. The CP model is typically fit using a least squares objective function, which is a maximum likelihood estimate under the assumption of independent and identically distributed (i.i.d.) Gaussian noise. We demonstrate that this loss function can be highly sensitive to non-Gaussian noise. Therefore, we propose a loss function based on the 1-norm because it can accommodate both Gaussian and grossly non-Gaussian perturbations. We also present an alternating majorization-minimization (MM) algorithm for fitting a CP model using our proposed loss function (CPAL1) and compare its performance to the workhorse algorithm for fitting CP models, CP alternating least squares (CPALS).
Development and modification of a Gaussian and non-Gaussian noise exposure system
NASA Astrophysics Data System (ADS)
Schlag, Adam W.
Millions of people across the world currently have noise induced hearing loss, and many are working in conditions with both continuous Gaussian and non-Gaussian noises that could affect their hearing. It was hypothesized that the energy of the noise was the cause of the hearing loss and did not depend on temporal pattern of a noise. This was referred to as the equal energy hypothesis. This hypothesis has been shown to have limitations though. This means that there is a difference in the types of noise a person receives to induce hearing loss and it is necessary to build a system that can easily mimic various conditions to conduct research. This study builds a system that can produce both non-Gaussian impulse/impact noises and continuous Gaussian noise. It was found that the peak sound pressure level of the system could reach well above the needed 120 dB level to represent acoustic trauma and could replicate well above the 85 dB A-weighted sound pressure level to produce conditions of gradual developing hearing loss. The system reached a maximum of 150 dB sound peak pressure level and a maximum of 133 dB A-weighted sound pressure level. Various parameters could easily be adjusted to control the sound, such as the high and low cutoff frequency to center the sound at 4 kHz. The system build can easily be adjusted to create numerous sound conditions and will hopefully be modified and improved in hopes of eventually being used for animal studies to lead to the creation of a method to treat or prevent noise induced hearing loss.
Qubit Noise Spectroscopy for Non-Gaussian Dephasing Environments
NASA Astrophysics Data System (ADS)
Norris, Leigh M.; Paz-Silva, Gerardo A.; Viola, Lorenza
2016-04-01
We introduce open-loop quantum control protocols for characterizing the spectral properties of non-Gaussian noise, applicable to both classical and quantum dephasing environments. By engineering a multidimensional frequency comb via repetition of suitably designed pulse sequences, the desired high-order spectra may be related to observable properties of the qubit probe. We prove that access to a high time resolution is key to achieving spectral reconstruction over an extended bandwidth, overcoming the limitations of existing schemes. Non-Gaussian spectroscopy is demonstrated for a classical noise model describing quadratic dephasing at an optimal point, as well as a quantum spin-boson model out of equilibrium. In both cases, we obtain spectral reconstructions that accurately predict the qubit dynamics in the non-Gaussian regime.
Analysis of fractional Gaussian noises using level crossing method
NASA Astrophysics Data System (ADS)
Vahabi, M.; Jafari, G. R.; Sadegh Movahed, M.
2011-11-01
The so-called level crossing analysis has been used to investigate the empirical data set, but there is a lack of interpretation for what is reflected by the level crossing results. The fractional Gaussian noise as a well-defined stochastic series could be a suitable benchmark to make more sense of the level crossing findings. In this paper, we calculated the average frequency of upcrossing for a wide range of fractional Gaussian noises from logarithmic (zero Hurst exponent, H = 0), to Gaussian, H = 1 (0 < H < 1). By introducing the relative change of the total number of upcrossings for original data with respect to the so-called shuffled data, {R} , an empirical function for the Hurst exponent versus {R} has been established. Finally to make the concept more obvious, we applied this approach to some financial series.
Stochastic Schroedinger equations with general complex Gaussian noises
Bassi, Angelo
2003-06-01
Within the framework of non-Markovian stochastic Schroedinger equations, we generalize the results of [W. T. Strunz, Phys. Lett. A 224, 25 (1996)] to the case of general complex Gaussian noises; we analyze the two important cases of purely real and purely imaginary stochastic processes.
Gaussian noise and the two-network frustrated Kuramoto model
NASA Astrophysics Data System (ADS)
Holder, Andrew B.; Zuparic, Mathew L.; Kalloniatis, Alexander C.
2017-02-01
We examine analytically and numerically a variant of the stochastic Kuramoto model for phase oscillators coupled on a general network. Two populations of phased oscillators are considered, labelled 'Blue' and 'Red', each with their respective networks, internal and external couplings, natural frequencies, and frustration parameters in the dynamical interactions of the phases. We disentangle the different ways that additive Gaussian noise may influence the dynamics by applying it separately on zero modes or normal modes corresponding to a Laplacian decomposition for the sub-graphs for Blue and Red. Under the linearisation ansatz that the oscillators of each respective network remain relatively phase-synchronised centroids or clusters, we are able to obtain simple closed-form expressions using the Fokker-Planck approach for the dynamics of the average angle of the two centroids. In some cases, this leads to subtle effects of metastability that we may analytically describe using the theory of ratchet potentials. These considerations are extended to a regime where one of the populations has fragmented in two. The analytic expressions we derive largely predict the dynamics of the non-linear system seen in numerical simulation. In particular, we find that noise acting on a more tightly coupled population allows for improved synchronisation of the other population where deterministically it is fragmented.
Blind signal processing algorithms under DC biased Gaussian noise
NASA Astrophysics Data System (ADS)
Kim, Namyong; Byun, Hyung-Gi; Lim, Jeong-Ok
2013-05-01
Distortions caused by the DC-biased laser input can be modeled as DC biased Gaussian noise and removing DC bias is important in the demodulation process of the electrical signal in most optical communications. In this paper, a new performance criterion and a related algorithm for unsupervised equalization are proposed for communication systems in the environment of channel distortions and DC biased Gaussian noise. The proposed criterion utilizes the Euclidean distance between the Dirac-delta function located at zero on the error axis and a probability density function of biased constant modulus errors, where constant modulus error is defined by the difference between the system out and a constant modulus calculated from the transmitted symbol points. From the results obtained from the simulation under channel models with fading and DC bias noise abruptly added to background Gaussian noise, the proposed algorithm converges rapidly even after the interruption of DC bias proving that the proposed criterion can be effectively applied to optical communication systems corrupted by channel distortions and DC bias noise.
Cochlear toughening, protection, and potentiation of noise-induced trauma by non-Gaussian noise
NASA Astrophysics Data System (ADS)
Hamernik, Roger P.; Qiu, Wei; Davis, Bob
2003-02-01
An interrupted noise exposure of sufficient intensity, presented on a daily repeating cycle, produces a threshold shift (TS) following the first day of exposure. TSs measured on subsequent days of the exposure sequence have been shown to decrease relative to the initial TS. This reduction of TS, despite the continuing daily exposure regime, has been called a cochlear toughening effect and the exposures referred to as toughening exposures. Four groups of chinchillas were exposed to one of four different noises presented on an interrupted (6 h/day for 20 days) or noninterrupted (24 h/day for 5 days) schedule. The exposures had equivalent total energy, an overall level of 100 dB(A) SPL, and approximately the same flat, broadband long-term spectrum. The noises differed primarily in their temporal structures; two were Gaussian and two were non-Gausssian, nonstationary. Brainstem auditory evoked potentials were used to estimate hearing thresholds and surface preparation histology was used to determine sensory cell loss. The experimental results presented here show that: (1) Exposures to interrupted high-level, non-Gaussian signals produce a toughening effect comparable to that produced by an equivalent interrupted Gaussian noise. (2) Toughening, whether produced by Gaussian or non-Gaussian noise, results in reduced trauma compared to the equivalent uninterrupted noise, and (3) that both continuous and interrupted non-Gaussian exposures produce more trauma than do energy and spectrally equivalent Gaussian noises. Over the course of the 20-day exposure, the pattern of TS following each day's exposure could exhibit a variety of configurations. These results do not support the equal energy hypothesis as a unifying principal for estimating the potential of a noise exposure to produce hearing loss.
Cameron, Donnie; Bouhrara, Mustapha; Reiter, David A; Fishbein, Kenneth W; Choi, Seongjin; Bergeron, Christopher M; Ferrucci, Luigi; Spencer, Richard G
2017-04-06
This work characterizes the effect of lipid and noise signals on muscle diffusion parameter estimation in several conventional and non-Gaussian models, the ultimate objectives being to characterize popular fat suppression approaches for human muscle diffusion studies, to provide simulations to inform experimental work and to report normative non-Gaussian parameter values. The models investigated in this work were the Gaussian monoexponential and intravoxel incoherent motion (IVIM) models, and the non-Gaussian kurtosis and stretched exponential models. These were evaluated via simulations, and in vitro and in vivo experiments. Simulations were performed using literature input values, modeling fat contamination as an additive baseline to data, whereas phantom studies used a phantom containing aliphatic and olefinic fats and muscle-like gel. Human imaging was performed in the hamstring muscles of 10 volunteers. Diffusion-weighted imaging was applied with spectral attenuated inversion recovery (SPAIR), slice-select gradient reversal and water-specific excitation fat suppression, alone and in combination. Measurement bias (accuracy) and dispersion (precision) were evaluated, together with intra- and inter-scan repeatability. Simulations indicated that noise in magnitude images resulted in <6% bias in diffusion coefficients and non-Gaussian parameters (α, K), whereas baseline fitting minimized fat bias for all models, except IVIM. In vivo, popular SPAIR fat suppression proved inadequate for accurate parameter estimation, producing non-physiological parameter estimates without baseline fitting and large biases when it was used. Combining all three fat suppression techniques and fitting data with a baseline offset gave the best results of all the methods studied for both Gaussian diffusion and, overall, for non-Gaussian diffusion. It produced consistent parameter estimates for all models, except IVIM, and highlighted non-Gaussian behavior perpendicular to muscle fibers (
NASA Astrophysics Data System (ADS)
Saha, Surajit; Ghosh, Manas
2016-03-01
We perform a broad exploration of profiles of third harmonic generation (THG) susceptibility of impurity doped quantum dots (QDs) in the presence and absence of noise. We have invoked Gaussian white noise in the present study. A Gaussian impurity has been introduced into the QD. Noise has been applied to the system additively and multiplicatively. A perpendicular magnetic field emerges out as a confinement source and a static external electric field has been applied. The THG profiles have been pursued as a function of incident photon energy when several important parameters such as electric field strength, magnetic field strength, confinement energy, dopant location, Al concentration, dopant potential, relaxation time and noise strength assume different values. Moreover, the role of the pathway through which noise is applied (additive/multiplicative) on the THG profiles has also been deciphered. The THG profiles are found to be decorated with interesting observations such as shift of THG peak position and maximization/minimization of THG peak intensity. Presence of noise alters the characteristics of THG profiles and sometimes enhances the THG peak intensity. Furthermore, the mode of application of noise (additive/multiplicative) also regulates the THG profiles in a few occasions in contrasting manners. The observations highlight the possible scope of tuning the THG coefficient of doped QD systems in the presence of noise and bears tremendous technological importance.
NASA Astrophysics Data System (ADS)
Bera, Aindrila; Saha, Surajit; Ganguly, Jayanta; Ghosh, Manas
2016-11-01
We explore diamagnetic susceptibility (DMS) of impurity doped quantum dot (QD) in presence of Gaussian white noise. Noise has been introduced to the system additively and multiplicatively. In view of these profiles of DMS have been pursued with variations of several important quantities e.g. magnetic field strength, confinement frequency, dopant location, dopant potential, and aluminium concentration, both in presence and absence of noise. We have invariably envisaged noise-induced suppression of DMS. Moreover, the extent of suppression noticeably depends on mode of application (additive/multiplicative) of noise. The said mode of application also plays a governing role in the onset of saturation of DMS values. The present study provides a deep insight into the promising role played by noise in controlling effective confinement imposed on the system which bears significant relevance.
Nonlinear Bayesian Estimation of BOLD Signal under Non-Gaussian Noise
Khan, Ali Fahim; Younis, Muhammad Shahzad; Bajwa, Khalid Bashir
2015-01-01
Modeling the blood oxygenation level dependent (BOLD) signal has been a subject of study for over a decade in the neuroimaging community. Inspired from fluid dynamics, the hemodynamic model provides a plausible yet convincing interpretation of the BOLD signal by amalgamating effects of dynamic physiological changes in blood oxygenation, cerebral blood flow and volume. The nonautonomous, nonlinear set of differential equations of the hemodynamic model constitutes the process model while the weighted nonlinear sum of the physiological variables forms the measurement model. Plagued by various noise sources, the time series fMRI measurement data is mostly assumed to be affected by additive Gaussian noise. Though more feasible, the assumption may cause the designed filter to perform poorly if made to work under non-Gaussian environment. In this paper, we present a data assimilation scheme that assumes additive non-Gaussian noise, namely, the e-mixture noise, affecting the measurements. The proposed filter MAGSF and the celebrated EKF are put to test by performing joint optimal Bayesian filtering to estimate both the states and parameters governing the hemodynamic model under non-Gaussian environment. Analyses using both the synthetic and real data reveal superior performance of the MAGSF as compared to EKF. PMID:25691911
Gaussian white noise analysis and its application to Feynman path integral
NASA Astrophysics Data System (ADS)
Suryawan, Herry Pribawanto
2016-02-01
In applied science, Gaussian white noise (the time derivative of Brownian motion) is often chosen as a mathematical idealization of phenomena involving sudden and extremely large fluctuations. It is also possible to define and study Gaussian white noise in a mathematically rigorous framework. In this survey paper we review the Gaussian white noise as an object in an infinite dimensional topological vector space. A brief construction of Gaussian white noise space and Gaussian white noise distributions will be presented. Gaussian white noise analysis provides a framework which offers various generalization of concept known from finite dimensional analysis to the infinite dimensional case, among them are differential operators, Fourier transform, and distribution theory. We will also present some recent developments and results on the application of Gaussian white noise theory to Feynman's path integral approach for quantum mechanics.
Numeric Solutions of Dirac-Gursey Spinor Field Equation Under External Gaussian White Noise
NASA Astrophysics Data System (ADS)
Aydogmus, Fatma
2016-06-01
In this paper, we consider the Dirac-Gursey spinor field equation that has particle-like solutions derived classical field equations so-called instantons, formed by using Heisenberg ansatz, under the effect of an additional Gaussian white noise term. Our purpose is to understand how the behavior of spinor-type excited instantons in four dimensions can be affected by noise. Thus, we simulate the phase portraits and Poincaré sections of the obtained system numerically both with and without noise. Recurrence plots are also given for more detailed information regarding the system.
NASA Astrophysics Data System (ADS)
Ganguly, Jayanta; Ghosh, Manas
2014-05-01
We investigate the profiles of diagonal components of frequency-dependent first nonlinear (βxxx and βyyy) optical response of repulsive impurity doped quantum dots. We have assumed a Gaussian function to represent the dopant impurity potential. This study primarily addresses the role of noise on the polarizability components. We have invoked Gaussian white noise consisting of additive and multiplicative characteristics (in Stratonovich sense). The doped system has been subjected to an oscillating electric field of given intensity, and the frequency-dependent first nonlinear polarizabilities are computed. The noise characteristics are manifested in an interesting way in the nonlinear polarizability components. In case of additive noise, the noise strength remains practically ineffective in influencing the optical responses. The situation completely changes with the replacement of additive noise by its multiplicative analog. The replacement enhances the nonlinear optical response dramatically and also causes their maximization at some typical value of noise strength that depends on oscillation frequency.
Ganguly, Jayanta; Ghosh, Manas
2014-05-07
We investigate the profiles of diagonal components of frequency-dependent first nonlinear (β{sub xxx} and β{sub yyy}) optical response of repulsive impurity doped quantum dots. We have assumed a Gaussian function to represent the dopant impurity potential. This study primarily addresses the role of noise on the polarizability components. We have invoked Gaussian white noise consisting of additive and multiplicative characteristics (in Stratonovich sense). The doped system has been subjected to an oscillating electric field of given intensity, and the frequency-dependent first nonlinear polarizabilities are computed. The noise characteristics are manifested in an interesting way in the nonlinear polarizability components. In case of additive noise, the noise strength remains practically ineffective in influencing the optical responses. The situation completely changes with the replacement of additive noise by its multiplicative analog. The replacement enhances the nonlinear optical response dramatically and also causes their maximization at some typical value of noise strength that depends on oscillation frequency.
Response of MDOF strongly nonlinear systems to fractional Gaussian noises.
Deng, Mao-Lin; Zhu, Wei-Qiu
2016-08-01
In the present paper, multi-degree-of-freedom strongly nonlinear systems are modeled as quasi-Hamiltonian systems and the stochastic averaging method for quasi-Hamiltonian systems (including quasi-non-integrable, completely integrable and non-resonant, completely integrable and resonant, partially integrable and non-resonant, and partially integrable and resonant Hamiltonian systems) driven by fractional Gaussian noise is introduced. The averaged fractional stochastic differential equations (SDEs) are derived. The simulation results for some examples show that the averaged SDEs can be used to predict the response of the original systems and the simulation time for the averaged SDEs is less than that for the original systems.
Toward the detection of gravitational waves under non-Gaussian noises I. Locally optimal statistic
YOKOYAMA, Jun’ichi
2014-01-01
After reviewing the standard hypothesis test and the matched filter technique to identify gravitational waves under Gaussian noises, we introduce two methods to deal with non-Gaussian stationary noises. We formulate the likelihood ratio function under weakly non-Gaussian noises through the Edgeworth expansion and strongly non-Gaussian noises in terms of a new method we call Gaussian mapping where the observed marginal distribution and the two-body correlation function are fully taken into account. We then apply these two approaches to Student’s t-distribution which has a larger tails than Gaussian. It is shown that while both methods work well in the case the non-Gaussianity is small, only the latter method works well for highly non-Gaussian case. PMID:25504231
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.
Classical communication in the presence of quantum Gaussian noise (Invited Paper)
NASA Astrophysics Data System (ADS)
Shapiro, Jeffrey H.; Yen, Brent J.; Guha, Saikat; Erkmen, Baris I.
2005-05-01
The classical information capacity of channels that are subject to quantum Gaussian noise is studied. Recent work has established the capacity of the pure-loss channel, as well as bounds on and a conjecture for the capacity of the lossy channel with isotropic-Gaussian excess noise. This work is applied to the pure-loss free-space channel that uses multiple Hermite-Gaussian (HG) or Laguerre-Gaussian (LG) spatial modes to communicate between soft-aperture transmit and receive pupils, and to the lossy channel with anisotropic (colored) Gaussian noise.
Analysis of regularized inversion of data corrupted by white Gaussian noise
NASA Astrophysics Data System (ADS)
Kekkonen, Hanne; Lassas, Matti; Siltanen, Samuli
2014-04-01
Tikhonov regularization is studied in the case of linear pseudodifferential operator as the forward map and additive white Gaussian noise as the measurement error. The measurement model for an unknown function u(x) is \\begin{eqnarray*} m(x) = Au(x) + \\delta \\varepsilon (x), \\end{eqnarray*} where δ > 0 is the noise magnitude. If ɛ was an L2-function, Tikhonov regularization gives an estimate \\begin{eqnarray*} T_\\alpha (m) = \\mathop {{arg\\, min}}_{u\\in H^r} \\big \\lbrace \\Vert A u-m\\Vert _{L^2}^2+ \\alpha \\Vert u\\Vert _{H^r}^2 \\big \\rbrace \\end{eqnarray*} for u where α = α(δ) is the regularization parameter. Here penalization of the Sobolev norm \\Vert u\\Vert _{H^r} covers the cases of standard Tikhonov regularization (r = 0) and first derivative penalty (r = 1). Realizations of white Gaussian noise are almost never in L2, but do belong to Hs with probability one if s < 0 is small enough. A modification of Tikhonov regularization theory is presented, covering the case of white Gaussian measurement noise. Furthermore, the convergence of regularized reconstructions to the correct solution as δ → 0 is proven in appropriate function spaces using microlocal analysis. The convergence of the related finite-dimensional problems to the infinite-dimensional problem is also analysed.
Using Gaussian Processes to Model Noise in Eclipsing Binary Light Curves
NASA Astrophysics Data System (ADS)
Prsa, Andrej; Hambleton, Kelly M.
2017-01-01
The most precise data we have at hand arguably comes from NASA's Kepler mission, for which there is no good flux calibration available since it was designed to measure relative flux changes down to ~20ppm level. Instrumental artifacts thus abound in the data, and they vary with the module, location on the CCD, target brightness, electronic cross-talk, etc. In addition, Kepler's near-uninterrupted mode of observation reveals astrophysical signals and transient phenomena (i.e. spots, flares, protuberances, pulsations, magnetic field features, etc) that are not accounted for in the models. These "nuisance" signals, along with instrumental artifacts, are considered noise when modeling light curves; this noise is highly correlated and it cannot be considered poissonian or gaussian. Detrending non-white noise from light curve data has been an ongoing challenge in modeling eclipsing binary star and exoplanet transit light curves. Here we present an approach using Gaussian Processes (GP) to model noise as part of the overall likelihood function. The likelihood function consists of the eclipsing binary light curve generator PHOEBE, correlated noise model using GP, and a poissonian (shot) noise attributed to the actual stochastic component of the entire noise model. We consider GP parameters and poissonian noise amplitude as free parameters that are being sampled within the likelihood function, so the end result is the posterior probability not only for eclipsing binary model parameters, but for the noise parameters as well. We show that the posteriors of principal parameters are significantly more robust when noise is modeled rigorously compared to modeling detrended data with an eclipsing binary model alone. This work has been funded by NSF grant #1517460.
On signal design by the R/0/ criterion for non-white Gaussian noise channels
NASA Technical Reports Server (NTRS)
Bordelon, D. L.
1977-01-01
The use of the cut-off rate criterion for modulation system design is investigated for channels with non-white Gaussian noise. A signal space representation of the waveform channel is developed, and the cut-off rate for vector channels with additive non-white Gaussian noise and unquantized demodulation is derived. When the signal input to the channel is a continuous random vector, maximization of the cut-off rate with constrained average signal energy leads to a water-filling interpretation of optimal energy distribution in signal space. The necessary condition for a finite signal set to maximize the cut-off rate with constrained energy and an equally likely probability assignment of signal vectors is presented, and an algorithm is outlined for numerically computing the optimum signal set. As an example, the rectangular signal set which has the water-filling average energy distribution and the optimum rectangular set are compared.
Discriminating additive from dynamical noise for chaotic time series.
Strumik, Marek; Macek, Wiesław M; Redaelli, Stefano
2005-09-01
We consider the dynamics of the Hénon and Ikeda maps in the presence of additive and dynamical noise. We show that, from the point of view of computations of some statistical quantities, dynamical noise corrupting these deterministic systems can be considered effectively as an additive "pseudonoise" with the Cauchy distribution. In the case of the Hénon and Ikeda maps, this effect occurs only for one variable of the system, while the noise corrupting the second variable is still Gaussian distributed independent of distribution of dynamical noise. Based on these results and using scaling properties of the correlation entropy, we propose a simple method of discriminating additive from dynamical noise. This approach is also useful for estimation of noise level for chaotic time series. We show that the proposed method works well in a wide range of noise levels, providing that one kind of noise predominates and we analyze the variable of the system for which the contamination follows Cauchy-like distribution in the presence of dynamical noise.
Non-stationary noise estimation using dictionary learning and Gaussian mixture models
NASA Astrophysics Data System (ADS)
Hughes, James M.; Rockmore, Daniel N.; Wang, Yang
2014-02-01
Stationarity of the noise distribution is a common assumption in image processing. This assumption greatly simplifies denoising estimators and other model parameters and consequently assuming stationarity is often a matter of convenience rather than an accurate model of noise characteristics. The problematic nature of this assumption is exacerbated in real-world contexts, where noise is often highly non-stationary and can possess time- and space-varying characteristics. Regardless of model complexity, estimating the parameters of noise dis- tributions in digital images is a difficult task, and estimates are often based on heuristic assumptions. Recently, sparse Bayesian dictionary learning methods were shown to produce accurate estimates of the level of additive white Gaussian noise in images with minimal assumptions. We show that a similar model is capable of accu- rately modeling certain kinds of non-stationary noise processes, allowing for space-varying noise in images to be estimated, detected, and removed. We apply this modeling concept to several types of non-stationary noise and demonstrate the model's effectiveness on real-world problems, including denoising and segmentation of images according to noise characteristics, which has applications in image forensics.
Lifting primordial non-Gaussianity above the noise
NASA Astrophysics Data System (ADS)
Welling, Yvette; van der Woude, Drian; Pajer, Enrico
2016-08-01
Primordial non-Gaussianity (PNG) in Large Scale Structures is obfuscated by the many additional sources of non-linearity. Within the Effective Field Theory approach to Standard Perturbation Theory, we show that matter non-linearities in the bispectrum can be modeled sufficiently well to strengthen current bounds with near future surveys, such as Euclid. We find that the EFT corrections are crucial to this improvement in sensitivity. Yet, our understanding of non-linearities is still insufficient to reach important theoretical benchmarks for equilateral PNG, while, for local PNG, our forecast is more optimistic. We consistently account for the theoretical error intrinsic to the perturbative approach and discuss the details of its implementation in Fisher forecasts.
NASA Astrophysics Data System (ADS)
Ganguly, Jayanta; Saha, Surajit; Pal, Suvajit; Ghosh, Manas
2016-03-01
We perform a meticulous analysis of profiles of third-order nonlinear optical susceptibility (TONOS) of impurity doped quantum dots (QDs) in the presence and absence of noise. We have invoked Gaussian white noise in the present study and noise has been introduced to the system additively and multiplicatively. The QD is doped with a Gaussian impurity. A magnetic field applied perpendicularly serves as a confinement source and the doped system has been exposed to a static external electric field. The TONOS profiles have been monitored against a continuous variation of incident photon energy when several important parameters such as electric field strength, magnetic field strength, confinement energy, dopant location, Al concentration, dopant potential, relaxation time, anisotropy, and noise strength assume different values. Moreover, the influence of mode of introduction of noise (additive/multiplicative) on the TONOS profiles has also been addressed. The said profiles are found to be consisting of interesting observations such as shift of TONOS peak position and maximization/minimization of TONOS peak intensity. The presence of noise alters the features of TONOS profiles and sometimes enhances the TONOS peak intensity from that of noise-free state. Furthermore, the mode of application of noise also often tailors the TONOS profiles in diverse fashions. The observations accentuate the possibility of tuning the TONOS of doped QD systems in the presence of noise.
Morisaki, Soichiro; Yokoyama, Jun'ichi; Eda, Kazunari; Itoh, Yousuke
2016-01-01
We introduce a new analysis method to deal with stationary non-Gaussian noises in gravitational wave detectors in terms of the independent component analysis. First, we consider the simplest case where the detector outputs are linear combinations of the inputs, consisting of signals and various noises, and show that this method may be helpful to increase the signal-to-noise ratio. Next, we take into account the time delay between the inputs and the outputs. Finally, we extend our method to nonlinearly correlated noises and show that our method can identify the coupling coefficients and remove non-Gaussian noises. Although we focus on gravitational wave data analysis, our methods are applicable to the detection of any signals under non-Gaussian noises.
MORISAKI, Soichiro; YOKOYAMA, Jun’ichi; EDA, Kazunari; ITOH, Yousuke
2016-01-01
We introduce a new analysis method to deal with stationary non-Gaussian noises in gravitational wave detectors in terms of the independent component analysis. First, we consider the simplest case where the detector outputs are linear combinations of the inputs, consisting of signals and various noises, and show that this method may be helpful to increase the signal-to-noise ratio. Next, we take into account the time delay between the inputs and the outputs. Finally, we extend our method to nonlinearly correlated noises and show that our method can identify the coupling coefficients and remove non-Gaussian noises. Although we focus on gravitational wave data analysis, our methods are applicable to the detection of any signals under non-Gaussian noises. PMID:27725472
Quantum error correction of continuous-variable states against Gaussian noise
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)
Sarkar, Sucharita; Ghosh, Arghya Pratim; Mandal, Arkajit; Ghosh, Manas
2016-02-01
The influence of anisotropy on various nonlinear optical (NLO) properties such as total optical absorption coefficient (TOAC), nonlinear optical rectification (NOR), second harmonic generation (SHG) and third harmonic generation (THG) of impurity doped quantum dots (QDs) have been investigated in presence and absence of noise. Noise has been applied to the system additively and multiplicatively. The impurity potential is modeled by a Gaussian function and the noise applied being Gaussian white noise. A perpendicular magnetic field emerges out as a confinement source and a static external electric field has been applied. Profiles of the optical properties have been monitored as a function of incident photon energy for different values of anisotropy. In this connection the role of mode of application of noise (additive/multiplicative) has also been analysed. The interplay between noise and anisotropy has been found to profoundly affect the NLO properties. The investigation reveals that there are only one or two anisotropy regimes (depending on the particular NLO property under consideration) where noise-induced enhancement of the NLO property can be realized. Thus, anisotropy appears to be the central parameter by which the noise-induced enhancement of NLO properties of doped QD systems can be tailored.
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.
On stochastic differential equations driven by the renormalized square of the Gaussian white noise
NASA Astrophysics Data System (ADS)
Ben Ammou, Bilel Kacem; Lanconelli, Alberto
2015-11-01
We investigate the properties of the Wick square of Gaussian white noises through a new method to perform nonlinear operations on Hida distributions. This method lays in between the Wick product interpretation and the usual definition of nonlinear functions. We prove an Itô-type formula and solve stochastic differential equations driven by the renormalized square of the Gaussian white noise. Our approach works with standard assumptions on the coefficients of the equations, global Lipschitz continuity, and produces existence and uniqueness results in the space where the noise lives. The linear case is studied in details and positivity of the solution is proved.
A study on the Gaussianity and stationarity of the random noise in the seismic exploration
NASA Astrophysics Data System (ADS)
Wang, Dongmei; Li, Yue; Nie, Pengfei
2014-10-01
Seismic exploration is an important means of the resource exploration. With the increasing of the demand for oil, gas and mineral resources, the resources which are easy to explore are reducing. At the same time, the high signal to noise ratio and the high quality seismic data is required with the continuous improvement of the accuracy of seismic exploration. The characteristics of complex noise in the seismic record are needed to be analyzed in detail in order to suppress the random noise and achieve the preserved amplitude processing as much as possible. The paper researches the Gaussianity and stationarity of the random noise in the seismic exploration of land area in China. The research areas are plain with sandstone structure. First, a theoretical model verifies the effectiveness that the Shapiro-Wilk test method is used in Gaussian statistical research, and the combination of surrogate data and time-frequency analysis tests stationarity. Then, there are 98.54% of the record channels which refuse the assumption of the Gaussian noise, and 25.6% of the record channels which don't meet the stationarity noise analysis by the above method in the research area through the statistical analysis of the seismic noise. Finally, we discuss the causes of non-Gaussianity and quasi-stationarity, and analyze the application of judging the stationarity in the denoising processing.
Suboptimal Threshold Detection in Narrowband Non-Gaussian Noise,
1983-01-01
noise," optimum nonlinearity g; for the PDF containing just Proc. 7Wznfirth An. AfLe,-on Cbnf. Cbmm . Con- the first two terms (i.e., f (o) as in (5...S. D. Middleton. "Man-made noise in urban environ- ments and transportation systems." IEEE 71mons. Cbmm .. VoL COM-Zl. pp. 1232-1241. Nov. 1973. 9
NASA Astrophysics Data System (ADS)
Brádler, Kamil
2015-03-01
We prove that whenever the coherent information of a one-mode Gaussian (OMG) channel is non-zero its supremum is achieved for the infinite input power. This is a well established fact for zero added classical noise, whereas the non-zero case has not been studied in detail. The presented analysis fills the gap for three canonical classes of OMG channels: the lossy, amplifying and additive classical noise channel class. For the remaining OMG channel classes the coherent information is known to vanish.
A feedback control strategy for the airfoil system under non-Gaussian colored noise excitation.
Huang, Yong; Tao, Gang
2014-09-01
The stability of a binary airfoil with feedback control under stochastic disturbances, a non-Gaussian colored noise, is studied in this paper. First, based on some approximated theories and methods the non-Gaussian colored noise is simplified to an Ornstein-Uhlenbeck process. Furthermore, via the stochastic averaging method and the logarithmic polar transformation, one dimensional diffusion process can be obtained. At last by applying the boundary conditions, the largest Lyapunov exponent which can determine the almost-sure stability of the system and the effective region of control parameters is calculated.
A feedback control strategy for the airfoil system under non-Gaussian colored noise excitation
Huang, Yong E-mail: taogang@njust.edu.cn; Tao, Gang E-mail: taogang@njust.edu.cn
2014-09-01
The stability of a binary airfoil with feedback control under stochastic disturbances, a non-Gaussian colored noise, is studied in this paper. First, based on some approximated theories and methods the non-Gaussian colored noise is simplified to an Ornstein-Uhlenbeck process. Furthermore, via the stochastic averaging method and the logarithmic polar transformation, one dimensional diffusion process can be obtained. At last by applying the boundary conditions, the largest Lyapunov exponent which can determine the almost-sure stability of the system and the effective region of control parameters is calculated.
Discontinuous transitions in globally coupled potential systems with additive noise
NASA Astrophysics Data System (ADS)
Kürsten, Rüdiger; Behn, Ulrich
2016-12-01
An infinite array of globally coupled overdamped constituents moving in a double-well potential with n th order saturation term under the influence of additive Gaussian white noise is investigated. The system exhibits a continuous phase transition from a symmetric phase to a symmetry-broken phase. The qualitative behavior is independent on n . The critical point is calculated for strong and for weak noise; these limits are also bounds for the critical point. Introducing an additional nonlinearity, such that the potential can have up to three minima, leads to richer behavior. There the parameter space divides into three regions: a region with a symmetric phase, a region with a phase of broken symmetry and a region where both phases coexist. The region of coexistence collapses into one of the others via a discontinuous phase transition, whereas the transition between the symmetric phase and the phase of broken symmetry is continuous. The tricritical point where the three regions intersect can be calculated for strong and for weak noise. These limiting values form tight bounds on the tricritical point. In the region of coexistence simulations of finite systems are performed. One finds that the stationary distribution of finite but large systems differs qualitatively from the one of the infinite system. Hence the limits of stationarity and large system size do not commute.
Comparison of Bistable Systems and Matched Filters in Non-Gaussian Noise
NASA Astrophysics Data System (ADS)
Zhang, Xinming; Yan, Jianfeng; Duan, Fabing
2016-10-01
In this paper, we report that for a weak signal buried in the heavy-tailed noise, the bistable system can outperform the matched filter, yielding a higher output signal-to-noise ratio (SNR) or a lower probability of error. Moreover, by adding mutually independent internal noise components to an array of bistable systems, the output SNR or the probability of error can be further improved via the mechanism of stochastic resonance (SR). These comparison results demonstrate the potential capability of bistable systems for detecting weak signals in non-Gaussian noise environments.
Threshold Detection in Narrowband Non-Gaussian Noise.
1983-03-01
Middleton, "Man-made noise in urban environments and transpor- tation systems," IEEE Thwis. Cbmm ., Vol. COM-21, pp. 1232-1241, Nov. 1973. 9. D. Middleton...Coherent detection" IEEE Trw. Cbmm ., Vol. COM-25, No. 9, pp. 910-923, September 1977. 12. D. Middleton, "Procedures for determining the parameters of
Mixed Gaussian-Impulse Noise Image Restoration Via Total Variation
2012-05-01
pp. 402–407. [12] L. Rudin , S. Osher, and E. Fatemi, “Nonlinear total vari- ation based noise removal algorithms.,” Physica D. Non- lin. Phenomena...variation regularization in positron emission tomography,” UCLA CAM Report 98-48, 1998, CAM Report 98-48, UCLA. [16] S. Osher, N. Paragios, L. Rudin , and P
NASA Technical Reports Server (NTRS)
Cheung, K. M.; Vilnrotter, V.
1996-01-01
A closed-form expression for the capacity of an array of correlated Gaussian channels is derived. It is shown that when signal and noise are independent, the array of observables can be replaced with a single observable without diminishing the capacity of the array channel. Examples are provided to illustrate the dependence of channel capacity on noise correlation for two- and three-channel arrays.
Minimal model of stochastic athermal systems: origin of non-Gaussian noise.
Kanazawa, Kiyoshi; Sano, Tomohiko G; Sagawa, Takahiro; Hayakawa, Hisao
2015-03-06
For a wide class of stochastic athermal systems, we derive Langevin-like equations driven by non-Gaussian noise, starting from master equations and developing a new asymptotic expansion. We found an explicit condition whereby the non-Gaussian properties of the athermal noise become dominant for tracer particles associated with both thermal and athermal environments. Furthermore, we derive an inverse formula to infer microscopic properties of the athermal bath from the statistics of the tracer particle. We apply our formulation to a granular motor under viscous friction and analytically obtain the angular velocity distribution function. Our theory demonstrates that the non-Gaussian Langevin equation is the minimal model of athermal systems.
An unbiased risk estimator for image denoising in the presence of mixed poisson-gaussian noise.
Le Montagner, Yoann; Angelini, Elsa D; Olivo-Marin, Jean-Christophe
2014-03-01
The behavior and performance of denoising algorithms are governed by one or several parameters, whose optimal settings depend on the content of the processed image and the characteristics of the noise, and are generally designed to minimize the mean squared error (MSE) between the denoised image returned by the algorithm and a virtual ground truth. In this paper, we introduce a new Poisson-Gaussian unbiased risk estimator (PG-URE) of the MSE applicable to a mixed Poisson-Gaussian noise model that unifies the widely used Gaussian and Poisson noise models in fluorescence bioimaging applications. We propose a stochastic methodology to evaluate this estimator in the case when little is known about the internal machinery of the considered denoising algorithm, and we analyze both theoretically and empirically the characteristics of the PG-URE estimator. Finally, we evaluate the PG-URE-driven parametrization for three standard denoising algorithms, with and without variance stabilizing transforms, and different characteristics of the Poisson-Gaussian noise mixture.
Adaptive subspace detection of extended target in white Gaussian noise using sinc basis
NASA Astrophysics Data System (ADS)
Zhang, Xiao-Wei; Li, Ming; Qu, Jian-She; Yang, Hui
2016-01-01
For the high resolution radar (HRR), the problem of detecting the extended target is considered in this paper. Based on a single observation, a new two-step detection based on sparse representation (TSDSR) method is proposed to detect the extended target in the presence of Gaussian noise with unknown covariance. In the new method, the Sinc dictionary is introduced to sparsely represent the high resolution range profile (HRRP). Meanwhile, adaptive subspace pursuit (ASP) is presented to recover the HRRP embedded in the Gaussian noise and estimate the noise covariance matrix. Based on the Sinc dictionary and the estimated noise covariance matrix, one step subspace detector (OSSD) for the first-order Gaussian (FOG) model without secondary data is adopted to realise the extended target detection. Finally, the proposed TSDSR method is applied to raw HRR data. Experimental results demonstrate that HRRPs of different targets can be sparsely represented very well with the Sinc dictionary. Moreover, the new method can estimate the noise power with tiny errors and have a good detection performance.
NASA Technical Reports Server (NTRS)
Blasche, P. R.
1980-01-01
Specific configurations of first and second order all digital phase locked loops are analyzed for both ideal and additive white gaussian noise inputs. In addition, a design for a hardware digital phase locked loop capable of either first or second order operation is presented along with appropriate experimental data obtained from testing of the hardware loop. All parameters chosen for the analysis and the design of the digital phase locked loop are consistent with an application to an Omega navigation receiver although neither the analysis nor the design are limited to this application.
An Improved Detection Method for Hyperspectral Imagery Based on White Gaussian Noise.
Wang, Yiting; Huang, Shiqi; Wang, Hongxia; Liu, Daizhi
2015-07-01
To solve the low detection efficiency of the present hyperspectral detection method based on adaptive coherence estimator (ACE), an improved detection method based on white Gaussian noise (WGN) is proposed in this paper. Primarily the method uses the spectral angle mapping (SAM) method to adaptively set an optimal signal-to-noise (SNR) parameter based on the hyperspectral image. Then, a corresponding white Gaussian noise is generated according to this SNR parameter and is added to the original image to get a new image data. Finally, based on the new image data, a better target detection result can be obtained by using the ACE detection algorithm. The image data, added to the white Gaussian noise, are more consistent with the theoretical hypotheses of the ACE algorithm. Therefore the detection performance of the algorithm can be efficiently improved. Meanwhile, the adaptivity of setting the optimum SNR parameter in various images can make the method more universal. Experimental results of real world hyperspectral data show that the proposed ACE-WGN method can effectively improve detection performance.
Absolute judgment for one- and two-dimensional stimuli embedded in Gaussian noise
NASA Technical Reports Server (NTRS)
Kvalseth, T. O.
1977-01-01
This study examines the effect on human performance of adding Gaussian noise or disturbance to the stimuli in absolute judgment tasks involving both one- and two-dimensional stimuli. For each selected stimulus value (both an X-value and a Y-value were generated in the two-dimensional case), 10 values (or 10 pairs of values in the two-dimensional case) were generated from a zero-mean Gaussian variate, added to the selected stimulus value and then served as the coordinate values for the 10 points that were displayed sequentially on a CRT. The results show that human performance, in terms of the information transmitted and rms error as functions of stimulus uncertainty, was significantly reduced as the noise variance increased.
Canales-Rodríguez, Erick J; Daducci, Alessandro; Sotiropoulos, Stamatios N; Caruyer, Emmanuel; Aja-Fernández, Santiago; Radua, Joaquim; Yurramendi Mendizabal, Jesús M; Iturria-Medina, Yasser; Melie-García, Lester; Alemán-Gómez, Yasser; Thiran, Jean-Philippe; Sarró, Salvador; Pomarol-Clotet, Edith; Salvador, Raymond
2015-01-01
Spherical deconvolution (SD) methods are widely used to estimate the intra-voxel white-matter fiber orientations from diffusion MRI data. However, while some of these methods assume a zero-mean Gaussian distribution for the underlying noise, its real distribution is known to be non-Gaussian and to depend on many factors such as the number of coils and the methodology used to combine multichannel MRI signals. Indeed, the two prevailing methods for multichannel signal combination lead to noise patterns better described by Rician and noncentral Chi distributions. Here we develop a Robust and Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD) technique, intended to deal with realistic MRI noise, based on a Richardson-Lucy (RL) algorithm adapted to Rician and noncentral Chi likelihood models. To quantify the benefits of using proper noise models, RUMBA-SD was compared with dRL-SD, a well-established method based on the RL algorithm for Gaussian noise. Another aim of the study was to quantify the impact of including a total variation (TV) spatial regularization term in the estimation framework. To do this, we developed TV spatially-regularized versions of both RUMBA-SD and dRL-SD algorithms. The evaluation was performed by comparing various quality metrics on 132 three-dimensional synthetic phantoms involving different inter-fiber angles and volume fractions, which were contaminated with noise mimicking patterns generated by data processing in multichannel scanners. The results demonstrate that the inclusion of proper likelihood models leads to an increased ability to resolve fiber crossings with smaller inter-fiber angles and to better detect non-dominant fibers. The inclusion of TV regularization dramatically improved the resolution power of both techniques. The above findings were also verified in human brain data.
Canales-Rodríguez, Erick J.; Caruyer, Emmanuel; Aja-Fernández, Santiago; Radua, Joaquim; Yurramendi Mendizabal, Jesús M.; Iturria-Medina, Yasser; Melie-García, Lester; Alemán-Gómez, Yasser; Thiran, Jean-Philippe; Sarró, Salvador; Pomarol-Clotet, Edith; Salvador, Raymond
2015-01-01
Spherical deconvolution (SD) methods are widely used to estimate the intra-voxel white-matter fiber orientations from diffusion MRI data. However, while some of these methods assume a zero-mean Gaussian distribution for the underlying noise, its real distribution is known to be non-Gaussian and to depend on many factors such as the number of coils and the methodology used to combine multichannel MRI signals. Indeed, the two prevailing methods for multichannel signal combination lead to noise patterns better described by Rician and noncentral Chi distributions. Here we develop a Robust and Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD) technique, intended to deal with realistic MRI noise, based on a Richardson-Lucy (RL) algorithm adapted to Rician and noncentral Chi likelihood models. To quantify the benefits of using proper noise models, RUMBA-SD was compared with dRL-SD, a well-established method based on the RL algorithm for Gaussian noise. Another aim of the study was to quantify the impact of including a total variation (TV) spatial regularization term in the estimation framework. To do this, we developed TV spatially-regularized versions of both RUMBA-SD and dRL-SD algorithms. The evaluation was performed by comparing various quality metrics on 132 three-dimensional synthetic phantoms involving different inter-fiber angles and volume fractions, which were contaminated with noise mimicking patterns generated by data processing in multichannel scanners. The results demonstrate that the inclusion of proper likelihood models leads to an increased ability to resolve fiber crossings with smaller inter-fiber angles and to better detect non-dominant fibers. The inclusion of TV regularization dramatically improved the resolution power of both techniques. The above findings were also verified in human brain data. PMID:26470024
NASA Astrophysics Data System (ADS)
Edwards, Darrin C.; Kupinski, Matthew A.; Nishikawa, Robert M.; Metz, Charles E.
2000-04-01
We extend a method for linear template estimation developed by Abbey et al. which demonstrated that a linear observer template can be estimated effectively through a two- alternative forced choice (2AFC) experiment, assuming the noise in the images is Gaussian, or multivariate normal (MVN). We relax this assumption, allowing the noise in the images to be drawn from a weighted sum of MVN distributions, which we call a multi-peaked MVN (MPMVN) distribution. Our motivation is that more complicated probability density functions might be approximated in general by such MPMVN distributions. Our extension of Abbey et al.'s method requires us to impose the additional constraint that the covariance matrices of the component peaks of the signal-present noise distribution all be equal, and that the covariance matrices of the component peaks of the signal-absent noise distribution all be equal (but different in general from the signal-present covariance matrices). Preliminary research shows that our generalized method is capable of producing unbiased estimates of linear observer templates in the presence of MPMVN noise under the stated assumptions. We believe this extension represents a next step toward the general treatment of arbitrary image noise distributions.
Modified periodogram method for estimating the Hurst exponent of fractional Gaussian noise.
Liu, Yingjun; Liu, Yong; Wang, Kun; Jiang, Tianzi; Yang, Lihua
2009-12-01
Fractional Gaussian noise (fGn) is an important and widely used self-similar process, which is mainly parametrized by its Hurst exponent (H) . Many researchers have proposed methods for estimating the Hurst exponent of fGn. In this paper we put forward a modified periodogram method for estimating the Hurst exponent based on a refined approximation of the spectral density function. Generalizing the spectral exponent from a linear function to a piecewise polynomial, we obtained a closer approximation of the fGn's spectral density function. This procedure is significant because it reduced the bias in the estimation of H . Furthermore, the averaging technique that we used markedly reduced the variance of estimates. We also considered the asymptotical unbiasedness of the method and derived the upper bound of its variance and confidence interval. Monte Carlo simulations showed that the proposed estimator was superior to a wavelet maximum likelihood estimator in terms of mean-squared error and was comparable to Whittle's estimator. In addition, a real data set of Nile river minima was employed to evaluate the efficiency of our proposed method. These tests confirmed that our proposed method was computationally simpler and faster than Whittle's estimator.
Modified periodogram method for estimating the Hurst exponent of fractional Gaussian noise
NASA Astrophysics Data System (ADS)
Liu, Yingjun; Liu, Yong; Wang, Kun; Jiang, Tianzi; Yang, Lihua
2009-12-01
Fractional Gaussian noise (fGn) is an important and widely used self-similar process, which is mainly parametrized by its Hurst exponent (H) . Many researchers have proposed methods for estimating the Hurst exponent of fGn. In this paper we put forward a modified periodogram method for estimating the Hurst exponent based on a refined approximation of the spectral density function. Generalizing the spectral exponent from a linear function to a piecewise polynomial, we obtained a closer approximation of the fGn’s spectral density function. This procedure is significant because it reduced the bias in the estimation of H . Furthermore, the averaging technique that we used markedly reduced the variance of estimates. We also considered the asymptotical unbiasedness of the method and derived the upper bound of its variance and confidence interval. Monte Carlo simulations showed that the proposed estimator was superior to a wavelet maximum likelihood estimator in terms of mean-squared error and was comparable to Whittle’s estimator. In addition, a real data set of Nile river minima was employed to evaluate the efficiency of our proposed method. These tests confirmed that our proposed method was computationally simpler and faster than Whittle’s estimator.
A median-Gaussian filtering framework for Moiré pattern noise removal from X-ray microscopy image.
Wei, Zhouping; Wang, Jian; Nichol, Helen; Wiebe, Sheldon; Chapman, Dean
2012-02-01
Moiré pattern noise in Scanning Transmission X-ray Microscopy (STXM) imaging introduces significant errors in qualitative and quantitative image analysis. Due to the complex origin of the noise, it is difficult to avoid Moiré pattern noise during the image data acquisition stage. In this paper, we introduce a post-processing method for filtering Moiré pattern noise from STXM images. This method includes a semi-automatic detection of the spectral peaks in the Fourier amplitude spectrum by using a local median filter, and elimination of the spectral noise peaks using a Gaussian notch filter. The proposed median-Gaussian filtering framework shows good results for STXM images with the size of power of two, if such parameters as threshold, sizes of the median and Gaussian filters, and size of the low frequency window, have been properly selected.
Non-Gaussian resistance noise in misfit layer compounds: Bi-Se-Cr
NASA Astrophysics Data System (ADS)
Peng, Lintao; Freedman, Alex; Clarke, Samantha; Freedman, Danna; Grayson, M.
Misfit layer ternary compounds Bi-Se-Cr have been synthesized and structurally and magnetically characterized. However, the nature of the magnetic ordering below the transition temperature remains debatable between ferromagnetic and spin-glass. These misfit layer compounds consist of two alternating chalcogenide layers of CrSe2 and BiSe along the c-axis. Whereas the a-axis is lattice matched, the lattice mismatch along the b-axis introduces non-periodic modulation of atomic position leading to quasi-crystalline order along the b-axis alone. We explore unconventional electrical transport properties in the noise spectrum of these compounds. After thinning down the compounds to nanoscale, Van der Pauw devices are fabricated with standard electron beam lithography process. Large resistance noise was observed at temperature below the Cure temperature. The magnitude of resistance noise is much greater than trivial intrinsic noises like thermal Johnson noise and increases as temperature decreases. The probability density function of the relative noise shows 2-4 peaks among different observations which indicate strong non-Gaussian statistic property suggesting glassy behaviors in this material.
Optimal inversion of the generalized Anscombe transformation for Poisson-Gaussian noise.
Mäkitalo, Markku; Foi, Alessandro
2013-01-01
Many digital imaging devices operate by successive photon-to-electron, electron-to-voltage, and voltage-to-digit conversions. These processes are subject to various signal-dependent errors, which are typically modeled as Poisson-Gaussian noise. The removal of such noise can be effected indirectly by applying a variance-stabilizing transformation (VST) to the noisy data, denoising the stabilized data with a Gaussian denoising algorithm, and finally applying an inverse VST to the denoised data. The generalized Anscombe transformation (GAT) is often used for variance stabilization, but its unbiased inverse transformation has not been rigorously studied in the past. We introduce the exact unbiased inverse of the GAT and show that it plays an integral part in ensuring accurate denoising results. We demonstrate that this exact inverse leads to state-of-the-art results without any notable increase in the computational complexity compared to the other inverses. We also show that this inverse is optimal in the sense that it can be interpreted as a maximum likelihood inverse. Moreover, we thoroughly analyze the behavior of the proposed inverse, which also enables us to derive a closed-form approximation for it. This paper generalizes our work on the exact unbiased inverse of the Anscombe transformation, which we have presented earlier for the removal of pure Poisson noise.
Mu, Tingkui; Chen, Zeyu; Zhang, Chunmin; Liang, Rongguang
2016-12-26
In this paper, the design, optimization and analysis of broadband full-Stokes polarimeters with immunity to both Poisson and Gaussian noise are presented. Different from the commonly-used optimization metrics such as, the condition number (CN), the equally weighted variance (EWV), or the polarimetric modulation efficiency (PME) for Gaussian noise, the optimally balanced condition for Poisson noise (BCPN) is, for the first time, proposed and used as a metric for the optimization of polarimeters. The numerical results show that the polarimeters optimized with the BCPN have immunity to both Poisson and Gaussian noise. The broadband polarimeters optimized from the BCPN are achromatic and have similar polarimetric modulation properties over the waveband, in contrast to the polychromatic polarimeters optimized from the CN, EWV and PME, whose polarimetric modulation properties vary with wavelength.
Temporal and spectral effects in the auditory discrimination of Gaussian noise samples
NASA Astrophysics Data System (ADS)
Rickert, Martin Erhard
1998-10-01
This thesis considers the ability of human listeners to discriminate among samples from a particular class of random signals: band-limited Gaussian noise. Two psychophysical experiments were performed to study how discriminability depends on the temporal and spectral characteristics of the noise. In Experiment 1, there was within-sample homogeneity with respect to the long-term power spectrum of the noise; each sample was identically band-pass filtered throughout. It was observed that discriminability is better for conditions in which the temporal fine-structures of the waveforms differ near the end rather than at the beginning. The magnitude of this effect depends on the bandwidth of the external noise process but not to the extent predicted by optimal statistical integration across frequency and time. In Experiment 2, there was within- segment homogeneity on either side of a temporal boundary; each sample contained an abrupt transition from one bandwidth to another. There was no direct evidence that listeners could use transitions in bandwidth to perceptually segment the correlated and uncorrelated segments of the noise sample. In fact, the form of the psychometric functions measured using nonstationary samples was similar to that seen in the stationary narrowband conditions. The implication is that, if any part of the waveform is narrowband, listeners listen narrowband. A psychoacoustical model for the discrimination of noise is developed in the second part of the thesis. This model describes the ``effective'' signal processing underlying the ability to discriminate noise. Two stages of processing are assumed. During the first stage, each noise signal is jittered by multiplicative internal noise, band-pass filtered, subjected to a non-linearity, then smoothed using a low-pass filter with a relatively short time constant. During the second stage, the internal representations of the noise signals are compared by subtraction, squared, then passed through a low
Vanin, Evgeny; Jacobsen, Gunnar; Berntson, Anders
2007-06-15
We propose a novel method for effective simulation of optical fiber transmission system performance with nonlinear interaction between the amplified spontaneous emission noise and the modulated optical signal employing on-off keying. The method enables a standard analytical description of the receiver operation even when the detected optical field obeys non-Gaussian statistics with a substantial amount of nonlinear phase noise accumulated along the fiber link due to strong signal-noise interaction.
NASA Technical Reports Server (NTRS)
Kalson, S.
1986-01-01
Previous work in the area of choosing channel quantization levels for a additive white Gaussian noise channel composed of one receiver-demodulator is reviewed, and how this applies to the Deep Space Network composed of several receiver-demodulators (space diversity reception) is shown. Viterbi decoding for the resulting quantized channel is discussed.
NASA Technical Reports Server (NTRS)
Simon, M. K.; Huth, G. K.; Polydoros, A.
1982-01-01
Bandwidth-conserving modulation techniques, which trade average power for bandwidth in a favorable exchange, have recently found widespread application in digital radio and satellite communication systems. Quadrature amplitude-shift-keying (QASK) is a particular type of the considered techniques. QASK makes use of multilevel signals to amplitude modulate the in-phase and quadrature components of a carrier. Frequency hopping (FH) is used to protect a conventional communication system from radio frequency interference (RFI) or jamming. Differentially coherent detection provides a possible solution to the effect of phase discontinuities introduced by FH. The application of such a detection technique to QASK signals is discussed. A receiver structure is proposed and its symbol error probability performance for an additive white Gaussian noise (AWGN) background is investigated.
Yang, Sejung; Lee, Byung-Uk
2015-01-01
In certain image acquisitions processes, like in fluorescence microscopy or astronomy, only a limited number of photons can be collected due to various physical constraints. The resulting images suffer from signal dependent noise, which can be modeled as a Poisson distribution, and a low signal-to-noise ratio. However, the majority of research on noise reduction algorithms focuses on signal independent Gaussian noise. In this paper, we model noise as a combination of Poisson and Gaussian probability distributions to construct a more accurate model and adopt the contourlet transform which provides a sparse representation of the directional components in images. We also apply hidden Markov models with a framework that neatly describes the spatial and interscale dependencies which are the properties of transformation coefficients of natural images. In this paper, an effective denoising algorithm for Poisson-Gaussian noise is proposed using the contourlet transform, hidden Markov models and noise estimation in the transform domain. We supplement the algorithm by cycle spinning and Wiener filtering for further improvements. We finally show experimental results with simulations and fluorescence microscopy images which demonstrate the improved performance of the proposed approach.
Type-A Worst-Case Uncertainty for Gaussian noise instruments
NASA Astrophysics Data System (ADS)
Arpaia, P.; Baccigalupi, C.; Martino, M.
2015-07-01
An analytical type-A approach is proposed for predicting the Worst-Case Uncertainty of a measurement system. In a set of independent observations of the same measurand, modelled as independent- and identically-distributed random variables, the upcoming extreme values (e.g. peaks) can be forecast by only characterizing the measurement system noise level, assumed to be white and Gaussian. Simulation and experimental results are presented to validate the model for a case study on the worst-case repeatability of a pulsed power supply for the klystron modulators of the Compact LInear Collider at CERN. The experimental validation highlights satisfying results for an acquisition system repeatable in the order of ±25 ppm over a bandwidth of 5 MHz.
Modular design and implementation of field-programmable-gate-array-based Gaussian noise generator
NASA Astrophysics Data System (ADS)
Li, Yuan-Ping; Lee, Ta-Sung; Hwang, Jeng-Kuang
2016-05-01
The modular design of a Gaussian noise generator (GNG) based on field-programmable gate array (FPGA) technology was studied. A new range reduction architecture was included in a series of elementary function evaluation modules and was integrated into the GNG system. The approximation and quantisation errors for the square root module with a first polynomial approximation were high; therefore, we used the central limit theorem (CLT) to improve the noise quality. This resulted in an output rate of one sample per clock cycle. We subsequently applied Newton's method for the square root module, thus eliminating the need for the use of the CLT because applying the CLT resulted in an output rate of two samples per clock cycle (>200 million samples per second). Two statistical tests confirmed that our GNG is of high quality. Furthermore, the range reduction, which is used to solve a limited interval of the function approximation algorithms of the System Generator platform using Xilinx FPGAs, appeared to have a higher numerical accuracy, was operated at >350 MHz, and can be suitably applied for any function evaluation.
Xiao, Yanwen; Xu, Wei; Wang, Liang
2016-03-01
This paper focuses on the study of the stochastic Van der Pol vibro-impact system with fractional derivative damping under Gaussian white noise excitation. The equations of the original system are simplified by non-smooth transformation. For the simplified equation, the stochastic averaging approach is applied to solve it. Then, the fractional derivative damping term is facilitated by a numerical scheme, therewith the fourth-order Runge-Kutta method is used to obtain the numerical results. And the numerical simulation results fit the analytical solutions. Therefore, the proposed analytical means to study this system are proved to be feasible. In this context, the effects on the response stationary probability density functions (PDFs) caused by noise excitation, restitution condition, and fractional derivative damping are considered, in addition the stochastic P-bifurcation is also explored in this paper through varying the value of the coefficient of fractional derivative damping and the restitution coefficient. These system parameters not only influence the response PDFs of this system but also can cause the stochastic P-bifurcation.
NASA Astrophysics Data System (ADS)
Hao, Meng-Li; Xu, Wei; Li, Dong-Xi; Liu, Di
2014-05-01
The extinction phenomenon induced by multiplicative non-Gaussian Lévy noise in a tumor growth model with immune response is discussed. Under the influence of the stochastic immune rate, the model is analyzed in terms of a stochastic differential equation with multiplicative noise. By means of the theory of the infinitesimal generator of Hunt processes, the escape probability, which is used to measure the noise-induced extinction probability of tumor cells, is explicitly expressed as a function of initial tumor cell density, stability index and noise intensity. Based on the numerical calculations, it is found that for different initial densities of tumor cells, noise parameters play opposite roles on the escape probability. The optimally selected values of the multiplicative noise intensity and the stability index are found to maximize the escape probability.
The spectra and periodograms of anti-correlated discrete fractional Gaussian noise.
Raymond, G M; Percival, D B; Bassingthwaighte, J B
2003-05-01
Discrete fractional Gaussian noise (dFGN) has been proposed as a model for interpreting a wide variety of physiological data. The form of actual spectra of dFGN for frequencies near zero varies as f(1-2H), where 0 < H < 1 is the Hurst coefficient; however, this form for the spectra need not be a good approximation at other frequencies. When H approaches zero, dFGN spectra exhibit the 1 - 2H power-law behavior only over a range of low frequencies that is vanishingly small. When dealing with a time series of finite length drawn from a dFGN process with unknown H, practitioners must deal with estimated spectra in lieu of actual spectra. The most basic spectral estimator is the periodogram. The expected value of the periodogram for dFGN with small H also exhibits non-power-law behavior. At the lowest Fourier frequencies associated with a time series of N values sampled from a dFGN process, the expected value of the periodogram for H approaching zero varies as f(0) rather than f(1-2H). For finite N and small H, the expected value of the periodogram can in fact exhibit a local power-law behavior with a spectral exponent of 1 - 2H at only two distinct frequencies.
NASA Astrophysics Data System (ADS)
Yalim, Jason; Welfert, Bruno D.; Lopez, Juan M.
2017-03-01
The response of a Duffing oscillator subject to a periodic forcing with slowly and stochastically modulated frequency is analyzed numerically. The results of both moment and cumulant-based stochastic reductions are compared to Monte Carlo simulations. It is shown how the explicit characterization of higher-order central moments of the (Gaussian) noise source and the periodic nature of the forcing enable a reliable reduction strategy providing a faithful description of the mean behavior of stochastic solutions. The reduced model is then used to illustrate how a large noise level and fast frequency drift may combine to sustain a strong response that is normally associated to resonance in the noiseless static case.
Capacity of optical communication in loss and noise with general quantum Gaussian receivers
NASA Astrophysics Data System (ADS)
Takeoka, Masahiro; Guha, Saikat
2014-04-01
Laser-light (coherent-state) modulation is sufficient to achieve the ultimate (Holevo) capacity of classical communication over a lossy and noisy optical channel, but requires a receiver that jointly detects long modulated code words with highly nonlinear quantum operations, which are near-impossible to realize using current technology. We analyze the capacity of the lossy-noisy optical channel when the transmitter uses coherent-state modulation but the receiver is restricted to a general quantum-limited Gaussian receiver, i.e., one that may involve arbitrary combinations of Gaussian operations [passive linear optics: beam splitters and phase shifters; second-order nonlinear optics (or active linear optics): squeezers, along with homodyne or heterodyne detection measurements] and any amount of classical feedforward within the receiver. Under these assumptions, we show that the Gaussian receiver that attains the maximum mutual information is either homodyne detection, heterodyne detection, or time sharing between the two, depending upon the received power level. In other words, our result shows that to exceed the theoretical limit of conventional coherent optical communication, one has to incorporate non-Gaussian, i.e., third- or higher-order nonlinear operations in the receiver. Finally we compare our Gaussian receiver limit with experimentally feasible non-Gaussian receivers and show that in the regime of low received photon flux, it is possible to overcome the Gaussian receiver limit by relatively simple non-Gaussian receivers based on photon counting.
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.
NASA Astrophysics Data System (ADS)
Ryu, Ji-Woo; Lee, Seon-Oh; Sim, Dong-Gyu; Han, Jong-Ki
2012-02-01
We present a no-reference peak signal to noise ratio (PSNR) estimation algorithm based on discrete cosine transform (DCT) coefficient distributions from H.264/MPEG-4 part 10 advanced video codec (H.264/AVC) bitstreams. To estimate the PSNR of a compressed picture without the original picture on the decoder side, it is important to model the distribution of transform coefficients obtained from quantized coefficients accurately. Whereas several conventional algorithms use the Laplacian or Cauchy distribution to model the DCT coefficient distribution, the proposed algorithm uses a generalized Gaussian distribution. Pearson's χ2 (chi-square) test was applied to show that the generalized Gaussian distribution is more appropriate than the other models for modeling the transform coefficients. The χ2 test was also used to find optimum parameters for the generalized Gaussian model. It was found that the generalized Gaussian model improves the accuracy of the DCT coefficient distribution, thus reducing the mean squared error between the real and the estimated PSNR.
NASA Astrophysics Data System (ADS)
Molz, F. J.; Liu, H. H.; Szulga, J.
Recent studies have shown that fractional Brownian motion (fBm) and fractional Gaussian noise (fGn) are useful in characterizing subsurface heterogeneities in addition to geophysical time series. Although these studies have led to a fairly good understanding of some aspects of fBm/fGn, a comprehensive introduction to these stochastic, fractal functions is still lacking in the subsurface hydrology literature. In this paper, efforts have been made to define fBm/fGn and present a development of their mathematical properties in a direct yet rigorous manner. Use of the spectral representation theorem allows one to derive spectral representations for fBm/fGn even though these functions do not have classical Fourier transforms. The discrete and truncated forms of these representations have served as a basis for synthetic generation of fBm/fGn. The discrete spectral representations are developed and various implications discussed. In particular, it is shown that a discrete form of the fBm spectral representation is equivalent to the well known Weierstrass-Mandelbrot random fractal function. Although the full implications are beyond the scope of the present paper, it is observed that discrete spectral representations of fBm constitute stationary processes even though fBm is nonstationary. A new and general spectral density function is introduced for construction of complicated, anisotropic, (3-D) fractals, including those characterized by vertical fGn and horizontal fBm. Such fractals are useful for modeling anisotropic subsurface heterogeneities but cannot be generated with existing schemes. Finally, some basic properties of fractional Lévy motion and concepts of universal multifractals, which can be considered as generalizations of fBm/fGn, are reviewed briefly.
Non-Gaussian noise in x-ray and γ-ray detectors
NASA Astrophysics Data System (ADS)
Chen, Liying; Barrett, Harrison H.
2005-04-01
Image statistics are usually modeled as Poisson in γ-ray imaging and as Gaussian in x-ray imaging. In nuclear medicine, event-driven detectors analyze the pulses from every absorbed gamma photon individually; the resulting images rigorously obey Poisson statistics but are approximately Gaussian when the mean number of counts per pixel is large. With integrating detectors, as in digital radiography, each x-ray photon makes a contribution to the image proportional to its pulse height. One pixel senses many photons in long exposures, so the image statistics approach Gaussian by the central limit theorem (CLT). If the exposure time is short enough, however, each pixel will usually respond to no more than one photon, and we can separate individual photons for position estimation. Integrating detectors are therefore event-driven when we use many short-exposure frames rather than one long exposure. In intermediate exposures, the number of photons in one pixel is too small to invoke CLT and apply Gaussian statistics, yet too large to identify individual photons and apply Poisson statistics. In this paper, we analyze the image quality in this intermediate case. Image quality is defined for detection tasks performed by the ideal observer. Because the frames in a data set are independent of each other, the probability density function (PDF) of the whole data set is a product of the frame PDFs. The log-likelihood ratio λ of the ideal observer is thus a sum across the frames and has Gaussian statistics even with non-Gaussian images. We compare the ideal observer's performance with the Hotelling observer's performance under this approximation. A data-thresholding technique to improve Hotelling observer's performance is also discussed.
NASA Technical Reports Server (NTRS)
Reddy, C. P.; Gupta, S. C.
1973-01-01
An all digital phase locked loop which tracks the phase of the incoming sinusoidal signal once per carrier cycle is proposed. The different elements and their functions and the phase lock operation are explained in detail. The nonlinear difference equations which govern the operation of the digital loop when the incoming signal is embedded in white Gaussian noise are derived, and a suitable model is specified. The performance of the digital loop is considered for the synchronization of a sinusoidal signal. For this, the noise term is suitably modelled which allows specification of the output probabilities for the two level quantizer in the loop at any given phase error. The loop filter considered increases the probability of proper phase correction. The phase error states in modulo two-pi forms a finite state Markov chain which enables the calculation of steady state probabilities, RMS phase error, transient response and mean time for cycle skipping.
NASA Astrophysics Data System (ADS)
Bose, Sukanta; Dhurandhar, Sanjeev; Gupta, Anuradha; Lundgren, Andrew
2016-12-01
Gravitational wave signals were recently detected directly by LIGO from the coalescences of two stellar mass black hole pairs. These detections have strengthened our long held belief that compact binary coalescences (CBCs) are the most promising gravitational wave detection prospects accessible to ground-based interferometric detectors. For detecting CBC signals, it is of vital importance to characterize and identify non-Gaussian and nonstationary noise in these detectors. In this work, we model two important classes of transient artifacts that contribute to this noise and adversely affect the detector sensitivity to CBC signals. One of them is the sine-Gaussian "glitch," characterized by a central frequency f0 and a quality factor Q and the other is the chirping sine-Gaussian glitch, which is characterized by f0, Q as well as a chirp parameter. We study the response that a bank of compact binary inspiral templates has to these two families of glitches when they are used to match filter data containing any of these glitches. Two important characteristics of this response are the distributions of the signal-to-noise ratio and the time lag (i.e., how long after the occurrence of a glitch the signal-to-noise ratio of a trigger arises from its matched filtering by a template peaks) of individual templates. We show how these distributions differ from those when the detector data has a real CBC signal instead of a glitch. We argue that these distinctions can be utilized to develop useful signal-artifact discriminators that add negligibly to the computational cost of a CBC search. Specifically, we show how the central frequency of a glitch can be used to set adaptive time windows around it so that any template trigger occurring in that window can be quarantined for further vetting of its supposed astrophysical nature. Second, we recommend focusing efforts on reducing the incidence of glitches with low central-frequency values because they create CBC triggers with the
Additional noise data on the SR-3 propeller
NASA Astrophysics Data System (ADS)
Dittmar, J. H.; Jeracki, R. J.
1981-05-01
The noise generated by supersonic-tip-speed propellers is investigated. An eight bladed propeller was tested in the Lewis 8- by 6-foot wind tunnel with conditions providing data in the subsonic operating region of the propeller. These conditions resulted in a slight reshaping of the curve for blade passing tone as a function of helical tip Mach number as compared with previous results. Directivity curves with an additional transducer position gave an indication of a lobe pattern for this propeller that was not previously observed. The present data at the aft-most position indicate that some reflections, possibly from the test rig support strut, may have affected the data taken previously.
NASA Technical Reports Server (NTRS)
Dembo, Amir
1989-01-01
Pinsker and Ebert (1970) proved that in channels with additive Gaussian noise, feedback at most doubles the capacity. Cover and Pombra (1989) proved that feedback at most adds half a bit per transmission. Following their approach, the author proves that in the limit as signal power approaches either zero (very low SNR) or infinity (very high SNR), feedback does not increase the finite block-length capacity (which for nonstationary Gaussian channels replaces the standard notion of capacity that may not exist). Tighter upper bounds on the capacity are obtained in the process. Specializing these results to stationary channels, the author recovers some of the bounds recently obtained by Ozarow.
NASA Astrophysics Data System (ADS)
Daqaq, Mohammed F.
2011-05-01
In this theoretical study, the response of an inductive power generator with a bistable symmetric potential to stationary random environmental excitations is investigated. Both white and Ornstein-Uhlenbeck-type excitations are considered. In the white noise limit, the stationary Fokker-Plank-Kolmagorov equation is solved for the exact joint probability density function (PDF) of the response. The PDF is then used to obtain analytical expressions for the response statistics. It is shown that the expected value of the generator's output power is independent of the potential shape leading to the conclusion that under white noise excitations, bistabilities in the potential do not provide any enhancement over the traditional linear resonant generators which have a single-well potential. In the case of Ornstein-Uhlenbeck (exponentially correlated) noise, an approximate expression for the mean power of the generator which depends on the potential shape, the generator's design parameters and the noise bandwidth and intensity is obtained. It is shown that there exists an optimal potential shape which maximizes the output power. This optimal shape guarantees an optimal escapement frequency between the potential wells which remains constant even as the noise intensity is varied.
Fuzzy Filtering Method for Color Videos Corrupted by Additive Noise
Ponomaryov, Volodymyr I.; Montenegro-Monroy, Hector; Nino-de-Rivera, Luis
2014-01-01
A novel method for the denoising of color videos corrupted by additive noise is presented in this paper. The proposed technique consists of three principal filtering steps: spatial, spatiotemporal, and spatial postprocessing. In contrast to other state-of-the-art algorithms, during the first spatial step, the eight gradient values in different directions for pixels located in the vicinity of a central pixel as well as the R, G, and B channel correlation between the analogous pixels in different color bands are taken into account. These gradient values give the information about the level of contamination then the designed fuzzy rules are used to preserve the image features (textures, edges, sharpness, chromatic properties, etc.). In the second step, two neighboring video frames are processed together. Possible local motions between neighboring frames are estimated using block matching procedure in eight directions to perform interframe filtering. In the final step, the edges and smoothed regions in a current frame are distinguished for final postprocessing filtering. Numerous simulation results confirm that this novel 3D fuzzy method performs better than other state-of-the-art techniques in terms of objective criteria (PSNR, MAE, NCD, and SSIM) as well as subjective perception via the human vision system in the different color videos. PMID:24688428
Analysis of a first order phase locked loop in the presence of Gaussian noise
NASA Technical Reports Server (NTRS)
Blasche, P. R.
1977-01-01
A first-order digital phase locked loop is analyzed by application of a Markov chain model. Steady state loop error probabilities, phase standard deviation, and mean loop transient times are determined for various input signal to noise ratios. Results for direct loop simulation are presented for comparison.
Estimation and Control for Linear Systems with Additive Cauchy Noise
2013-12-17
In this class, α = 0.5, 1, 2 yield the Lévy, Cauchy and Gaussian distributions , respectively. For α ∈ (0, 2), all the densities have infinite...are in the form of the Cauchy distribution . Although the conditional expectation of the cost function can be determined from the conditional pdf in...inputs are assumed to be independent with know Cauchy pdf. Specifically, wk is assumed to be Cauchy distributed with a zero median and a scaling parameter
NASA Astrophysics Data System (ADS)
Krubsack, David Allan
1990-01-01
This dissertation presents two algorithms that extract parameters which are important to speech processing in high levels of noise. The first algorithm determines whether a signal containing noise corrupted human speech is voiced or not and estimates the fundamental frequency (pitch) of voiced speech. The second algorithm produces an estimate of the additive noise which is corrupting the speech. Previous research related to the voicing decision and pitch estimation has been concentrated at signal-to -noise ratios (SNRs) above 0 dB. Consequently, speech processing requiring the extraction of these parameters in higher levels of noise could not be performed with much success. The research presented in this dissertation concentrates on SNRs around and below 0 dB. Although the algorithm, based on the autocorrelation function, is designed to work well for high levels of noise, good results for the no noise case have been maintained. The idea of a confidence measure for parameter estimation is introduced. Confidence measures are defined and developed for both the voicing decision and the pitch estimation algorithms. Estimation of noise that is corrupting a speech signal has been motivated by the need to enhance the corrupted speech. Previous research has concentrated on speech which is band limited to about 3500 Hz. Therefore, the estimation of the noise corrupting high frequency speech had not been considered. The noise estimation algorithm presented in this dissertation considers the effects of high frequency speech on the noise estimate in addition to the effects of low frequency speech. A new spectral averaging method is introduced which significantly reduces the corrupting effect of the speech components on the noise estimate for SNRs above 0 dB. The algorithm is tested for stationary white noise, stationary non-white noise, and non-stationary white noise.
Noise reduction by continuous addition of subchannel holograms.
Som, S C; Budhiraja, C J
1975-07-01
A new and convenient technique for reducing both speckle and coherent noise in holographic imagery is described with supporting experimental results. Its advantages and disadvantages have been mentioned in the context of other known techniques.
The Electrical Activity of Neurons Subject to Electromagnetic Induction and Gaussian White Noise
NASA Astrophysics Data System (ADS)
Wang, Ya; Ma, Jun; Xu, Ying; Wu, Fuqiang; Zhou, Ping
Neurons can give appropriate response to external electrical stimuli and the modes in electrical activities can be carefully selected. Most of the neuron models mainly emphasize on the ion channel currents embedded into the membrane and the properties in electrical activities can be produced in the theoretical models. Indeed, some physical effect should be considered during the model setting for neuronal activities. In fact, induced current and the electrical field will cause the membrane potential to change and an exchange of charged ions during the fluctuation of ion concentration in cell. As a result, the effect of electromagnetic induction should be seriously considered. In this paper, magnetic flux is proposed to describe the effect of electromagnetic field, and the memristor is used to realize coupling on membrane by inputting induced current based on consensus of physical unit. Noise is also considered to detect the dynamical response in electrical activities and stochastic resonance, it is found that multiple modes can be selected in the electrical activities and it could be associated with memory effect and self-adaption in neurons.
Jin, Lei; Xu, Bo; Yamashita, Shinji
2012-11-19
We theoretically and numerically explain the power saturation and the additional phase noise brought by the fiber optical parametric amplifier (FOPA). An equation to calculate an approximation to the saturated signal output power is presented. We also propose a scheme for alleviating the phase noise brought by the FOPA at the saturated state. In simulation, by controlling the decisive factor dispersion difference term Δk of the FOPA, amplitude-noise and additional phase noise reduction of quadrature phase shift keying (QPSK) based on the saturated FOPA is studied, which can provide promising performance to deal with PSK signals.
Gaussian Decomposition of Laser Altimeter Waveforms
NASA Technical Reports Server (NTRS)
Hofton, Michelle A.; Minster, J. Bernard; Blair, J. Bryan
1999-01-01
We develop a method to decompose a laser altimeter return waveform into its Gaussian components assuming that the position of each Gaussian within the waveform can be used to calculate the mean elevation of a specific reflecting surface within the laser footprint. We estimate the number of Gaussian components from the number of inflection points of a smoothed copy of the laser waveform, and obtain initial estimates of the Gaussian half-widths and positions from the positions of its consecutive inflection points. Initial amplitude estimates are obtained using a non-negative least-squares method. To reduce the likelihood of fitting the background noise within the waveform and to minimize the number of Gaussians needed in the approximation, we rank the "importance" of each Gaussian in the decomposition using its initial half-width and amplitude estimates. The initial parameter estimates of all Gaussians ranked "important" are optimized using the Levenburg-Marquardt method. If the sum of the Gaussians does not approximate the return waveform to a prescribed accuracy, then additional Gaussians are included in the optimization procedure. The Gaussian decomposition method is demonstrated on data collected by the airborne Laser Vegetation Imaging Sensor (LVIS) in October 1997 over the Sequoia National Forest, California.
Schäfer, Joachim; Karpov, Evgueni; Cerf, Nicolas J.
2014-12-04
We seek for a realistic implementation of multimode Gaussian entangled states that can realize the optimal encoding for quantum bosonic Gaussian channels with memory. For a Gaussian channel with classical additive Markovian correlated noise and a lossy channel with non-Markovian correlated noise, we demonstrate the usefulness using Gaussian matrix-product states (GMPS). These states can be generated sequentially, and may, in principle, approximate well any Gaussian state. We show that we can achieve up to 99.9% of the classical Gaussian capacity with GMPS requiring squeezing parameters that are reachable with current technology. This may offer a way towards an experimental realization.
Kastelein, Ronald A; Wensveen, Paul J; Hoek, Lean; Au, Whitlow W L; Terhune, John M; de Jong, Christ A F
2009-09-01
A psychoacoustic behavioral technique was used to determine the critical ratios (CRs) of two harbor porpoises for tonal signals with frequencies between 0.315 and 150 kHz, in random Gaussian white noise. The masked 50% detection hearing thresholds were measured using a "go/no-go" response paradigm and an up-down staircase psychometric method. CRs were determined at one masking noise level for each test frequency and were similar in both animals. For signals between 0.315 and 4 kHz, the CRs were relatively constant at around 18 dB. Between 4 and 150 kHz the CR increased gradually from 18 to 39 dB ( approximately 3.3 dB/octave). Generally harbor porpoises can detect tonal signals in Gaussian white noise slightly better than most odontocetes tested so far. By combining the mean CRs found in the present study with the spectrum level of the background noise levels at sea, the basic audiogram, and the directivity index, the detection threshold levels of harbor porpoises for tonal signals in various sea states can be calculated.
Langevin simulation of scalar fields: Additive and multiplicative noises and lattice renormalization
NASA Astrophysics Data System (ADS)
Cassol-Seewald, N. C.; Farias, R. L. S.; Fraga, E. S.; Krein, G.; Ramos, Rudnei O.
2012-08-01
We consider the Langevin lattice dynamics for a spontaneously broken λϕ4 scalar field theory where both additive and multiplicative noise terms are incorporated. The lattice renormalization for the corresponding stochastic Ginzburg-Landau-Langevin and the subtleties related to the multiplicative noise are investigated.
NASA Astrophysics Data System (ADS)
Wang, Shuai; Hou, Li-Li; Chen, Xian-Feng; Xu, Xue-Fen
2015-06-01
We theoretically analyze the Einstein-Podolsky-Rosen (EPR) correlation, the quadrature squeezing, and the continuous-variable quantum teleportation when considering non-Gaussian entangled states generated by applying multiple-photon subtraction and multiple-photon addition to a two-mode squeezed vacuum state (TMSVs). Our results indicate that in the case of the multiple-photon-subtracted TMSVs with symmetric operations, the corresponding EPR correlation, the two-mode squeezing degree, the sum squeezing, and the fidelity of teleporting a coherent state or a squeezed vacuum state can be enhanced for any squeezing parameter r and these enhancements increase with the number of subtracted photons in the low-squeezing regime, while asymmetric multiple-photon subtractions will generally reduce these quantities. For the multiple-photon-added TMSVs, although it holds stronger entanglement, its EPR correlation, two-mode squeezing, sum squeezing, and the fidelity of a coherent state are always smaller than that of the TMSVs. Only when considering the case of teleporting a squeezed vacuum state does the symmetric photon addition make somewhat of an improvement in the fidelity for large-squeezing parameters. In addition, we analytically prove that a one-mode multiple-photon-subtracted TMSVs is equivalent to that of the one-mode multiple-photon-added one. And one-mode multiple-photon operations will diminish the above four quantities for any squeezing parameter r .
NASA Astrophysics Data System (ADS)
Qiao, Zijian; Lei, Yaguo; Lin, Jing; Niu, Shantao
2016-11-01
The influence of potential asymmetries on stochastic resonance (SR) subject to both multiplicative and additive noise is studied by using two-state theory, where three types of asymmetries are introduced in double-well potential by varying the depth, the width, and both the depth and the width of the left well alone. The characteristics of SR in the asymmetric cases are different from symmetric ones, where asymmetry has a strong influence on output signal-to-noise ratio (SNR) and optimal noise intensity. Even optimal noise intensity is also associated with the steepness of the potential-barrier wall, which is generally ignored. Moreover, the largest SNR in asymmetric SR is found to be relatively larger than the symmetric one, which also closely depends on noise intensity ratio. In addition, a moderate cross-correlation intensity between two noises is good for improving the output SNR. More interestingly, a double SR phenomenon is observed in certain cases for two correlated noises, whereas it disappears for two independent noises. The above clues are helpful in achieving weak signal detection under heavy background noise.
A laboratory study of the perceived benefit of additional noise attenuation by houses
NASA Technical Reports Server (NTRS)
Flindell, I. H.
1983-01-01
Two Experiments were conducted to investigate the perceived benefit of additional house attenuation against aircraft flyover noise. First, subjects made annoyance judgments in a simulated living room while an operative window with real and dummy storm windows was manipulated in full view of those subjects. Second, subjects made annoyance judgments in an anechoic audiometric test chamber of frequency shaped noise signals having spectra closely matched to those of the aircraft flyover noises reproduced in the first experiment. These stimuli represented the aircraft flyover noises in levels and spectra but without the situational and visual cues present in the simulated living room. Perceptual constancy theory implies that annoyance tends to remain constant despite reductions in noise level caused by additional attenuation of which the subjects are fully aware. This theory was supported when account was taken for a reported annoyance overestimation for certain spectra and for a simulated condition cue overreaction.
Spectral models of additive and modulation noise in speech and phonatory excitation signals
NASA Astrophysics Data System (ADS)
Schoentgen, Jean
2003-01-01
The article presents spectral models of additive and modulation noise in speech. The purpose is to learn about the causes of noise in the spectra of normal and disordered voices and to gauge whether the spectral properties of the perturbations of the phonatory excitation signal can be inferred from the spectral properties of the speech signal. The approach to modeling consists of deducing the Fourier series of the perturbed speech, assuming that the Fourier series of the noise and of the clean monocycle-periodic excitation are known. The models explain published data, take into account the effects of supraglottal tremor, demonstrate the modulation distortion owing to vocal tract filtering, establish conditions under which noise cues of different speech signals may be compared, and predict the impossibility of inferring the spectral properties of the frequency modulating noise from the spectral properties of the frequency modulation noise (e.g., phonatory jitter and frequency tremor). The general conclusion is that only phonatory frequency modulation noise is spectrally relevant. Other types of noise in speech are either epiphenomenal, or their spectral effects are masked by the spectral effects of frequency modulation noise.
George: Gaussian Process regression
NASA Astrophysics Data System (ADS)
Foreman-Mackey, Daniel
2015-11-01
George is a fast and flexible library, implemented in C++ with Python bindings, for Gaussian Process regression useful for accounting for correlated noise in astronomical datasets, including those for transiting exoplanet discovery and characterization and stellar population modeling.
Statistical addition method for external noise sources affecting HF-MF-LF systems
NASA Astrophysics Data System (ADS)
Neudegg, David
2001-01-01
The current statistical method for the addition of external component noise sources in the LF, MF, and lower HF band (100 kHz to 3 MHz) produces total median noise levels that may be less than the largest-component median in some cases. Several case studies illustrate this anomaly. Methods used to sum the components rely on their power (decibels) distributions being represented as normal by the statistical parameters. The atmospheric noise component is not correctly represented by its decile values when it is assumed to have a normal distribution, causing anomalies in the noise summation when components are similar in magnitude. A revised component summation method is proposed, and the way it provides a more physically realistic total noise median for LF, MF, and lower HF frequencies is illustrated.
Conditional probability calculations for the nonlinear Schrödinger equation with additive noise.
Terekhov, I S; Vergeles, S S; Turitsyn, S K
2014-12-05
The method for the computation of the conditional probability density function for the nonlinear Schrödinger equation with additive noise is developed. We present in a constructive form the conditional probability density function in the limit of small noise and analytically derive it in a weakly nonlinear case. The general theory results are illustrated using fiber-optic communications as a particular, albeit practically very important, example.
Phase-shifting interferometry corrupted by white and non-white additive noise.
Servin, M; Quiroga, J A; Estrada, J C
2011-05-09
The standard tool to estimate the phase of a sequence of phase-shifted interferograms is the Phase Shifting Algorithm (PSA). The performance of PSAs to a sequence of interferograms corrupted by non-white additive noise has not been reported before. In this paper we use the Frequency Transfer Function (FTF) of a PSA to generalize previous white additive noise analysis to non-white additive noisy interferograms. That is, we find the ensemble average and the variance of the estimated phase in a general PSA when interferograms corrupted by non-white additive noise are available. Moreover, for the special case of additive white-noise, and using the Parseval's theorem, we show (for the first time in the PSA literature) a useful relationship of the PSA's noise robustness; in terms of its FTF spectrum, and in terms of its coefficients. In other words, we find the PSA's estimated phase variance, in the spectral space as well as in the PSA's coefficients space.
Yadav, Ram Bharos; Srivastava, Subodh; Srivastava, Rajeev
2016-01-01
The proposed framework is obtained by casting the noise removal problem into a variational framework. This framework automatically identifies the various types of noise present in the magnetic resonance image and filters them by choosing an appropriate filter. This filter includes two terms: the first term is a data likelihood term and the second term is a prior function. The first term is obtained by minimizing the negative log likelihood of the corresponding probability density functions: Gaussian or Rayleigh or Rician. Further, due to the ill-posedness of the likelihood term, a prior function is needed. This paper examines three partial differential equation based priors which include total variation based prior, anisotropic diffusion based prior, and a complex diffusion (CD) based prior. A regularization parameter is used to balance the trade-off between data fidelity term and prior. The finite difference scheme is used for discretization of the proposed method. The performance analysis and comparative study of the proposed method with other standard methods is presented for brain web dataset at varying noise levels in terms of peak signal-to-noise ratio, mean square error, structure similarity index map, and correlation parameter. From the simulation results, it is observed that the proposed framework with CD based prior is performing better in comparison to other priors in consideration.
Yadav, Ram Bharos; Srivastava, Subodh; Srivastava, Rajeev
2016-01-01
The proposed framework is obtained by casting the noise removal problem into a variational framework. This framework automatically identifies the various types of noise present in the magnetic resonance image and filters them by choosing an appropriate filter. This filter includes two terms: the first term is a data likelihood term and the second term is a prior function. The first term is obtained by minimizing the negative log likelihood of the corresponding probability density functions: Gaussian or Rayleigh or Rician. Further, due to the ill-posedness of the likelihood term, a prior function is needed. This paper examines three partial differential equation based priors which include total variation based prior, anisotropic diffusion based prior, and a complex diffusion (CD) based prior. A regularization parameter is used to balance the trade-off between data fidelity term and prior. The finite difference scheme is used for discretization of the proposed method. The performance analysis and comparative study of the proposed method with other standard methods is presented for brain web dataset at varying noise levels in terms of peak signal-to-noise ratio, mean square error, structure similarity index map, and correlation parameter. From the simulation results, it is observed that the proposed framework with CD based prior is performing better in comparison to other priors in consideration. PMID:28144118
Kamppeter, T.; Mertens, F.G.; Moro, E.; Sanchez, A.; Bishop, A.R.
1998-09-01
We study how thermal fluctuations affect the dynamics of vortices in the two-dimensional anisotropic Heisenberg model depending on their additive or multiplicative character. Using a collective coordinate theory, we analytically show that multiplicative noise, arising from fluctuations in the local field term of the Landau-Lifshitz equations, and Langevin-like additive noise have the same effect on vortex dynamics (within a very plausible assumption consistent with the collective coordinate approach). This is a highly non-trivial result as multiplicative and additive noises usually modify the dynamics in very different ways. We also carry out numerical simulations of both versions of the model finding that they indeed give rise to very similar vortex dynamics.
Equivalence of time and aperture domain additive noise in ultrasound coherence.
Bottenus, Nick B; Trahey, Gregg E
2015-01-01
Ultrasonic echoes backscattered from diffuse media, recorded by an array transducer and appropriately focused, demonstrate coherence predicted by the van Cittert-Zernike theorem. Additive noise signals from off-axis scattering, reverberation, phase aberration, and electronic (thermal) noise can all superimpose incoherent or partially coherent signals onto the recorded echoes, altering the measured coherence. An expression is derived to describe the effect of uncorrelated random channel noise in terms of the noise-to-signal ratio. Equivalent descriptions are made in the aperture dimension to describe uncorrelated magnitude and phase apodizations of the array. Binary apodization is specifically described as an example of magnitude apodization and adjustments are presented to minimize the artifacts caused by finite signal length. The effects of additive noise are explored in short-lag spatial coherence imaging, an image formation technique that integrates the calculated coherence curve of acquired signals up to a small fraction of the array length for each lateral and axial location. A derivation of the expected contrast as a function of noise-to-signal ratio is provided and validation is performed in simulation.
How to detect the Granger-causal flow direction in the presence of additive noise?
Vinck, Martin; Huurdeman, Lisanne; Bosman, Conrado A; Fries, Pascal; Battaglia, Francesco P; Pennartz, Cyriel M A; Tiesinga, Paul H
2015-03-01
Granger-causality metrics have become increasingly popular tools to identify directed interactions between brain areas. However, it is known that additive noise can strongly affect Granger-causality metrics, which can lead to spurious conclusions about neuronal interactions. To solve this problem, previous studies have proposed the detection of Granger-causal directionality, i.e. the dominant Granger-causal flow, using either the slope of the coherency (Phase Slope Index; PSI), or by comparing Granger-causality values between original and time-reversed signals (reversed Granger testing). We show that for ensembles of vector autoregressive (VAR) models encompassing bidirectionally coupled sources, these alternative methods do not correctly measure Granger-causal directionality for a substantial fraction of VAR models, even in the absence of noise. We then demonstrate that uncorrelated noise has fundamentally different effects on directed connectivity metrics than linearly mixed noise, where the latter may result as a consequence of electric volume conduction. Uncorrelated noise only weakly affects the detection of Granger-causal directionality, whereas linearly mixed noise causes a large fraction of false positives for standard Granger-causality metrics and PSI, but not for reversed Granger testing. We further show that we can reliably identify cases where linearly mixed noise causes a large fraction of false positives by examining the magnitude of the instantaneous influence coefficient in a structural VAR model. By rejecting cases with strong instantaneous influence, we obtain an improved detection of Granger-causal flow between neuronal sources in the presence of additive noise. These techniques are applicable to real data, which we demonstrate using actual area V1 and area V4 LFP data, recorded from the awake monkey performing a visual attention task.
The Unilateral Mean Luminance Alters Additive Internal Noise in Normal Vision.
Li, Lin; Yu, Yongqiang; Zhou, Yifeng
2015-01-01
Luminance has been found to play a modulating role in the processes of many visual tasks. However, the mechanisms underlying the modulation role of luminance have been little studied, and the conclusions have been controversial. Here, using a dichoptic viewing paradigm by varying the luminance in one eye while measuring the contrast-detection threshold in the other eye, we studied the effect of different unilateral mean luminance values on the detectability of sine wave gratings against backgrounds of various levels of white noise in normal subjects. We found that unilateral luminance altered the additive internal noise within a perceptual template model framework, with low luminance increasing the additive internal noise and high luminance reducing it. This finding helps to reveal how luminance modulates contrast detection and its relative mechanisms.
NB-PLC channel modelling with cyclostationary noise addition & OFDM implementation for smart grid
NASA Astrophysics Data System (ADS)
Thomas, Togis; Gupta, K. K.
2016-03-01
Power line communication (PLC) technology can be a viable solution for the future ubiquitous networks because it provides a cheaper alternative to other wired technology currently being used for communication. In smart grid Power Line Communication (PLC) is used to support communication with low rate on low voltage (LV) distribution network. In this paper, we propose the channel modelling of narrowband (NB) PLC in the frequency range 5 KHz to 500 KHz by using ABCD parameter with cyclostationary noise addition. Behaviour of the channel was studied by the addition of 11KV/230V transformer, by varying load location and load. Bit error rate (BER) Vs signal to noise ratio SNR) was plotted for the proposed model by employing OFDM. Our simulation results based on the proposed channel model show an acceptable performance in terms of bit error rate versus signal to noise ratio, which enables communication required for smart grid applications.
Mass dependence of instabilities of an oscillator with multiplicative and additive noise.
Gitterman, Moshe; Kessler, David A
2013-02-01
We study the instabilities of a harmonic oscillator subject to additive and dichotomous multiplicative noise, focusing on the dependence of the instability threshold on the mass. For multiplicative noise in the damping, the energy instability threshold is crossed as the mass is decreased, as long as the smaller damping is in fact negative. For multiplicative noise in the stiffness, the situation is more complicated and in fact the energy transition is reentrant for intermediate noise strength and damping. For multiplicative noise in the mass, the results depend on the implementation of the noise. One can take the velocity or the momentum to be conserved as the mass is changed. In these cases increasing the mass destabilizes the system. Alternatively, if the change in mass is caused by the accretion and loss of particles to the Brownian particle, these processes are asymmetric with momentum conserved upon accretion and velocity upon loss. In this case, there is no instability, as opposed to the other two implementations. We also present the mass dependence of the instability threshold for the first moment. Finally, we study the distribution of the energy, finding a power-law cutoff at a value that increases with time.
Random attractors for the stochastic coupled fractional Ginzburg-Landau equation with additive noise
Shu, Ji E-mail: 530282863@qq.com; Li, Ping E-mail: 530282863@qq.com; Zhang, Jia; Liao, Ou
2015-10-15
This paper is concerned with the stochastic coupled fractional Ginzburg-Landau equation with additive noise. We first transform the stochastic coupled fractional Ginzburg-Landau equation into random equations whose solutions generate a random dynamical system. Then we prove the existence of random attractor for random dynamical system.
Yang, Kai; Huang, Shih-Ying; Packard, Nathan J.; Boone, John M.
2010-01-01
Purpose: A simplified linear model approach was proposed to accurately model the response of a flat panel detector used for breast CT (bCT). Methods: Individual detector pixel mean and variance were measured from bCT projection images acquired both in air and with a polyethylene cylinder, with the detector operating in both fixed low gain and dynamic gain mode. Once the coefficients of the linear model are determined, the fractional additive noise can be used as a quantitative metric to evaluate the system’s efficiency in utilizing x-ray photons, including the performance of different gain modes of the detector. Results: Fractional additive noise increases as the object thickness increases or as the radiation dose to the detector decreases. For bCT scan techniques on the UC Davis prototype scanner (80 kVp, 500 views total, 30 frames∕s), in the low gain mode, additive noise contributes 21% of the total pixel noise variance for a 10 cm object and 44% for a 17 cm object. With the dynamic gain mode, additive noise only represents approximately 2.6% of the total pixel noise variance for a 10 cm object and 7.3% for a 17 cm object. Conclusions: The existence of the signal-independent additive noise is the primary cause for a quadratic relationship between bCT noise variance and the inverse of radiation dose at the detector. With the knowledge of the additive noise contribution to experimentally acquired images, system modifications can be made to reduce the impact of additive noise and improve the quantum noise efficiency of the bCT system. PMID:20831059
Yang Kai; Huang, Shih-Ying; Packard, Nathan J.; Boone, John M.
2010-07-15
Purpose: A simplified linear model approach was proposed to accurately model the response of a flat panel detector used for breast CT (bCT). Methods: Individual detector pixel mean and variance were measured from bCT projection images acquired both in air and with a polyethylene cylinder, with the detector operating in both fixed low gain and dynamic gain mode. Once the coefficients of the linear model are determined, the fractional additive noise can be used as a quantitative metric to evaluate the system's efficiency in utilizing x-ray photons, including the performance of different gain modes of the detector. Results: Fractional additive noise increases as the object thickness increases or as the radiation dose to the detector decreases. For bCT scan techniques on the UC Davis prototype scanner (80 kVp, 500 views total, 30 frames/s), in the low gain mode, additive noise contributes 21% of the total pixel noise variance for a 10 cm object and 44% for a 17 cm object. With the dynamic gain mode, additive noise only represents approximately 2.6% of the total pixel noise variance for a 10 cm object and 7.3% for a 17 cm object. Conclusions: The existence of the signal-independent additive noise is the primary cause for a quadratic relationship between bCT noise variance and the inverse of radiation dose at the detector. With the knowledge of the additive noise contribution to experimentally acquired images, system modifications can be made to reduce the impact of additive noise and improve the quantum noise efficiency of the bCT system.
NASA Astrophysics Data System (ADS)
Azad, Nasser L.; Mozaffari, Ahmad
2015-12-01
The main scope of the current study is to develop a systematic stochastic model to capture the undesired uncertainty and random noises on the key parameters affecting the catalyst temperature over the coldstart operation of automotive engine systems. In the recent years, a number of articles have been published which aim at the modeling and analysis of automotive engines' behavior during coldstart operations by using regression modeling methods. Regarding highly nonlinear and uncertain nature of the coldstart operation, calibration of the engine system's variables, for instance the catalyst temperature, is deemed to be an intricate task, and it is unlikely to develop an exact physics-based nonlinear model. This encourages automotive engineers to take advantage of knowledge-based modeling tools and regression approaches. However, there exist rare reports which propose an efficient tool for coping with the uncertainty associated with the collected database. Here, the authors introduce a random noise to experimentally derived data and simulate an uncertain database as a representative of the engine system's behavior over coldstart operations. Then, by using a Gaussian process regression machine (GPRM), a reliable model is used for the sake of analysis of the engine's behavior. The simulation results attest the efficacy of GPRM for the considered case study. The research outcomes confirm that it is possible to develop a practical calibration tool which can be reliably used for modeling the catalyst temperature.
Gaussian entanglement of formation
Wolf, M.M.; Giedke, G.; Krueger, O.; Werner, R. F.; Cirac, J.I.
2004-05-01
We introduce a Gaussian version of the entanglement of formation adapted to bipartite Gaussian states by considering decompositions into pure Gaussian states only. We show that this quantity is an entanglement monotone under Gaussian operations and provide a simplified computation for states of arbitrary many modes. For the case of one mode per site the remaining variational problem can be solved analytically. If the considered state is in addition symmetric with respect to interchanging the two modes, we prove additivity of the considered entanglement measure. Moreover, in this case and considering only a single copy, our entanglement measure coincides with the true entanglement of formation.
Noise robust estimates of correlation dimension and K2 entropy
NASA Astrophysics Data System (ADS)
Nolte, Guido; Ziehe, Andreas; Müller, Klaus-Robert
2001-07-01
Using Gaussian kernels to define the correlation sum we derive simple formulas that correct the noise bias in estimates of the correlation dimension and K2 entropy of chaotic time series. The corrections are only based on the difference of correlation dimensions for adjacent embedding dimensions and hence preserve the full functional dependencies on both the scale parameter and embedding dimension. It is shown theoretically that the estimates, which are derived for additive white Gaussian noise, are also robust for moderately colored noise. Simulations underline the usefulness of the proposed correction schemes. It is demonstrated that the method gives satisfactory results also for non-Gaussian and dynamical noise.
Mohamed Salleh, Faridah Hani; Arif, Shereena Mohd; Zainudin, Suhaila; Firdaus-Raih, Mohd
2015-12-01
A gene regulatory network (GRN) is a large and complex network consisting of interacting elements that, over time, affect each other's state. The dynamics of complex gene regulatory processes are difficult to understand using intuitive approaches alone. To overcome this problem, we propose an algorithm for inferring the regulatory interactions from knock-out data using a Gaussian model combines with Pearson Correlation Coefficient (PCC). There are several problems relating to GRN construction that have been outlined in this paper. We demonstrated the ability of our proposed method to (1) predict the presence of regulatory interactions between genes, (2) their directionality and (3) their states (activation or suppression). The algorithm was applied to network sizes of 10 and 50 genes from DREAM3 datasets and network sizes of 10 from DREAM4 datasets. The predicted networks were evaluated based on AUROC and AUPR. We discovered that high false positive values were generated by our GRN prediction methods because the indirect regulations have been wrongly predicted as true relationships. We achieved satisfactory results as the majority of sub-networks achieved AUROC values above 0.5.
NASA Astrophysics Data System (ADS)
Ongkittikul, Surachai; Jundang, Nattapong; Srisuk, Sanun
2017-02-01
This paper presents a new data compilation of the image transformation base on the series of the trace transform. The advantage of this new compilation is to solve the noise problem that usually appears in the pattern recognition. Submicro pattern analysis is employ to encode the series of the trace transform from a image which organizes by the shift-invariant sub-micro pattern scheme (SiSMP). Then, all data will sum to the final result by 2-D histogram with the Discriminant Feature Transform. The experiments of our approach show that the new compilation can increase the performance of the recognition compare with the LBP technique by using Brodatz texture database.
NASA Astrophysics Data System (ADS)
Morse, Robert P.; Roper, Peter
2000-05-01
Analog electrical stimulation of the cochlear nerve (the nerve of hearing) by a cochlear implant is an effective method of providing functional hearing to profoundly deaf people. Recent physiological and computational experiments have shown that analog cochlear implants are unlikely to convey certain speech cues by the temporal pattern of evoked nerve discharges. However, these experiments have also shown that the optimal addition of noise to cochlear implant signals can enhance the temporal representation of speech cues [R. P. Morse and E. F. Evans, Nature Medicine 2, 928 (1996)]. We present a simple model to explain this enhancement of temporal representation. Our model derives from a rate equation for the mean threshold-crossing rate of an infinite set of parallel discriminators (level-crossing detectors); a system that well describes the time coding of information by a set of nerve fibers. Our results show that the optimal transfer of information occurs when the threshold level of each discriminator is equal to the root-mean-square noise level. The optimal transfer of information by a cochlear implant is therefore expected to occur when the internal root-mean-square noise level of each stimulated fiber is approximately equal to the nerve threshold. When interpreted within the framework of aperiodic stochastic resonance, our results indicate therefore that for an infinite array of discriminators, a tuning of the noise is still necessary for optimal performance. This is in contrast to previous results [Collins, Chow, and Imhoff, Nature 376, 236 (1995); Chialvo, Longtin, and Müller-Gerking, Phys. Rev. E 55, 1798 (1997)] on arrays of FitzHugh-Nagumo neurons.
Breaking Gaussian incompatibility on continuous variable quantum systems
Heinosaari, Teiko; Kiukas, Jukka; Schultz, Jussi
2015-08-15
We characterise Gaussian quantum channels that are Gaussian incompatibility breaking, that is, transform every set of Gaussian measurements into a set obtainable from a joint Gaussian observable via Gaussian postprocessing. Such channels represent local noise which renders measurements useless for Gaussian EPR-steering, providing the appropriate generalisation of entanglement breaking channels for this scenario. Understanding the structure of Gaussian incompatibility breaking channels contributes to the resource theory of noisy continuous variable quantum information protocols.
The conditional entropy power inequality for Gaussian quantum states
Koenig, Robert
2015-02-15
We propose a generalization of the quantum entropy power inequality involving conditional entropies. For the special case of Gaussian states, we give a proof based on perturbation theory for symplectic spectra. We discuss some implications for entanglement-assisted classical communication over additive bosonic noise channels.
NASA Astrophysics Data System (ADS)
Rugini, Luca; Banelli, Paolo
2016-12-01
The minimum mean-squared error (MMSE) is one of the most popular criteria for Bayesian estimation. Conversely, the signal-to-noise ratio (SNR) is a typical performance criterion in communications, radar, and generally detection theory. In this paper we first formalize an SNR criterion to design an estimator, and then we prove that there exists an equivalence between MMSE and maximum-SNR estimators, for any statistics. We also extend this equivalence to specific classes of suboptimal estimators, which are expressed by a basis expansion model (BEM). Then, by exploiting an orthogonal BEM for the estimator, we derive the MMSE estimator constrained to a given quantization resolution of the noisy observations, and we prove that this suboptimal MMSE estimator tends to the optimal MMSE estimator that uses an infinite resolution of the observation. Besides, we derive closed-form expressions for the mean-squared error (MSE) and for the SNR of the proposed suboptimal estimators, and we show that these expressions constitute tight, asymptotically exact, bounds for the optimal MMSE and maximum SNR.
NASA Astrophysics Data System (ADS)
Zhou, Bingchang; McDonnell, Mark D.
2015-02-01
The problem of optimising the threshold levels in multilevel threshold system subject to multiplicative Gaussian and uniform noise is considered. Similar to previous results for additive noise, we find a bifurcation phenomenon in the optimal threshold values, as the noise intensity changes. This occurs when the number of threshold units is greater than one. We also study the optimal thresholds for combined additive and multiplicative Gaussian noise, and find that all threshold levels need to be identical to optimise the system when the additive noise intensity is a constant. However, this identical value is not equal to the signal mean, unlike the case of additive noise. When the multiplicative noise intensity is instead held constant, the optimal threshold levels are not all identical for small additive noise intensity but are all equal to zero for large additive noise intensity. The model and our results are potentially relevant for sensor network design and understanding neurobiological sensory neurons such as in the peripheral auditory system.
NASA Astrophysics Data System (ADS)
Fu, Jack; Khoury, Jehad; Cronin-Golomb, Mark; Woods, Charles L.
1995-01-01
Computer simulations of photorefractive thresholding filters for the reduction of artifact or dust noise demonstrate an increase in signal-to-noise ratio (SNR) of 70% to 95%, respectively, of that provided by the Wiener filter for inputs with a SNR of approximately 3. These simple, nearly optimal filters use a spectral thresholding profile that is proportional to the envelope of the noise spectrum. Alternative nonlinear filters with either 1/ nu or constant thresholding profiles increase the SNR almost as much as the noise-envelope thresholding filter.
Addition of visual noise boosts evoked potential-based brain-computer interface
Xie, Jun; Xu, Guanghua; Wang, Jing; Zhang, Sicong; Zhang, Feng; Li, Yeping; Han, Chengcheng; Li, Lili
2014-01-01
Although noise has a proven beneficial role in brain functions, there have not been any attempts on the dedication of stochastic resonance effect in neural engineering applications, especially in researches of brain-computer interfaces (BCIs). In our study, a steady-state motion visual evoked potential (SSMVEP)-based BCI with periodic visual stimulation plus moderate spatiotemporal noise can achieve better offline and online performance due to enhancement of periodic components in brain responses, which was accompanied by suppression of high harmonics. Offline results behaved with a bell-shaped resonance-like functionality and 7–36% online performance improvements can be achieved when identical visual noise was adopted for different stimulation frequencies. Using neural encoding modeling, these phenomena can be explained as noise-induced input-output synchronization in human sensory systems which commonly possess a low-pass property. Our work demonstrated that noise could boost BCIs in addressing human needs. PMID:24828128
3D filtering technique in presence of additive noise in color videos implemented on DSP
NASA Astrophysics Data System (ADS)
Ponomaryov, Volodymyr I.; Montenegro-Monroy, Hector; Palacios, Alfredo
2014-05-01
A filtering method for color videos contaminated by additive noise is presented. The proposed framework employs three filtering stages: spatial similarity filtering, neighboring frame denoising, and spatial post-processing smoothing. The difference with other state-of- the-art filtering methods, is that this approach, based on fuzzy logic, analyses basic and related gradient values between neighboring pixels into a 7 fi 7 sliding window in the vicinity of a central pixel in each of the RGB channels. Following, the similarity measures between the analogous pixels in the color bands are taken into account during the denoising. Next, two neighboring video frames are analyzed together estimating local motions between the frames using block matching procedure. In the final stage, the edges and smoothed areas are processed differently in a current frame during the post-processing filtering. Numerous simulations results confirm that this 3D fuzzy filter perform better than other state-of-the- art methods, such as: 3D-LLMMSE, WMVCE, RFMDAF, FDARTF G, VBM3D and NLM, in terms of objective criteria (PSNR, MAE, NCD and SSIM) as well as subjective perception via human vision system in the different color videos. An efficiency analysis of the designed and other mentioned filters have been performed on the DSPs TMS320 DM642 and TMS320DM648 by Texas Instruments through MATLAB and Simulink module showing that the novel 3D fuzzy filter can be used in real-time processing applications.
NASA Astrophysics Data System (ADS)
Wu, Qing
Millions of people across the world are suffering from noise induced hearing loss (NIHL), especially under working conditions of either continuous Gaussian or non-Gaussian noise that might affect human's hearing function. Impulse noise is a typical non-Gaussian noise exposure in military and industry, and generates severe hearing loss problem. This study mainly focuses on characterization of impulse noise using digital signal analysis method and prediction of the auditory hazard of impulse noise induced hearing loss by the Auditory Hazard Assessment Algorithm for Humans (AHAAH) modeling. A digital noise exposure system has been developed to produce impulse noises with peak sound pressure level (SPL) up to 160 dB. The characterization of impulse noise generated by the system has been investigated and analyzed in both time and frequency domains. Furthermore, the effects of key parameters of impulse noise on auditory risk unit (ARU) are investigated using both simulated and experimental measured impulse noise signals in the AHAAH model. The results showed that the ARUs increased monotonically with the peak pressure (both P+ and P-) increasing. With increasing of the time duration, the ARUs increased first and then decreased, and the peak of ARUs appeared at about t = 0.2 ms (for both t+ and t-). In addition, the auditory hazard of experimental measured impulse noises signals demonstrated a monotonically increasing relationship between ARUs and system voltages.
Burge, Johannes
2017-01-01
Accuracy Maximization Analysis (AMA) is a recently developed Bayesian ideal observer method for task-specific dimensionality reduction. Given a training set of proximal stimuli (e.g. retinal images), a response noise model, and a cost function, AMA returns the filters (i.e. receptive fields) that extract the most useful stimulus features for estimating a user-specified latent variable from those stimuli. Here, we first contribute two technical advances that significantly reduce AMA’s compute time: we derive gradients of cost functions for which two popular estimators are appropriate, and we implement a stochastic gradient descent (AMA-SGD) routine for filter learning. Next, we show how the method can be used to simultaneously probe the impact on neural encoding of natural stimulus variability, the prior over the latent variable, noise power, and the choice of cost function. Then, we examine the geometry of AMA’s unique combination of properties that distinguish it from better-known statistical methods. Using binocular disparity estimation as a concrete test case, we develop insights that have general implications for understanding neural encoding and decoding in a broad class of fundamental sensory-perceptual tasks connected to the energy model. Specifically, we find that non-orthogonal (partially redundant) filters with scaled additive noise tend to outperform orthogonal filters with constant additive noise; non-orthogonal filters and scaled additive noise can interact to sculpt noise-induced stimulus encoding uncertainty to match task-irrelevant stimulus variability. Thus, we show that some properties of neural response thought to be biophysical nuisances can confer coding advantages to neural systems. Finally, we speculate that, if repurposed for the problem of neural systems identification, AMA may be able to overcome a fundamental limitation of standard subunit model estimation. As natural stimuli become more widely used in the study of psychophysical and
AUTONOMOUS GAUSSIAN DECOMPOSITION
Lindner, Robert R.; Vera-Ciro, Carlos; Murray, Claire E.; Stanimirović, Snežana; Babler, Brian; Heiles, Carl; Hennebelle, Patrick; Dickey, John
2015-04-15
We present a new algorithm, named Autonomous Gaussian Decomposition (AGD), for automatically decomposing spectra into Gaussian components. AGD uses derivative spectroscopy and machine learning to provide optimized guesses for the number of Gaussian components in the data, and also their locations, widths, and amplitudes. We test AGD and find that it produces results comparable to human-derived solutions on 21 cm absorption spectra from the 21 cm SPectral line Observations of Neutral Gas with the EVLA (21-SPONGE) survey. We use AGD with Monte Carlo methods to derive the H i line completeness as a function of peak optical depth and velocity width for the 21-SPONGE data, and also show that the results of AGD are stable against varying observational noise intensity. The autonomy and computational efficiency of the method over traditional manual Gaussian fits allow for truly unbiased comparisons between observations and simulations, and for the ability to scale up and interpret the very large data volumes from the upcoming Square Kilometer Array and pathfinder telescopes.
Autonomous Gaussian Decomposition
NASA Astrophysics Data System (ADS)
Lindner, Robert R.; Vera-Ciro, Carlos; Murray, Claire E.; Stanimirović, Snežana; Babler, Brian; Heiles, Carl; Hennebelle, Patrick; Goss, W. M.; Dickey, John
2015-04-01
We present a new algorithm, named Autonomous Gaussian Decomposition (AGD), for automatically decomposing spectra into Gaussian components. AGD uses derivative spectroscopy and machine learning to provide optimized guesses for the number of Gaussian components in the data, and also their locations, widths, and amplitudes. We test AGD and find that it produces results comparable to human-derived solutions on 21 cm absorption spectra from the 21 cm SPectral line Observations of Neutral Gas with the EVLA (21-SPONGE) survey. We use AGD with Monte Carlo methods to derive the H i line completeness as a function of peak optical depth and velocity width for the 21-SPONGE data, and also show that the results of AGD are stable against varying observational noise intensity. The autonomy and computational efficiency of the method over traditional manual Gaussian fits allow for truly unbiased comparisons between observations and simulations, and for the ability to scale up and interpret the very large data volumes from the upcoming Square Kilometer Array and pathfinder telescopes.
The effectiveness of correcting codes in reception in the whole in additive normal white noise
NASA Technical Reports Server (NTRS)
Shtarkov, Y. M.
1974-01-01
Some possible criteria for estimating the effectiveness of correcting codes are presented, and the energy effectiveness of correcting codes is studied for symbol-by-symbol reception. Expressions for the energetic effectiveness of binary correcting codes for reception in the whole are produced. Asymptotic energetic effectiveness and finite signal/noise ratio cases are considered.
From almost Gaussian to Gaussian
NASA Astrophysics Data System (ADS)
Costa, Max H. M.; Rioul, Olivier
2015-01-01
We consider lower and upper bounds on the difference of differential entropies of a Gaussian random vector and an approximately Gaussian random vector after they are "smoothed" by an arbitrarily distributed random vector of finite power. These bounds are important to establish the optimality of the corner points in the capacity region of Gaussian interference channels. A problematic issue in a previous attempt to establish these bounds was detected in 2004 and the mentioned corner points have since been dubbed "the missing corner points". The importance of the given bounds comes from the fact that they induce Fano-type inequalities for the Gaussian interference channel. Usual Fano inequalities are based on a communication requirement. In this case, the new inequalities are derived from a non-disturbance constraint. The upper bound on the difference of differential entropies is established by the data processing inequality (DPI). For the lower bound, we do not have a complete proof, but we present an argument based on continuity and the DPI.
Mino, H
1993-03-01
A method of estimating the parameters of nonstationary ionic channel current fluctuations (NST-ICF's) in the presence of an additive measurement noise is proposed. The case is considered in which the sample records of NST-ICT's corrupted by the measurement noise are available for estimation, where the experiment can be repeated many times to calculate the statistics of noisy NST-ICF's. The conventional second-order regression model expressed in terms of the mean and variance of noisy NST-ICF's is derived theoretically, assuming that NST-ICF's are binomially distributed. Since the coefficients of the regression model are explicitly related to not only the parameters of NST-ICF's but also the measurement noise component, the parameters of NST-ICF's that are of interest can be estimated without interference from the additive measurement noise by identifying the regression coefficients. Furthermore, the accuracy of the parameter estimates is theoretically evaluated using the error-covariance matrix of the regression coefficients. The validity and effectiveness of the proposed method are demonstrated in a Monte Carlo simulation in which a fundamental kinetic scheme of Na+ channels is treated as a specific example.
[Denoising and assessing method of additive noise in the ultraviolet spectrum of SO2 in flue gas].
Zhou, Tao; Sun, Chang-Ku; Liu, Bin; Zhao, Yu-Mei
2009-11-01
The problem of denoising and assessing method of the spectrum of SO2 in flue gas was studied based on DOAS. The denoising procedure of the additive noise in the spectrum was divided into two parts: reducing the additive noise and enhancing the useful signal. When obtaining the absorption feature of measured gas, a multi-resolution preprocessing method of original spectrum was adopted for denoising by DWT (discrete wavelet transform). The signal energy operators in different scales were used to choose the denoising threshold and separate the useful signal from the noise. On the other hand, because there was no sudden change in the spectra of flue gas in time series, the useful signal component was enhanced according to the signal time dependence. And the standard absorption cross section was used to build the ideal absorption spectrum with the measured gas temperature and pressure. This ideal spectrum was used as the desired signal instead of the original spectrum in the assessing method to modify the SNR (signal-noise ratio). There were two different environments to do the proof test-in the lab and at the scene. In the lab, SO2 was measured several times with the system using this method mentioned above. The average deviation was less than 1.5%, while the repeatability was less than 1%. And the short range experiment data were better than the large range. In the scene of a power plant whose concentration of flue gas had a large variation range, the maximum deviation of this method was 2.31% in the 18 groups of contrast data. The experimental results show that the denoising effect of the scene spectrum was better than that of the lab spectrum. This means that this method can improve the SNR of the spectrum effectively, which is seriously polluted by additive noise.
Searching for primordial non-Gaussianity in Planck CMB maps using a combined estimator
Novaes, C.P.; Wuensche, C.A.; Bernui, A.; Ferreira, I.S. E-mail: bernui@on.br E-mail: ca.wuensche@inpe.br
2014-01-01
The extensive search for deviations from Gaussianity in cosmic microwave background radiation (CMB) data is very important due to the information about the very early moments of the universe encoded there. Recent analyses from Planck CMB data do not exclude the presence of non-Gaussianity of small amplitude, although they are consistent with the Gaussian hypothesis. The use of different techniques is essential to provide information about types and amplitudes of non-Gaussianities in the CMB data. In particular, we find interesting to construct an estimator based upon the combination of two powerful statistical tools that appears to be sensitive enough to detect tiny deviations from Gaussianity in CMB maps. This estimator combines the Minkowski functionals with a Neural Network, maximizing a tool widely used to study non-Gaussian signals with a reinforcement of another tool designed to identify patterns in a data set. We test our estimator by analyzing simulated CMB maps contaminated with different amounts of local primordial non-Gaussianity quantified by the dimensionless parameter f{sub NL}. We apply it to these sets of CMB maps and find ∼> 98% of chance of positive detection, even for small intensity local non-Gaussianity like f{sub NL} = 38±18, the current limit from Planck data for large angular scales. Additionally, we test the suitability to distinguish between primary and secondary non-Gaussianities: first we train the Neural Network with two sets, one of nearly Gaussian CMB maps (|f{sub NL}| ≤ 10) but contaminated with realistic inhomogeneous Planck noise (i.e., secondary non-Gaussianity) and the other of non-Gaussian CMB maps, that is, maps endowed with weak primordial non-Gaussianity (28 ≤ f{sub NL} ≤ 48); after that we test an ensemble composed of CMB maps either with one of these non-Gaussian contaminations, and find out that our method successfully classifies ∼ 95% of the tested maps as being CMB maps containing primordial or
Chen, Chuchu Hong, Jialin Zhang, Liying
2016-02-01
Stochastic Maxwell equations with additive noise are a system of stochastic Hamiltonian partial differential equations intrinsically, possessing the stochastic multi-symplectic conservation law. It is shown that the averaged energy increases linearly with respect to the evolution of time and the flow of stochastic Maxwell equations with additive noise preserves the divergence in the sense of expectation. Moreover, we propose three novel stochastic multi-symplectic methods to discretize stochastic Maxwell equations in order to investigate the preservation of these properties numerically. We make theoretical discussions and comparisons on all of the three methods to observe that all of them preserve the corresponding discrete version of the averaged divergence. Meanwhile, we obtain the corresponding dissipative property of the discrete averaged energy satisfied by each method. Especially, the evolution rates of the averaged energies for all of the three methods are derived which are in accordance with the continuous case. Numerical experiments are performed to verify our theoretical results.
NASA Astrophysics Data System (ADS)
Gao, Ting; Duan, Jinqiao
2016-10-01
Complex systems are sometimes subject to non-Gaussian α-stable Lévy fluctuations. A new method is devised to estimate the uncertain parameter α and other system parameters, using observations on mean exit time or escape probability for the system evolution. It is based on solving an inverse problem for a deterministic, nonlocal partial differential equation via numerical optimization. The existing methods for estimating parameters require observations on system state sample paths for long time periods or probability densities at large spatial ranges. The method proposed here, instead, requires observations on mean exit time or escape probability only for an arbitrarily small spatial domain. This new method is beneficial to systems for which mean exit time or escape probability is feasible to observe.
NASA Technical Reports Server (NTRS)
Smalheer, C. V.
1973-01-01
The chemistry of lubricant additives is discussed to show what the additives are chemically and what functions they perform in the lubrication of various kinds of equipment. Current theories regarding the mode of action of lubricant additives are presented. The additive groups discussed include the following: (1) detergents and dispersants, (2) corrosion inhibitors, (3) antioxidants, (4) viscosity index improvers, (5) pour point depressants, and (6) antifouling agents.
Optimal Gaussian entanglement swapping
Hoelscher-Obermaier, Jason; Loock, Peter van
2011-01-15
We consider entanglement swapping with general mixed two-mode Gaussian states and calculate the optimal gains for a broad class of such states including those states most relevant in communication scenarios. We show that, for this class of states, entanglement swapping adds no additional mixedness; that is, the ensemble-average output state has the same purity as the input states. This implies that, by using intermediate entanglement swapping steps, it is, in principle, possible to distribute entangled two-mode Gaussian states of higher purity as compared to direct transmission. We then apply the general results on optimal Gaussian swapping to the problem of quantum communication over a lossy fiber and demonstrate that, in contrast to the negative conclusions in the literature, swapping-based schemes in fact often perform better than direct transmission for high input squeezing. However, an effective transmission analysis reveals that the hope for improved performance based on optimal Gaussian entanglement swapping is spurious since the swapping does not lead to an enhancement of the effective transmission. This implies that the same or better results can always be obtained using direct transmission in combination with, in general, less squeezing.
Passive interferometric symmetries of multimode Gaussian pure states
NASA Astrophysics Data System (ADS)
Gabay, Natasha; Menicucci, Nicolas C.
2016-05-01
As large-scale multimode Gaussian states begin to become accessible in the laboratory, their representation and analysis become a useful topic of research in their own right. The graphical calculus for Gaussian pure states provides powerful tools for their representation, while this work presents a useful tool for their analysis: passive interferometric (i.e., number-conserving) symmetries. Here we show that these symmetries of multimode Gaussian states simplify calculations in measurement-based quantum computing and provide constructive tools for engineering large-scale harmonic systems with specific physical properties, and we provide a general mathematical framework for deriving them. Such symmetries are generated by linear combinations of operators expressed in the Schwinger representation of U (2 ) , called nullifiers because the Gaussian state in question is a zero eigenstate of them. This general framework is shown to have applications in the noise analysis of continuous-various cluster states and is expected to have additional applications in future work with large-scale multimode Gaussian states.
NASA Astrophysics Data System (ADS)
Wang, Kang-Kang; Zong, De-Cai; Wang, Ya-Jun; Li, Sheng-Hong
2016-05-01
In this paper, the transition between the stable state of a big density and the extinction state and stochastic resonance (SR) for a time-delayed metapopulation system disturbed by colored cross-correlated noises are investigated. By applying the fast descent method, the small time-delay approximation and McNamara and Wiesenfeld's SR theory, we investigate the impacts of time-delay, the multiplicative, additive noises and colored cross-correlated noise on the SNR and the shift between the two states of the system. Numerical results show that the multiplicative, additive noises and time-delay can all speed up the transition from the stable state to the extinction state, while the correlation noise and its correlation time can slow down the extinction process of the population system. With respect to SNR, the multiplicative noise always weakens the SR effect, while noise correlation time plays a dual role in motivating the SR phenomenon. Meanwhile, time-delay mainly plays a negative role in stimulating the SR phenomenon. Conversely, it could motivate the SR effect to increase the strength of the cross-correlation noise in the SNR-β plot, while the increase of additive noise intensity will firstly excite SR, and then suppress the SR effect.
Long-distance continuous-variable quantum key distribution with a Gaussian modulation
Jouguet, Paul; Kunz-Jacques, Sebastien; Leverrier, Anthony
2011-12-15
We designed high-efficiency error correcting codes allowing us to extract an errorless secret key in a continuous-variable quantum key distribution (CVQKD) protocol using a Gaussian modulation of coherent states and a homodyne detection. These codes are available for a wide range of signal-to-noise ratios on an additive white Gaussian noise channel with a binary modulation and can be combined with a multidimensional reconciliation method proven secure against arbitrary collective attacks. This improved reconciliation procedure considerably extends the secure range of a CVQKD with a Gaussian modulation, giving a secret key rate of about 10{sup -3} bit per pulse at a distance of 120 km for reasonable physical parameters.
Bénière, Arnaud; Goudail, François; Dolfi, Daniel; Alouini, Mehdi
2009-07-01
Active imaging systems that illuminate a scene with polarized light and acquire two images in two orthogonal polarizations yield information about the intensity contrast and the orthogonal state contrast (OSC) in the scene. Both contrasts are relevant for target detection. However, in real systems, the illumination is often spatially or temporally nonuniform. This creates artificial intensity contrasts that can lead to false alarms. We derive generalized likelihood ratio test (GLRT) detectors, for which intensity information is taken into account or not and determine the relevant expressions of the contrast in these two situations. These results are used to determine in which cases considering intensity information in addition to polarimetric information is relevant or not.
Conditional and unconditional Gaussian quantum dynamics
NASA Astrophysics Data System (ADS)
Genoni, Marco G.; Lami, Ludovico; Serafini, Alessio
2016-07-01
This article focuses on the general theory of open quantum systems in the Gaussian regime and explores a number of diverse ramifications and consequences of the theory. We shall first introduce the Gaussian framework in its full generality, including a classification of Gaussian (also known as 'general-dyne') quantum measurements. In doing so, we will give a compact proof for the parametrisation of the most general Gaussian completely positive map, which we believe to be missing in the existing literature. We will then move on to consider the linear coupling with a white noise bath, and derive the diffusion equations that describe the evolution of Gaussian states under such circumstances. Starting from these equations, we outline a constructive method to derive general master equations that apply outside the Gaussian regime. Next, we include the general-dyne monitoring of the environmental degrees of freedom and recover the Riccati equation for the conditional evolution of Gaussian states. Our derivation relies exclusively on the standard quantum mechanical update of the system state, through the evaluation of Gaussian overlaps. The parametrisation of the conditional dynamics we obtain is novel and, at variance with existing alternatives, directly ties in to physical detection schemes. We conclude our study with two examples of conditional dynamics that can be dealt with conveniently through our formalism, demonstrating how monitoring can suppress the noise in optical parametric processes as well as stabilise systems subject to diffusive scattering.
NASA Astrophysics Data System (ADS)
Zheng, Yue; Dang, Peipei; Zheng, Chuantao; Ye, Weilin; Wang, Yiding
2016-11-01
A miniature mid-infrared (mid-IR) methane (CH4) sensor system was developed by employing a wide-band wire-source and a semi-ellipsoid multi-pass gas cell. A dual-step differential method instead of the traditional one-step differential method was adopted by this sensor to tune measuring range/zero point and to suppress the additive/multiplicative noise. This method included a first subtraction operation between the two output signals (including a detection signal and a reference signal) from the dual-channel detector and a second subtraction operation on the amplitudes of the first-subtraction signal and the reference signal, followed by a ratio operation between the amplitude of the second-subtraction signal and the reference signal. Detailed experiments were performed to assess the performance of the sensor system. The detection range is 0-50 k ppm, and as the concentration gets larger than 12 k ppm, the relative detection error falls into the range of -3% to +3%. The Allan deviation is about 4.65 ppm with an averaging time of 1 s, and such value can be further improved to 0.45 ppm with an averaging time of 124 s. Due to the cost-effective incandescence wire-source, the small-size ellipsoid multi-pass gas cell and the miniature structure of the sensor, the developed standalone device shows potential applications of CH4 detection under coal-mine environment.
NASA Astrophysics Data System (ADS)
Zhao, Fan; Zhao, Jian; Zhao, Wenda; Qu, Feng
2016-05-01
Infrared images are characterized by low signal-to-noise ratio and low contrast. Therefore, the edge details are easily immerged in the background and noise, making it much difficult to achieve infrared image edge detail enhancement and denoising. This article proposes a novel method of Gaussian mixture model-based gradient field reconstruction, which enhances image edge details while suppressing noise. First, by analyzing the gradient histogram of noisy infrared image, Gaussian mixture model is adopted to simulate the distribution of the gradient histogram, and divides the image information into three parts corresponding to faint details, noise and the edges of clear targets, respectively. Then, the piecewise function is constructed based on the characteristics of the image to increase gradients of faint details and suppress gradients of noise. Finally, anisotropic diffusion constraint is added while visualizing enhanced image from the transformed gradient field to further suppress noise. The experimental results show that the method possesses unique advantage of effectively enhancing infrared image edge details and suppressing noise as well, compared with the existing methods. In addition, it can be used to effectively enhance other types of images such as the visible and medical images.
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising.
Zhang, Kai; Zuo, Wangmeng; Chen, Yunjin; Meng, Deyu; Zhang, Lei
2017-02-01
Discriminative model learning for image denoising has been recently attracting considerable attentions due to its favorable denoising performance. In this paper, we take one step forward by investigating the construction of feed-forward denoising convolutional neural networks (DnCNNs) to embrace the progress in very deep architecture, learning algorithm, and regularization method into image denoising. Specifically, residual learning and batch normalization are utilized to speed up the training process as well as boost the denoising performance. Different from the existing discriminative denoising models which usually train a specific model for additive white Gaussian noise (AWGN) at a certain noise level, our DnCNN model is able to handle Gaussian denoising with unknown noise level (i.e., blind Gaussian denoising). With the residual learning strategy, DnCNN implicitly removes the latent clean image in the hidden layers. This property motivates us to train a single DnCNN model to tackle with several general image denoising tasks such as Gaussian denoising, single image super-resolution and JPEG image deblocking. Our extensive experiments demonstrate that our DnCNN model can not only exhibit high effectiveness in several general image denoising tasks, but also be efficiently implemented by benefiting from GPU computing.
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.
NASA Astrophysics Data System (ADS)
Siu-Siu, Guo; Qingxuan, Shi
2017-03-01
In this paper, single-degree-of-freedom (SDOF) systems combined to Gaussian white noise and Gaussian/non-Gaussian colored noise excitations are investigated. By expressing colored noise excitation as a second-order filtered white noise process and introducing colored noise as an additional state variable, the equation of motion for SDOF system under colored noise is then transferred artificially to multi-degree-of-freedom (MDOF) system under white noise excitations with four-coupled first-order differential equations. As a consequence, corresponding Fokker-Planck-Kolmogorov (FPK) equation governing the joint probabilistic density function (PDF) of state variables increases to 4-dimension (4-D). Solution procedure and computer programme become much more sophisticated. The exponential-polynomial closure (EPC) method, widely applied for cases of SDOF systems under white noise excitations, is developed and improved for cases of systems under colored noise excitations and for solving the complex 4-D FPK equation. On the other hand, Monte Carlo simulation (MCS) method is performed to test the approximate EPC solutions. Two examples associated with Gaussian and non-Gaussian colored noise excitations are considered. Corresponding band-limited power spectral densities (PSDs) for colored noise excitations are separately given. Numerical studies show that the developed EPC method provides relatively accurate estimates of the stationary probabilistic solutions, especially the ones in the tail regions of the PDFs. Moreover, statistical parameter of mean-up crossing rate (MCR) is taken into account, which is important for reliability and failure analysis. Hopefully, our present work could provide insights into the investigation of structures under random loadings.
Binomial Gaussian mixture filter
NASA Astrophysics Data System (ADS)
Raitoharju, Matti; Ali-Löytty, Simo; Piché, Robert
2015-12-01
In this work, we present a novel method for approximating a normal distribution with a weighted sum of normal distributions. The approximation is used for splitting normally distributed components in a Gaussian mixture filter, such that components have smaller covariances and cause smaller linearization errors when nonlinear measurements are used for the state update. Our splitting method uses weights from the binomial distribution as component weights. The method preserves the mean and covariance of the original normal distribution, and in addition, the resulting probability density and cumulative distribution functions converge to the original normal distribution when the number of components is increased. Furthermore, an algorithm is presented to do the splitting such as to keep the linearization error below a given threshold with a minimum number of components. The accuracy of the estimate provided by the proposed method is evaluated in four simulated single-update cases and one time series tracking case. In these tests, it is found that the proposed method is more accurate than other Gaussian mixture filters found in the literature when the same number of components is used and that the proposed method is faster and more accurate than particle filters.
Stochastic resonance in Gaussian quantum channels
NASA Astrophysics Data System (ADS)
Lupo, Cosmo; Mancini, Stefano; Wilde, Mark M.
2013-02-01
We determine conditions for the presence of stochastic resonance in a lossy bosonic channel with a nonlinear, threshold decoding. The stochastic resonance effect occurs if and only if the detection threshold is outside of a ‘forbidden interval’. We show that it takes place in different settings: when transmitting classical messages through a lossy bosonic channel, when transmitting over an entanglement-assisted lossy bosonic channel and when discriminating channels with different loss parameters. Moreover, we consider a setting in which stochastic resonance occurs in the transmission of a qubit over a lossy bosonic channel with a particular encoding and decoding. In all cases, we assume the addition of Gaussian noise to the signal and show that it does not matter who, between sender and receiver, introduces such a noise. Remarkably, different results are obtained when considering a setting for private communication. In this case, the symmetry between sender and receiver is broken and the ‘forbidden interval’ may vanish, leading to the occurrence of stochastic resonance effects for any value of the detection threshold.
Luan, Shen
1995-10-06
This dissertation is focused on three problem areas in the performance of inductively coupled plasma (ICP) source. The noise characteristics of aerosols produced by ICP nebulizers are investigated. A laser beam is scattered by aerosol and detected by a photomultiplier tube and the noise amplitude spectrum of the scattered radiation is measured by a spectrum analyzer. Discrete frequency noise in the aerosol generated by a Meinhard nebulizer or a direct injection nebulizer is primarily caused by pulsation in the liquid flow from the pump. A Scott-type spray chamber suppresses white noise, while a conical, straight-pass spray chamber enhances white noise, relative to the noise seen from the primary aerosol. Simultaneous correction for both spectral interferences and matrix effects in ICP atomic emission spectrometry (AES) can be accomplished by using the generalized standard additions method (GSAM). Results obtained with the application of the GSAM to the Perkin-Elmer Optima 3000 ICP atomic emission spectrometer are presented. The echelle-based polychromator with segmented-array charge-coupled device detectors enables the direct, visual examination of the overlapping lines Cd (1) 228.802 nm and As (1) 228.812 nm. The slit translation capability allows a large number of data points to be sampled, therefore, the advantage of noise averaging is gained. An ICP is extracted into a small quartz vacuum chamber through a sampling orifice in a water-cooled copper plate. Optical emission from the Mach disk region is measured with a new type of echelle spectrometer equipped with two segmented-array charge-coupled-device detectors, with an effort to improve the detection limits for simultaneous multielement analysis by ICP-AES.
NASA Astrophysics Data System (ADS)
Dybiec, Bartłomiej; Gudowska-Nowak, Ewa
2009-05-01
A standard approach to analysis of noise-induced effects in stochastic dynamics assumes a Gaussian character of the noise term describing interaction of the analyzed system with its complex surroundings. An additional assumption about the existence of timescale separation between the dynamics of the measured observable and the typical timescale of the noise allows external fluctuations to be modeled as temporally uncorrelated and therefore white. However, in many natural phenomena the assumptions concerning the above mentioned properties of 'Gaussianity' and 'whiteness' of the noise can be violated. In this context, in contrast to the spatiotemporal coupling characterizing general forms of non-Markovian or semi-Markovian Lévy walks, so called Lévy flights correspond to the class of Markov processes which can still be interpreted as white, but distributed according to a more general, infinitely divisible, stable and non-Gaussian law. Lévy noise-driven non-equilibrium systems are known to manifest interesting physical properties and have been addressed in various scenarios of physical transport exhibiting a superdiffusive behavior. Here we present a brief overview of our recent investigations aimed at understanding features of stochastic dynamics under the influence of Lévy white noise perturbations. We find that the archetypal phenomena of noise-induced ordering are robust and can be detected also in systems driven by memoryless, non-Gaussian, heavy-tailed fluctuations with infinite variance.
Britten, A J; Crotty, M; Kiremidjian, H; Grundy, A; Adam, E J
2004-04-01
This study validates a method to add spatially correlated statistical noise to an image, applied to transaxial X-ray CT images of the head to simulate exposure reduction by up to 50%. 23 patients undergoing routine head CT had three additional slices acquired for validation purposes, two at the same clinical 420 mAs exposure and one at 300 mAs. Images at the level of the cerebrospinal fluid filled ventricles gave readings of noise from a single image, with subtraction of image pairs to obtain noise readings from non-uniform tissue regions. The spatial correlation of the noise was determined and added to the acquired 420 mAs image to simulate images at 340 mAs, 300 mAs, 260 mAs and 210 mAs. Two radiologists assessed the images, finding little difference between the 300 mAs simulated and acquired images. The presence of periventricular low density lesions (PVLD) was used as an example of the effect of simulated dose reduction on diagnostic accuracy, and visualization of the internal capsule was used as a measure of image quality. Diagnostic accuracy for the diagnosis of PVLD did not fall significantly even down to 210 mAs, though visualization of the internal capsule was poorer at lower exposure. Further work is needed to investigate means of measuring statistical noise without the need for uniform tissue areas, or image pairs. This technique has been shown to allow sufficiently accurate simulation of dose reduction and image quality degradation, even when the statistical noise is spatially correlated.
Speech Enhancement Using Gaussian Scale Mixture Models.
Hao, Jiucang; Lee, Te-Won; Sejnowski, Terrence J
2010-08-11
This paper presents a novel probabilistic approach to speech enhancement. Instead of a deterministic logarithmic relationship, we assume a probabilistic relationship between the frequency coefficients and the log-spectra. The speech model in the log-spectral domain is a Gaussian mixture model (GMM). The frequency coefficients obey a zero-mean Gaussian whose covariance equals to the exponential of the log-spectra. This results in a Gaussian scale mixture model (GSMM) for the speech signal in the frequency domain, since the log-spectra can be regarded as scaling factors. The probabilistic relation between frequency coefficients and log-spectra allows these to be treated as two random variables, both to be estimated from the noisy signals. Expectation-maximization (EM) was used to train the GSMM and Bayesian inference was used to compute the posterior signal distribution. Because exact inference of this full probabilistic model is computationally intractable, we developed two approaches to enhance the efficiency: the Laplace method and a variational approximation. The proposed methods were applied to enhance speech corrupted by Gaussian noise and speech-shaped noise (SSN). For both approximations, signals reconstructed from the estimated frequency coefficients provided higher signal-to-noise ratio (SNR) and those reconstructed from the estimated log-spectra produced lower word recognition error rate because the log-spectra fit the inputs to the recognizer better. Our algorithms effectively reduced the SSN, which algorithms based on spectral analysis were not able to suppress.
de Deckerk, Arnaud; Lee, John Aldo; Verlysen, Michel
2009-01-01
Denoising is a key step in the processing of medical images. It aims at improving both the interpretability and visual aspect of the images. Yet, designing a robust and efficient denoising tool remains an unsolved challenge and a specific issue concerns the noise model. Many filters typically assume that noise is additive and Gaussian, with uniform variance. In contrast, noise in medical images often has more complex properties. This paper considers images with Poissonian noise and the patch-based bilateral filters, that is, filters that involve a tonal kernel and pair wise comparisons between shifted blocks of the images. The main aim is then to integrate two variance stabilizing transformations that allow the filters to work with Gaussianized noise. The performances of these filters are compared to those of the classical bilateral filter with the same transformations. The experiments include an artificial benchmark as well as a positron emission tomography image.
Gaussian Intrinsic Entanglement
NASA Astrophysics Data System (ADS)
Mišta, Ladislav; Tatham, Richard
2016-12-01
We introduce a cryptographically motivated quantifier of entanglement in bipartite Gaussian systems called Gaussian intrinsic entanglement (GIE). The GIE is defined as the optimized mutual information of a Gaussian distribution of outcomes of measurements on parts of a system, conditioned on the outcomes of a measurement on a purifying subsystem. We show that GIE vanishes only on separable states and exhibits monotonicity under Gaussian local trace-preserving operations and classical communication. In the two-mode case, we compute GIE for all pure states as well as for several important classes of symmetric and asymmetric mixed states. Surprisingly, in all of these cases, GIE is equal to Gaussian Rényi-2 entanglement. As GIE is operationally associated with the secret-key agreement protocol and can be computed for several important classes of states, it offers a compromise between computable and physically meaningful entanglement quantifiers.
Gaussian benchmark for optical communication aiming towards ultimate capacity
NASA Astrophysics Data System (ADS)
Lee, Jaehak; Ji, Se-Wan; Park, Jiyong; Nha, Hyunchul
2016-05-01
We establish the fundamental limit of communication capacity within Gaussian schemes under phase-insensitive Gaussian channels, which employ multimode Gaussian states for encoding and collective Gaussian operations and measurements for decoding. We prove that this Gaussian capacity is additive, i.e., its upper bound occurs with separable encoding and separable receivers so that a single-mode communication suffices to achieve the largest capacity under Gaussian schemes. This rigorously characterizes the gap between the ultimate Holevo capacity and the capacity within Gaussian communication, showing that Gaussian regime is not sufficient to achieve the Holevo bound particularly in the low-photon regime. Furthermore, the Gaussian benchmark established here can be used to critically assess the performance of non-Gaussian protocols for optical communication. We move on to identify non-Gaussian schemes to beat the Gaussian capacity and show that a non-Gaussian receiver recently implemented by Becerra et al. [F. E. Becerra et al., Nat. Photon. 7, 147 (2013), 10.1038/nphoton.2012.316] can achieve this aim with an appropriately chosen encoding strategy.
Noise-driven optical absorption coefficients of impurity doped quantum dots
NASA Astrophysics Data System (ADS)
Ganguly, Jayanta; Saha, Surajit; Pal, Suvajit; Ghosh, Manas
2016-01-01
We make an extensive investigation of linear, third-order nonlinear, and total optical absorption coefficients (ACs) of impurity doped quantum dots (QDs) in presence and absence of noise. The noise invoked in the present study is a Gaussian white noise. The quantum dot is doped with repulsive Gaussian impurity. Noise has been introduced to the system additively and multiplicatively. A perpendicular magnetic field acts as a source of confinement and a static external electric field has been applied. The AC profiles have been studied as a function of incident photon energy when several important parameters such as optical intensity, electric field strength, magnetic field strength, confinement energy, dopant location, relaxation time, Al concentration, dopant potential, and noise strength take on different values. In addition, the role of mode of application of noise (additive/multiplicative) on the AC profiles has also been analyzed meticulously. The AC profiles often consist of a number of interesting observations such as one photon resonance enhancement, shift of AC peak position, variation of AC peak intensity, and bleaching of AC peak. However, presence of noise alters the features of AC profiles and leads to some interesting manifestations. Multiplicative noise brings about more complexity in the AC profiles than its additive counterpart. The observations indeed illuminate several useful aspects in the study of linear and nonlinear optical properties of doped QD systems, specially in presence of noise. The findings are expected to be quite relevant from a technological perspective.
Far-field errors due to random noise in cylindrical near-field measurements
NASA Astrophysics Data System (ADS)
Romeu, Jordi; Jofre, Luis; Cardama, Angel
1992-01-01
A full characterization of the far-field noise obtained from cylindrical near- to far-field transformation, for a white Gaussian, space stationary, near-field noise is derived. A possible source for such noise is the receiver additive noise. The noise characterization is done by obtaining the autocorrelation of the far-field noise, which is shown to be easily computed during the transformation process. Even for this simple case, the far-field noise has complex behavior dependent on the measurement probe. Once the statistical properties of the far-field noise are determined, it is possible to compute upper and lower bounds for the radiation pattern for a given probability. These bounds define a strip within the radiation pattern with the desired probability. This may be used as part of a complete near-field error analysis of a particular cylindrical near-field facility.
Banos, Oresti; Damas, Miguel; Pomares, Hector; Rojas, Ignacio
2012-01-01
The main objective of fusion mechanisms is to increase the individual reliability of the systems through the use of the collectivity knowledge. Moreover, fusion models are also intended to guarantee a certain level of robustness. This is particularly required for problems such as human activity recognition where runtime changes in the sensor setup seriously disturb the reliability of the initial deployed systems. For commonly used recognition systems based on inertial sensors, these changes are primarily characterized as sensor rotations, displacements or faults related to the batteries or calibration. In this work we show the robustness capabilities of a sensor-weighted fusion model when dealing with such disturbances under different circumstances. Using the proposed method, up to 60% outperformance is obtained when a minority of the sensors are artificially rotated or degraded, independent of the level of disturbance (noise) imposed. These robustness capabilities also apply for any number of sensors affected by a low to moderate noise level. The presented fusion mechanism compensates the poor performance that otherwise would be obtained when just a single sensor is considered. PMID:22969386
GAUSSIAN BEAM LASER RESONATOR PROGRAM
NASA Technical Reports Server (NTRS)
Cross, P. L.
1994-01-01
In designing a laser cavity, the laser engineer is frequently concerned with more than the stability of the resonator. Other considerations include the size of the beam at various optical surfaces within the resonator or the performance of intracavity line-narrowing or other optical elements. Laser resonators obey the laws of Gaussian beam propagation, not geometric optics. The Gaussian Beam Laser Resonator Program models laser resonators using Gaussian ray trace techniques. It can be used to determine the propagation of radiation through laser resonators. The algorithm used in the Gaussian Beam Resonator program has three major components. First, the ray transfer matrix for the laser resonator must be calculated. Next calculations of the initial beam parameters, specifically, the beam stability, the beam waist size and location for the resonator input element, and the wavefront curvature and beam radius at the input surface to the first resonator element are performed. Finally the propagation of the beam through the optical elements is computed. The optical elements can be modeled as parallel plates, lenses, mirrors, dummy surfaces, or Gradient Index (GRIN) lenses. A Gradient Index lens is a good approximation of a laser rod operating under a thermal load. The optical system may contain up to 50 elements. In addition to the internal beam elements the optical system may contain elements external to the resonator. The Gaussian Beam Resonator program was written in Microsoft FORTRAN (Version 4.01). It was developed for the IBM PS/2 80-071 microcomputer and has been implemented on an IBM PC compatible under MS DOS 3.21. The program was developed in 1988 and requires approximately 95K bytes to operate.
NASA Astrophysics Data System (ADS)
Bukofzer, Daniel C.
The performance of digital communication systems operating in the presence of noise and jamming is analyzed and evaluated. Specifically, by modeling the jamming as additive colored Gaussian noise, and considering transmission via M-ary phase shift keyed (MPSK) modulation as well as Quadrature Amplitude Modulation (QAM), receiver performance is determined in terms of symbol error probability, P(S). The receiver analyzed is optimum for the modulation used when the channel interference consists of additive white Gaussian noise (AWGN) only, and does not process signals utilizing spread spectrum modulation or forward error correction schemes. Furthermore, the derived results for P(S) are used in order to optimize the shape of the colored noise (jamming) spectrum so as to cause maximum receiver degradation, subject to a jamming power constraint. Results on numerical evaluations are presented graphically, thus displaying receiver vulnerability to a specific form of jamming.
NASA Astrophysics Data System (ADS)
Khodja, Mohamed; Belouchrani, Adel; Abed-Meraim, Karim
2012-12-01
This article deals with the application of Spatial Time-Frequency Distribution (STFD) to the direction finding problem using the Multiple Signal Classification (MUSIC)algorithm. A comparative performance analysis is performed for the method under consideration with respect to that using data covariance matrix when the received array signals are subject to calibration errors in a non-stationary environment. An unified analytical expression of the Direction Of Arrival (DOA) error estimation is derived for both methods. Numerical results show the effect of the parameters intervening in the derived expression on the algorithm performance. It is particularly observed that for low Signal to Noise Ratio (SNR) and high Signal to sensor Perturbation Ratio (SPR) the STFD method gives better performance, while for high SNR and for the same SPR both methods give similar performance.
NASA Astrophysics Data System (ADS)
Hanel, R.; Thurner, S.; Tsallis, C.
2009-11-01
Extremization of the Boltzmann-Gibbs (BG) entropy S_{BG}=-kint dx p(x) ln p(x) under appropriate norm and width constraints yields the Gaussian distribution pG(x) ∝e-βx. Also, the basic solutions of the standard Fokker-Planck (FP) equation (related to the Langevin equation with additive noise), as well as the Central Limit Theorem attractors, are Gaussians. The simplest stochastic model with such features is N ↦∞ independent binary random variables, as first proved by de Moivre and Laplace. What happens for strongly correlated random variables? Such correlations are often present in physical situations as e.g. systems with long range interactions or memory. Frequently q-Gaussians, pq(x) ∝[1-(1-q)βx2]1/(1-q) [p1(x)=pG(x)] become observed. This is typically so if the Langevin equation includes multiplicative noise, or the FP equation to be nonlinear. Scale-invariance, e.g. exchangeable binary stochastic processes, allow a systematical analysis of the relation between correlations and non-Gaussian distributions. In particular, a generalized stochastic model yielding q-Gaussians for all (q ≠ 1) was missing. This is achieved here by using the Laplace-de Finetti representation theorem, which embodies strict scale-invariance of interchangeable random variables. We demonstrate that strict scale invariance together with q-Gaussianity mandates the associated extensive entropy to be BG.
Hammouda, Boualem
2014-01-01
It is common practice to assume that Bragg scattering peaks have Gaussian shape. The Gaussian shape function is used to perform most instrumental smearing corrections. Using Monte Carlo ray tracing simulation, the resolution of a realistic small-angle neutron scattering (SANS) instrument is generated reliably. Including a single-crystal sample with large d-spacing, Bragg peaks are produced. Bragg peaks contain contributions from the resolution function and from spread in the sample structure. Results show that Bragg peaks are Gaussian in the resolution-limited condition (with negligible sample spread) while this is not the case when spread in the sample structure is non-negligible. When sample spread contributes, the exponentially modified Gaussian function is a better account of the Bragg peak shape. This function is characterized by a non-zero third moment (skewness) which makes Bragg peaks asymmetric for broad neutron wavelength spreads. PMID:26601025
Gaussian operations and privacy
Navascues, Miguel; Acin, Antonio
2005-07-15
We consider the possibilities offered by Gaussian states and operations for two honest parties, Alice and Bob, to obtain privacy against a third eavesdropping party, Eve. We first extend the security analysis of the protocol proposed in [Navascues et al. Phys. Rev. Lett. 94, 010502 (2005)]. Then, we prove that a generalized version of this protocol does not allow one to distill a secret key out of bound entangled Gaussian states.
Huidobro, Nayeli; Silva, Mayte; Flores, Amira; Trenado, Carlos; Quintanar, Luis; Arias-Carrión, Oscar; Kristeva, Rumyana
2015-01-01
The present investigation documents the electrophysiological occurrence of multisensory stochastic resonance in the human visual pathway elicited by tactile noise. We define multisensory stochastic resonance of brain evoked potentials as the phenomenon in which an intermediate level of input noise of one sensory modality enhances the brain evoked response of another sensory modality. Here we examined this phenomenon in visual evoked potentials (VEPs) modulated by the addition of tactile noise. Specifically, we examined whether a particular level of mechanical Gaussian noise applied to the index finger can improve the amplitude of the VEP. We compared the amplitude of the positive P100 VEP component between zero noise (ZN), optimal noise (ON), and high mechanical noise (HN). The data disclosed an inverted U-like graph for all the subjects, thus demonstrating the occurrence of a multisensory stochastic resonance in the P100 VEP. PMID:26156387
Méndez-Balbuena, Ignacio; Huidobro, Nayeli; Silva, Mayte; Flores, Amira; Trenado, Carlos; Quintanar, Luis; Arias-Carrión, Oscar; Kristeva, Rumyana; Manjarrez, Elias
2015-10-01
The present investigation documents the electrophysiological occurrence of multisensory stochastic resonance in the human visual pathway elicited by tactile noise. We define multisensory stochastic resonance of brain evoked potentials as the phenomenon in which an intermediate level of input noise of one sensory modality enhances the brain evoked response of another sensory modality. Here we examined this phenomenon in visual evoked potentials (VEPs) modulated by the addition of tactile noise. Specifically, we examined whether a particular level of mechanical Gaussian noise applied to the index finger can improve the amplitude of the VEP. We compared the amplitude of the positive P100 VEP component between zero noise (ZN), optimal noise (ON), and high mechanical noise (HN). The data disclosed an inverted U-like graph for all the subjects, thus demonstrating the occurrence of a multisensory stochastic resonance in the P100 VEP.
The method of narrow-band audio classification based on universal noise background model
NASA Astrophysics Data System (ADS)
Rui, Rui; Bao, Chang-chun
2013-03-01
Audio classification is the basis of content-based audio analysis and retrieval. The conventional classification methods mainly depend on feature extraction of audio clip, which certainly increase the time requirement for classification. An approach for classifying the narrow-band audio stream based on feature extraction of audio frame-level is presented in this paper. The audio signals are divided into speech, instrumental music, song with accompaniment and noise using the Gaussian mixture model (GMM). In order to satisfy the demand of actual environment changing, a universal noise background model (UNBM) for white noise, street noise, factory noise and car interior noise is built. In addition, three feature schemes are considered to optimize feature selection. The experimental results show that the proposed algorithm achieves a high accuracy for audio classification, especially under each noise background we used and keep the classification time less than one second.
A note on the wideband Gaussian broadcast channel
NASA Technical Reports Server (NTRS)
Mceliece, R. J.; Posner, E. C.; Swanson, L.
1986-01-01
It is well known that for the Gaussian broadcast channel, timeshared coding is not as efficient as more sophisticated broadcast coding strategies. However, the relative advantage of broadcast coding over timeshared coding is shown to be small if the signal-to-noise ratios of both receivers are small. One surprising consequence of this is that for the wideband Gaussian broadcast channel, which is defined, broadcast coding offers no advantage over timeshared coding at all, and so timeshared coding is optimal.
A stochastic resonator is able to greatly improve signal-to-noise ratio
NASA Astrophysics Data System (ADS)
Loerincz, K.; Gingl, Z.; Kiss, L. B.
1996-02-01
After a decade of doubts, for the first time in the history of stochastic resonance (SR), we demonstrate that a simple stochastic resonator does greatly improve the signal-to-noise ratio (SNR) of a periodic signal with additive Gaussian noise. The particular stochastic resonator is a level-crossing detector (LCD) driven by the sum of a periodic spike train signal and a band-limited Gaussian white noise. To reach the improvement of the SNR, the stochastic resonator has to work in the strongly nonlinear response limit and the noise has to have a high cut-off frequency compared to the reciprocal duration of the spikes. We demonstrate by analog and computer simulations that the SNR gain goes beyond four orders of magnitude at practical conditions. These findings get a particular importance due the fact that simplest neurone models behave very similarly to our arrangement, so the results might have direct applications in neural systems.
NASA Astrophysics Data System (ADS)
Bera, Aindrila; Ghosh, Manas
2017-01-01
We investigate the total optical dielectric function (TODF) of impurity doped QDs under the combined influence of hydrostatic pressure (HP) and temperature and in presence of Gaussian white noise. Noise has been incorporated to the system additively and multiplicatively. Variations of HP, temperature and noise strength affect TODF profile in subtle way. And the subtlety also depends on mode of application of noise. Extrapolation of the present study would be important in understanding the effective optical properties of the system under given conditions of HP and temperature and in presence of noise.
Automatic modulation classification of digital modulations in presence of HF noise
NASA Astrophysics Data System (ADS)
Alharbi, Hazza; Mobien, Shoaib; Alshebeili, Saleh; Alturki, Fahd
2012-12-01
Designing an automatic modulation classifier (AMC) for high frequency (HF) band is a research challenge. This is due to the recent observation that noise distribution in HF band is changing over time. Existing AMCs are often designed for one type of noise distribution, e.g., additive white Gaussian noise. This means their performance is severely compromised in the presence of HF noise. Therefore, an AMC capable of mitigating the time-varying nature of HF noise is required. This article presents a robust AMC method for the classification of FSK, PSK, OQPSK, QAM, and amplitude-phase shift keying modulations in presence of HF noise using feature-based methods. Here, extracted features are insensitive to symbol synchronization and carrier frequency and phase offsets. The proposed AMC method is simple to implement as it uses decision-tree approach with pre-computed thresholds for signal classification. In addition, it is capable to classify type and order of modulation in both Gaussian and non-Gaussian environments.
Mixed noise removal by weighted encoding with sparse nonlocal regularization.
Jiang, Jielin; Zhang, Lei; Yang, Jian
2014-06-01
Mixed noise removal from natural images is a challenging task since the noise distribution usually does not have a parametric model and has a heavy tail. One typical kind of mixed noise is additive white Gaussian noise (AWGN) coupled with impulse noise (IN). Many mixed noise removal methods are detection based methods. They first detect the locations of IN pixels and then remove the mixed noise. However, such methods tend to generate many artifacts when the mixed noise is strong. In this paper, we propose a simple yet effective method, namely weighted encoding with sparse nonlocal regularization (WESNR), for mixed noise removal. In WESNR, there is not an explicit step of impulse pixel detection; instead, soft impulse pixel detection via weighted encoding is used to deal with IN and AWGN simultaneously. Meanwhile, the image sparsity prior and nonlocal self-similarity prior are integrated into a regularization term and introduced into the variational encoding framework. Experimental results show that the proposed WESNR method achieves leading mixed noise removal performance in terms of both quantitative measures and visual quality.
A neural-network based estimator to search for primordial non-Gaussianity in Planck CMB maps
Novaes, C.P.; Bernui, A.; Ferreira, I.S.; Wuensche, C.A. E-mail: bernui@on.br E-mail: ca.wuensche@inpe.br
2015-09-01
We present an upgraded combined estimator, based on Minkowski Functionals and Neural Networks, with excellent performance in detecting primordial non-Gaussianity in simulated maps that also contain a weighted mixture of Galactic contaminations, besides real pixel's noise from Planck cosmic microwave background radiation data. We rigorously test the efficiency of our estimator considering several plausible scenarios for residual non-Gaussianities in the foreground-cleaned Planck maps, with the intuition to optimize the training procedure of the Neural Network to discriminate between contaminations with primordial and secondary non-Gaussian signatures. We look for constraints of primordial local non-Gaussianity at large angular scales in the foreground-cleaned Planck maps. For the SMICA map we found f{sub NL} = 33 ± 23, at 1σ confidence level, in excellent agreement with the WMAP-9yr and Planck results. In addition, for the other three Planck maps we obtain similar constraints with values in the interval f{sub NL} element of [33, 41], concomitant with the fact that these maps manifest distinct features in reported analyses, like having different pixel's noise intensities.
A weighted dictionary learning model for denoising images corrupted by mixed noise.
Liu, Jun; Tai, Xue-Cheng; Huang, Haiyang; Huan, Zhongdan
2013-03-01
This paper proposes a general weighted l(2)-l(0) norms energy minimization model to remove mixed noise such as Gaussian-Gaussian mixture, impulse noise, and Gaussian-impulse noise from the images. The approach is built upon maximum likelihood estimation framework and sparse representations over a trained dictionary. Rather than optimizing the likelihood functional derived from a mixture distribution, we present a new weighting data fidelity function, which has the same minimizer as the original likelihood functional but is much easier to optimize. The weighting function in the model can be determined by the algorithm itself, and it plays a role of noise detection in terms of the different estimated noise parameters. By incorporating the sparse regularization of small image patches, the proposed method can efficiently remove a variety of mixed or single noise while preserving the image textures well. In addition, a modified K-SVD algorithm is designed to address the weighted rank-one approximation. The experimental results demonstrate its better performance compared with some existing methods.
Generation of short and long range temporal correlated noise
Romero, A.H.; Sancho, J.M.
1999-11-20
The authors present the implementation of an algorithm to generate Gaussian random noises with prescribed time correlations that can be either long or short ranged. Examples of Langevin dynamics with short and long range noises are presented and discussed.
Calculation of mutual information for nonlinear communication channel at large signal-to-noise ratio
NASA Astrophysics Data System (ADS)
Terekhov, I. S.; Reznichenko, A. V.; Turitsyn, S. K.
2016-10-01
Using the path-integral technique we examine the mutual information for the communication channel modeled by the nonlinear Schrödinger equation with additive Gaussian noise. The nonlinear Schrödinger equation is one of the fundamental models in nonlinear physics, and it has a broad range of applications, including fiber optical communications—the backbone of the internet. At large signal-to-noise ratio we present the mutual information through the path-integral, which is convenient for the perturbative expansion in nonlinearity. In the limit of small noise and small nonlinearity we derive analytically the first nonzero nonlinear correction to the mutual information for the channel.
Fast and reliable image-noise estimation using a hybrid approach
NASA Astrophysics Data System (ADS)
Yang, Shih-Ming; Tai, Shen-Chuan
2010-07-01
Image denoising algorithms often require their parameters to be adjusted according to the noise level. We propose a fast and reliable method for estimating image noise. The input image is assumed to be contaminated by an additive white Gaussian noise process. To exclude structures or details from contributing to the estimation of noise variance, a Sobel edge detection operator with a self-determined threshold is first applied to each image block. Then a filter operation, followed by an averaging of the convolutions over the selected blocks, provides a very accurate estimation of noise variance. We successfully combine the effectiveness of filter-based approaches with the efficiency of block-based approaches, and the simulated results demonstrate that the proposed method performs well for a variety of images over a large range of noise variances. Performance comparisons against other approaches are also provided.
Noise to lubricate qubit transfer in a spin network
NASA Astrophysics Data System (ADS)
Rafiee, Morteza; Lupo, Cosmo; Mancini, Stefano
2013-09-01
We consider quantum state transfer in a fully connected spin network, in which the results indicate that it is impossible to achieve high fidelity by free dynamics. However, the addition of certain kinds of noise can be helpful for this purpose. In fact, we introduce a model of Gaussian white noise affecting the spin-spin couplings (edges), except those linked to the input and output node, and prove that it enhances the fidelity of state transfer. The observed noise benefit is scale free as it applies to a quantum network of any size. The amount of the fidelity enhancement, depending on the noise strength as well as on the number of edges to which it is applied, can be so high as to take the fidelity close to one.
NGMIX: Gaussian mixture models for 2D images
NASA Astrophysics Data System (ADS)
Sheldon, Erin
2015-08-01
NGMIX implements Gaussian mixture models for 2D images. Both the PSF profile and the galaxy are modeled using mixtures of Gaussians. Convolutions are thus performed analytically, resulting in fast model generation as compared to methods that perform the convolution in Fourier space. For the galaxy model, NGMIX supports exponential disks and de Vaucouleurs and Sérsic profiles; these are implemented approximately as a sum of Gaussians using the fits from Hogg & Lang (2013). Additionally, any number of Gaussians can be fit, either completely free or constrained to be cocentric and co-elliptical.
On Gaussian random supergravity
NASA Astrophysics Data System (ADS)
Bachlechner, Thomas C.
2014-04-01
We study the distribution of metastable vacua and the likelihood of slow roll inflation in high dimensional random landscapes. We consider two examples of landscapes: a Gaussian random potential and an effective supergravity potential defined via a Gaussian random superpotential and a trivial Kähler potential. To examine these landscapes we introduce a random matrix model that describes the correlations between various derivatives and we propose an efficient algorithm that allows for a numerical study of high dimensional random fields. Using these novel tools, we find that the vast majority of metastable critical points in N dimensional random supergravities are either approximately supersymmetric with | F| ≪ M susy or supersymmetric. Such approximately supersymmetric points are dynamical attractors in the landscape and the probability that a randomly chosen critical point is metastable scales as log( P ) ∝ - N. We argue that random supergravities lead to potentially interesting inflationary dynamics.
Adaptive Gaussian Pattern Classification
1988-08-01
redundant model of the data to be used in classification . There are two classes of learning, or adaptation schemes. The first, unsupervised learning...37, No. 3, pp. 242-247, 1983. [2] E. F. Codd, Cellular Automata , Academic Press, 1968. [31 H. Everett, G. Gilbreath, S. Alderson, D. J. Marchette...Na al Oca aytm aete !JTI FL E COPY AD-A 199 030 Technical Document 1335 August 1988 Adaptive Gaussian Pattern Classif ication C. E. Priebe D. J
Flauger, Raphael; Pajer, Enrico E-mail: ep295@cornell.edu
2011-01-01
We provide a derivation from first principles of the primordial bispectrum of scalar perturbations produced during inflation driven by a canonically normalized scalar field whose potential exhibits small sinusoidal modulations. A potential of this type has been derived in a class of string theory models of inflation based on axion monodromy. We use this model as a concrete example, but we present our derivations and results for a general slow-roll potential with superimposed modulations. We show analytically that a resonance between the oscillations of the background and the oscillations of the fluctuations is responsible for the production of an observably large non-Gaussian signal. We provide an explicit expression for the shape of this resonant non-Gaussianity. We show that there is essentially no overlap between this shape and the local, equilateral, and orthogonal shapes, and we stress that resonant non-Gaussianity is not captured by the simplest version of the effective field theory of inflation. We hope our analytic expression will be useful to further observationally constrain this class of models.
Gaussian Quadrature Formulae for Arbitrary Positive Measures
Fernandes, Andrew D.; Atchley, William R.
2007-01-01
We present computational methods and subroutines to compute Gaussian quadrature integration formulas for arbitrary positive measures. For expensive integrands that can be factored into well-known forms, Gaussian quadrature schemes allow for efficient evaluation of high-accuracy and -precision numerical integrals, especially compared to general ad hoc schemes. In addition, for certain well-known density measures (the normal, gamma, log-normal, Student’s t, inverse-gamma, beta, and Fisher’s F) we present exact formulae for computing the respective quadrature scheme. PMID:19455218
Graphical calculus for Gaussian pure states
Menicucci, Nicolas C.; Flammia, Steven T.; Loock, Peter van
2011-04-15
We provide a unified graphical calculus for all Gaussian pure states, including graph transformation rules for all local and semilocal Gaussian unitary operations, as well as local quadrature measurements. We then use this graphical calculus to analyze continuous-variable (CV) cluster states, the essential resource for one-way quantum computing with CV systems. Current graphical approaches to CV cluster states are only valid in the unphysical limit of infinite squeezing, and the associated graph transformation rules only apply when the initial and final states are of this form. Our formalism applies to all Gaussian pure states and subsumes these rules in a natural way. In addition, the term 'CV graph state' currently has several inequivalent definitions in use. Using this formalism we provide a single unifying definition that encompasses all of them. We provide many examples of how the formalism may be used in the context of CV cluster states: defining the 'closest' CV cluster state to a given Gaussian pure state and quantifying the error in the approximation due to finite squeezing; analyzing the optimality of certain methods of generating CV cluster states; drawing connections between this graphical formalism and bosonic Hamiltonians with Gaussian ground states, including those useful for CV one-way quantum computing; and deriving a graphical measure of bipartite entanglement for certain classes of CV cluster states. We mention other possible applications of this formalism and conclude with a brief note on fault tolerance in CV one-way quantum computing.
Adaptive noise Wiener filter for scanning electron microscope imaging system.
Sim, K S; Teh, V; Nia, M E
2016-01-01
Noise on scanning electron microscope (SEM) images is studied. Gaussian noise is the most common type of noise in SEM image. We developed a new noise reduction filter based on the Wiener filter. We compared the performance of this new filter namely adaptive noise Wiener (ANW) filter, with four common existing filters as well as average filter, median filter, Gaussian smoothing filter and the Wiener filter. Based on the experiments results the proposed new filter has better performance on different noise variance comparing to the other existing noise removal filters in the experiments.
Gaussian entanglement in the turbulent atmosphere
NASA Astrophysics Data System (ADS)
Bohmann, M.; Semenov, A. A.; Sperling, J.; Vogel, W.
2016-07-01
We provide a rigorous treatment of the entanglement properties of two-mode Gaussian states in atmospheric channels by deriving and analyzing the input-output relations for the corresponding entanglement test. A key feature of such turbulent channels is a nontrivial dependence of the transmitted continuous-variable entanglement on coherent displacements of the quantum state of the input field. Remarkably, this allows one to optimize the entanglement certification by modifying local coherent amplitudes using a finite, but optimal amount of squeezing. In addition, we propose a protocol which, in principle, renders it possible to transfer the Gaussian entanglement through any turbulent channel over arbitrary distances. Therefore, our approach provides the theoretical foundation for advanced applications of Gaussian entanglement in free-space quantum communication.
NASA Astrophysics Data System (ADS)
Terrillon, Jean-Christophe
1995-11-01
The comparative effects of optical-correlator signal-dependent and additive signal-independent noise on correlation-filter performance are analyzed by three different performance measures. For an identical value of the signal-to-noise ratio imposed on each type of noise in a binary input image, computer simulations performed with the phase-only filter show (i) that additive Gaussian signal-independent noise yields a much larger correlation-performance degradation than signal-dependent noise and (ii) that the different types of signal-dependent noise lead to similar correlation results because of similar effects on the input image that are inherent to the nature of the noise.
Distributions of Conductance and Shot Noise and Associated Phase Transitions
Vivo, Pierpaolo; Majumdar, Satya N.; Bohigas, Oriol
2008-11-21
For a chaotic cavity with two identical leads each supporting N channels, we compute analytically, for large N, the full distribution of the conductance and the shot noise power and show that in both cases there is a central Gaussian region flanked on both sides by non-Gaussian tails. The distribution is weakly singular at the junction of Gaussian and non-Gaussian regimes, a direct consequence of two phase transitions in an associated Coulomb gas problem.
NASA Technical Reports Server (NTRS)
Tranter, W. H.; Turner, M. D.
1977-01-01
Techniques are developed to estimate power gain, delay, signal-to-noise ratio, and mean square error in digital computer simulations of lowpass and bandpass systems. The techniques are applied to analog and digital communications. The signal-to-noise ratio estimates are shown to be maximum likelihood estimates in additive white Gaussian noise. The methods are seen to be especially useful for digital communication systems where the mapping from the signal-to-noise ratio to the error probability can be obtained. Simulation results show the techniques developed to be accurate and quite versatile in evaluating the performance of many systems through digital computer simulation.
NASA Astrophysics Data System (ADS)
Osicka, Teresa; Freedman, Matthew T.; Ahmed, Farid
2007-03-01
The goal of this project is to use computer analysis to classify small lung nodules, identified on CT, into likely benign and likely malignant categories. We compared discrete wavelet transforms (DWT) based features and a modification of classical features used and reported by others. To determine the best combination of features for classification, several intensities of white noise were added to the original images to determine the effect of such noise on classification accuracy. Two different approaches were used to determine the effect of noise: in the first method the best features for classification of nodules on the original image were retained as noise was added. In the second approach, we recalculated the results to reselect the best classification features for each particular level of added noise. The CT images are from the National Lung Screening Trial (NLST) of the National Cancer Institute (NCI). For this study, nodules were extracted in window frames of three sizes. Malignant nodules were cytologically or histogically diagnosed, while benign had two-year follow-up. A linear discriminant analysis with Fisher criterion (FLDA) approach was used for feature selection and classification, and decision matrix for matched sample to compare the classification accuracy. The initial features mode revealed sensitivity to both the amount of noise and the size of window frame. The recalculated feature mode proved more robust to noise with no change in terms of classification accuracy. This indicates that the best features for computer classification of lung nodules will differ with noise, and, therefore, with exposure.
M-Ary Alpha-Stable Noise Modulation in Spread-Spectrum Communication
NASA Astrophysics Data System (ADS)
Cek, Mehmet Emre
2015-04-01
In this paper, a spread-spectrum communication system based on a random carrier is proposed which transmits M-ary information. The random signal is considered as a single realization of a random process taken from prescribed symmetric α-stable (SαS) distribution that carries digital M-ary information to be transmitted. Considering the noise model in the channel as additive white Gaussian noise (AWGN), the transmitter sends the information carrying random signal from non-Gaussian density. Alpha-stable distribution is used to encode the M-ary message. Inspired by the chaos shift keying techniques, the proposed method is called M-ary symmetric alpha-stable differential shift keying (M-ary SαS-DSK). The main purpose of preferring non-Gaussian noise instead of conventional pseudo-noise (PN) sequence is to overcome the drawback of self-repeating noise-like sequences which are detectable due to the periodic behavior of the autocorrelation function of PN sequences. Having infinite second order moment in α-stable random carrier offers secrecy of the information due to the non-constant autocorrelation behavior. The bit error rate (BER) performance of the proposed method is illustrated by Monte Carlo simulations with respect to various characteristic exponent values and different data length.
Enhanced corticomuscular coherence by external stochastic noise
Trenado, Carlos; Mendez-Balbuena, Ignacio; Manjarrez, Elias; Huethe, Frank; Schulte-Mönting, Jürgen; Feige, Bernd; Hepp-Reymond, Marie-Claude; Kristeva, Rumyana
2014-01-01
Noise can have beneficial effects as shown by the stochastic resonance (SR) phenomenon which is characterized by performance improvement when an optimal noise is added. Modern attempts to improve human performance utilize this phenomenon. The purpose of the present study was to investigate whether performance improvement by addition of optimum noise (ON) is related to increased cortical motor spectral power (SP) and increased corticomuscular coherence. Eight subjects performed a visuomotor task requiring to compensate with the right index finger a static force (SF) generated by a manipulandum on which Gaussian noise was applied. The finger position was displayed on-line on a monitor as a small white dot which the subjects had to maintain in the center of a green bigger circle. Electroencephalogram from the contralateral motor area, electromyogram from active muscles and finger position were recorded. The performance was measured by the mean absolute deviation (MAD) of the white dot from the zero position. ON compared to the zero noise condition induced an improvement in motor accuracy together with an enhancement of cortical motor SP and corticomuscular coherence in beta-range. These data suggest that the improved sensorimotor performance via SR is consistent with an increase in the cortical motor SP and in the corticomuscular coherence. PMID:24904365
Judgments of aircraft noise in a traffic noise background
NASA Technical Reports Server (NTRS)
Powell, C. A.; Rice, C. G.
1975-01-01
An investigation was conducted to determine subjective response to aircraft noise in different road traffic backgrounds. In addition, two laboratory techniques for presenting the aircraft noise with the background noise were evaluated. For one technique, the background noise was continuous over an entire test session; for the other, the background noise level was changed with each aircraft noise during a session. Subjective response to aircraft noise was found to decrease with increasing background noise level, for a range of typical indoor noise levels. Subjective response was found to be highly correlated with the Noise Pollution Level (NPL) measurement scale.
Truncated Gaussians as tolerance sets
NASA Technical Reports Server (NTRS)
Cozman, Fabio; Krotkov, Eric
1994-01-01
This work focuses on the use of truncated Gaussian distributions as models for bounded data measurements that are constrained to appear between fixed limits. The authors prove that the truncated Gaussian can be viewed as a maximum entropy distribution for truncated bounded data, when mean and covariance are given. The characteristic function for the truncated Gaussian is presented; from this, algorithms are derived for calculation of mean, variance, summation, application of Bayes rule and filtering with truncated Gaussians. As an example of the power of their methods, a derivation of the disparity constraint (used in computer vision) from their models is described. The authors' approach complements results in Statistics, but their proposal is not only to use the truncated Gaussian as a model for selected data; they propose to model measurements as fundamentally in terms of truncated Gaussians.
Yu, Hancheng; Gao, Jianlin; Li, Aiting
2016-03-01
In this Letter, a probability-based non-local means filter is proposed for speckle reduction in optical coherence tomography (OCT). Originally developed for additive white Gaussian noise, the non-local means filter is not suitable for multiplicative speckle noise suppression. This Letter presents a two-stage non-local means algorithm using the uncorrupted probability of each pixel to effectively reduce speckle noise in OCT. Experiments on real OCT images demonstrate that the proposed filter is competitive with other state-of-the-art speckle removal techniques and able to accurately preserve edges and structural details with small computational cost.
A tremor detector based on Gaussianity differences
NASA Astrophysics Data System (ADS)
Dorman, L. M.; Schwartz, S. Y.; Tryon, M. D.
2011-12-01
Slip occurring at plate boundaries creates seismic tremor as well as "normal" earthquakes. This nonvolcanic tremor appears to consist of swarms of low-frequency earthquakes which lack impulsive P and S arrivals. Tremor is accompanied by slip observed by GPS and can show anomalies in fluid flow. The seismic radiation resembles continuous microseismic noise more than discrete events. We report dual-frequency coherence (DFC) calculations on tremor and normal microseismic background noise observed on Ocean-Bottom Seismographs and land seismic stations around the Nicoya Peninsula, Costa Rica. Both the OBS and land tremor signals show a banded pattern in DFC that is absent in normal noise. The similarity in the DFC patterns between OBS and land tremor signals suggests a common source, eliminating the possibility that DFC is a property of the OBS or seafloor environment. Banded DFC patterns can be generated by repeated events with a repeat time equal to the reciprocal of the offset frequency between bands. If, as is becoming widely accepted, nonvolcanic tremor consists of swarms of low frequency earthquakes (LFE), DFC analysis may help to reveal LFE periodicities or intervals. Timeseries statistics measuring departures from Gaussianity differ between time periods containing tremor and those with only background noise, and the statistic "S" can be used as a detection statistic. We show the Receiver Operating Characteristic for such a detector.
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.
NASA Astrophysics Data System (ADS)
Saha, Surajit; Ganguly, Jayanta; Bera, Aindrila; Ghosh, Manas
2016-11-01
We explore the diamagnetic susceptibility (DMS) of impurity doped quantum dot (QD) in presence of Gaussian white noise and under the combined influence of hydrostatic pressure (HP) and temperature (T). Presence of noise and also its mode of application discernibly affect the DMS profile. Application of HP and T invites greater delicacies in the observed DMS profiles. However, whereas the interplay between T and noise comes out to be extremely sensitive in fabricating the DMS profile, the pressure-noise interplay appears to be not that much noticeable. Under all conditions of temperature and pressure, the presence of multiplicative noise diminishes the value of DMS in comparison with that in presence of its additive analogue. The present study renders a deep insight into the remarkable role played by the interplay between noise, hydrostatic pressure and temperature in controlling the effective confinement imposed on the system which bears unquestionable relevance.
Note on non-Gaussianities in two-field inflation
NASA Astrophysics Data System (ADS)
Wang, Tower
2010-12-01
Two-field slow-roll inflation is the most conservative modification of a single-field model. The main motivations to study it are its entropic mode and non-Gaussianity. Several years ago, for a two-field model with additive separable potentials, Vernizzi and Wands invented an analytic method to estimate its non-Gaussianities. Later on, Choi et al. applied this method to the model with multiplicative separable potentials. In this note, we design a larger class of models whose non-Gaussianity can be estimated by the same method. Under some simplistic assumptions, roughly these models are unlikely able to generate a large non-Gaussianity. We look over some specific models of this class by scanning the full parameter space, but still no large non-Gaussianity appears in the slow-roll region. These models and scanning techniques would be useful for a future model hunt if observational evidence shows up for two-field inflation.
Distillation and purification of symmetric entangled Gaussian states
Fiurasek, Jaromir
2010-10-15
We propose an entanglement distillation and purification scheme for symmetric two-mode entangled Gaussian states that allows to asymptotically extract a pure entangled Gaussian state from any input entangled symmetric Gaussian state. The proposed scheme is a modified and extended version of the entanglement distillation protocol originally developed by Browne et al. [Phys. Rev. A 67, 062320 (2003)]. A key feature of the present protocol is that it utilizes a two-copy degaussification procedure that involves a Mach-Zehnder interferometer with single-mode non-Gaussian filters inserted in its two arms. The required non-Gaussian filtering operations can be implemented by coherently combining two sequences of single-photon addition and subtraction operations.
Rossi, Matteo A. C.; Paris, Matteo G. A.
2016-01-14
We address the interaction of single- and two-qubit systems with an external transverse fluctuating field and analyze in detail the dynamical decoherence induced by Gaussian noise and random telegraph noise (RTN). Upon exploiting the exact RTN solution of the time-dependent von Neumann equation, we analyze in detail the behavior of quantum correlations and prove the non-Markovianity of the dynamical map in the full parameter range, i.e., for either fast or slow noise. The dynamics induced by Gaussian noise is studied numerically and compared to the RTN solution, showing the existence of (state dependent) regions of the parameter space where the two noises lead to very similar dynamics. We show that the effects of RTN noise and of Gaussian noise are different, i.e., the spectrum alone is not enough to summarize the noise effects, but the dynamics under the effect of one kind of noise may be simulated with high fidelity by the other one.
Noise-enhanced phase synchronization in time-delayed systems.
Senthilkumar, D V; Shrii, M Manju; Kurths, J
2012-02-01
We investigate the phenomenon of noise-enhanced phase synchronization (PS) in coupled time-delay systems, which usually exhibit non-phase-coherent attractors with complex topological properties. As a delay system is essentially an infinite dimensional in nature with multiple characteristic time scales, it is interesting and crucial to understand the interplay of noise and the time scales in achieving PS. In unidirectionally coupled systems, the response system adjust all its time scales to that of the drive, whereas both subsystems adjust their rhythms to a single (main time scale of the uncoupled system) time scale in bidirectionally coupled systems. We find similar effects for both a common and an independent additive Gaussian noise.
Gaussian ARTMAP: A Neural Network for Fast Incremental Learning of Noisy Multidimensional Maps.
Williamson, James R.
1996-07-01
A new neural network architecture for incremental supervised learning of analog multidimensional maps is introduced. The architecture, called Gaussian ARTMAP, is a synthesis of a Gaussian classifier and an adaptive resonance theory (ART) neural network, achieved by defining the ART choice function as the discriminant function of a Gaussian classifier with separable distributions, and the ART match function as the same, but with the distributions normalized to a unit height. While Gaussian ARTMAP retains the attractive parallel computing and fast learning properties of fuzzy ARTMAP, it learns a more efficient internal representation of a mapping while being more resistant to noise than fuzzy ARTMAP on a number of benchmark databases. SSeveral simulations are presented which demonstrate that Gaussian ARTMAP consistently obtains a better trade-off of classification rate to number of categories than fuzzy ARTMAP. Results on a vowel classification problem are also presented which demonstrate that Gaussian ARTMAP outperforms many other classifiers. Copyright 1996 Elsevier Science Ltd
Normal form decomposition for Gaussian-to-Gaussian superoperators
De Palma, Giacomo; Mari, Andrea; Giovannetti, Vittorio; Holevo, Alexander S.
2015-05-15
In this paper, we explore the set of linear maps sending the set of quantum Gaussian states into itself. These maps are in general not positive, a feature which can be exploited as a test to check whether a given quantum state belongs to the convex hull of Gaussian states (if one of the considered maps sends it into a non-positive operator, the above state is certified not to belong to the set). Generalizing a result known to be valid under the assumption of complete positivity, we provide a characterization of these Gaussian-to-Gaussian (not necessarily positive) superoperators in terms of their action on the characteristic function of the inputs. For the special case of one-mode mappings, we also show that any Gaussian-to-Gaussian superoperator can be expressed as a concatenation of a phase-space dilatation, followed by the action of a completely positive Gaussian channel, possibly composed with a transposition. While a similar decomposition is shown to fail in the multi-mode scenario, we prove that it still holds at least under the further hypothesis of homogeneous action on the covariance matrix.
Normal form decomposition for Gaussian-to-Gaussian superoperators
NASA Astrophysics Data System (ADS)
De Palma, Giacomo; Mari, Andrea; Giovannetti, Vittorio; Holevo, Alexander S.
2015-05-01
In this paper, we explore the set of linear maps sending the set of quantum Gaussian states into itself. These maps are in general not positive, a feature which can be exploited as a test to check whether a given quantum state belongs to the convex hull of Gaussian states (if one of the considered maps sends it into a non-positive operator, the above state is certified not to belong to the set). Generalizing a result known to be valid under the assumption of complete positivity, we provide a characterization of these Gaussian-to-Gaussian (not necessarily positive) superoperators in terms of their action on the characteristic function of the inputs. For the special case of one-mode mappings, we also show that any Gaussian-to-Gaussian superoperator can be expressed as a concatenation of a phase-space dilatation, followed by the action of a completely positive Gaussian channel, possibly composed with a transposition. While a similar decomposition is shown to fail in the multi-mode scenario, we prove that it still holds at least under the further hypothesis of homogeneous action on the covariance matrix.
Noise filtering algorithm for the MFTF-B computer based control system
Minor, E.G.
1983-11-30
An algorithm to reduce the message traffic in the MFTF-B computer based control system is described. The algorithm filters analog inputs to the control system. Its purpose is to distinguish between changes in the inputs due to noise and changes due to significant variations in the quantity being monitored. Noise is rejected while significant changes are reported to the control system data base, thus keeping the data base updated with a minimum number of messages. The algorithm is memory efficient, requiring only four bytes of storage per analog channel, and computationally simple, requiring only subtraction and comparison. Quantitative analysis of the algorithm is presented for the case of additive Gaussian noise. It is shown that the algorithm is stable and tends toward the mean value of the monitored variable over a wide variety of additive noise distributions.
Multi-Compartment T2 Relaxometry Using a Spatially Constrained Multi-Gaussian Model
Raj, Ashish; Pandya, Sneha; Shen, Xiaobo; LoCastro, Eve; Nguyen, Thanh D.; Gauthier, Susan A.
2014-01-01
The brain’s myelin content can be mapped by T2-relaxometry, which resolves multiple differentially relaxing T2 pools from multi-echo MRI. Unfortunately, the conventional fitting procedure is a hard and numerically ill-posed problem. Consequently, the T2 distributions and myelin maps become very sensitive to noise and are frequently difficult to interpret diagnostically. Although regularization can improve stability, it is generally not adequate, particularly at relatively low signal to noise ratio (SNR) of around 100–200. The purpose of this study was to obtain a fitting algorithm which is able to overcome these difficulties and generate usable myelin maps from noisy acquisitions in a realistic scan time. To this end, we restrict the T2 distribution to only 3 distinct resolvable tissue compartments, modeled as Gaussians: myelin water, intra/extra-cellular water and a slow relaxing cerebrospinal fluid compartment. We also impose spatial smoothness expectation that volume fractions and T2 relaxation times of tissue compartments change smoothly within coherent brain regions. The method greatly improves robustness to noise, reduces spatial variations, improves definition of white matter fibers, and enhances detection of demyelinating lesions. Due to efficient design, the additional spatial aspect does not cause an increase in processing time. The proposed method was applied to fast spiral acquisitions on which conventional fitting gives uninterpretable results. While these fast acquisitions suffer from noise and inhomogeneity artifacts, our preliminary results indicate the potential of spatially constrained 3-pool T2 relaxometry. PMID:24896833
Pérez Suárez, Santiago T.; Travieso González, Carlos M.; Alonso Hernández, Jesús B.
2013-01-01
This article presents a design methodology for designing an artificial neural network as an equalizer for a binary signal. Firstly, the system is modelled in floating point format using Matlab. Afterward, the design is described for a Field Programmable Gate Array (FPGA) using fixed point format. The FPGA design is based on the System Generator from Xilinx, which is a design tool over Simulink of Matlab. System Generator allows one to design in a fast and flexible way. It uses low level details of the circuits and the functionality of the system can be fully tested. System Generator can be used to check the architecture and to analyse the effect of the number of bits on the system performance. Finally the System Generator design is compiled for the Xilinx Integrated System Environment (ISE) and the system is described using a hardware description language. In ISE the circuits are managed with high level details and physical performances are obtained. In the Conclusions section, some modifications are proposed to improve the methodology and to ensure portability across FPGA manufacturers.
Gaussian and non-Gaussian fluctuations in pure classical fluids
NASA Astrophysics Data System (ADS)
Naleem, Nawavi; Ploetz, Elizabeth A.; Smith, Paul E.
2017-03-01
The particle number, energy, and volume probability distributions in the canonical, isothermal-isobaric, grand canonical, and isobaric-isenthalpic ensembles are investigated. In particular, we consider Gaussian and non-Gaussian behavior and formulate the results in terms of a single expression valid for all the ensembles employing common, experimentally accessible, thermodynamic derivatives. This is achieved using Fluctuation Solution Theory to help manipulate derivatives of the entropy. The properties of the distributions are then investigated using available equations of state for fluid water and argon. Purely Gaussian behavior is not observed for any of the state points considered here. A set of simple measures, involving thermodynamic derivatives, indicating non-Gaussian behavior is proposed. A general expression, valid in the high temperature limit, for small energy fluctuations in the canonical ensemble is provided.
Investigating binocular summation in human vision using complementary fused external noise
NASA Astrophysics Data System (ADS)
Howell, Christopher L.; Olson, Jeffrey T.
2016-05-01
The impact noise has on the processing of visual information at various stages within the human visual system (HVS) is still an open research area. To gain additional insight, twelve experiments were administered to human observers using sine wave targets to determine their contrast thresholds. A single frame of additive white Gaussian noise (AWGN) and its complement were used to investigate the effect of noise on the summation of visual information within the HVS. A standard contrast threshold experiment served as the baseline for comparisons. In the standard experiment, a range of sine wave targets are shown to the observers and their ability to detect the targets at varying contrast levels were recorded. The remaining experiments added some form of noise (noise image or its complement) and/or an additional sine wave target separated between one to three octaves to the test target. All of these experiments were tested using either a single monitor for viewing the targets or with a dual monitor presentation method for comparison. In the dual monitor experiments, a ninety degree mirror was used to direct each target to a different eye, allowing for the information to be fused binocularly. The experiments in this study present different approaches for delivering external noise to the HVS, and should allow for an improved understanding regarding how noise enters the HVS and what impact noise has on the processing of visual information.
Some results on Gaussian mixtures
NASA Astrophysics Data System (ADS)
Felgueiras, Miguel; Santos, Rui; Martins, João Paulo
2014-10-01
We investigate Gaussian mixtures with independent components, whose parameters are numerically estimated. A decomposition of a Gaussian mixture is presented when the components have a common variance. We introduce a shifted and scaled t-Student distribution as an approximation for the distribution of Gaussian mixtures when their components have a common mean and develop a hypothesis test for testing the equality of the components means. Finally, we analyse the fitness of the approximate model to the logarithmic daily returns of the Portuguese stock index PSI-20.
Research on Bayes matting algorithm based on Gaussian mixture model
NASA Astrophysics Data System (ADS)
Quan, Wei; Jiang, Shan; Han, Cheng; Zhang, Chao; Jiang, Zhengang
2015-12-01
The digital matting problem is a classical problem of imaging. It aims at separating non-rectangular foreground objects from a background image, and compositing with a new background image. Accurate matting determines the quality of the compositing image. A Bayesian matting Algorithm Based on Gaussian Mixture Model is proposed to solve this matting problem. Firstly, the traditional Bayesian framework is improved by introducing Gaussian mixture model. Then, a weighting factor is added in order to suppress the noises of the compositing images. Finally, the effect is further improved by regulating the user's input. This algorithm is applied to matting jobs of classical images. The results are compared to the traditional Bayesian method. It is shown that our algorithm has better performance in detail such as hair. Our algorithm eliminates the noise well. And it is very effectively in dealing with the kind of work, such as interested objects with intricate boundaries.
Remarkably Gaussian Tephra Fallout from Basaltic Eruptions
NASA Astrophysics Data System (ADS)
Courtland, L. M.; Kruse, S.; Connor, C.
2008-12-01
Tephra fallout models used to forecast volcanic hazards rely on the advection-diffusion equation to forecast hazards. If the advection-diffusion equation applies, then the thickness of tephra blanket deposits should show Gaussian crosswind profiles and exponential decay with distance from the vent. Complications may arise due to factors such as particle size distributions, particle density, and atmospheric effects not incorporated in the advection-diffusion model. Continuous profiles derived from GPR surveys collected on the tephra blanket of Cerro Negro Volcano, Nicaragua allow us to test the advection-diffusion model. Steady trade winds coupled with eruptions that tend to be brief and relatively low energy create relatively simple deposits. Data was collected for cross wind profiles at varying distances from the vent. Horizons identified in these profiles exhibit Gaussian distributions with a high degree of statistical confidence. Additionally, the shape of one continuous profile leading from the crater rim out onto the tephra blanket is examined.
Arbitrage with fractional Gaussian processes
NASA Astrophysics Data System (ADS)
Zhang, Xili; Xiao, Weilin
2017-04-01
While the arbitrage opportunity in the Black-Scholes model driven by fractional Brownian motion has a long history, the arbitrage strategy in the Black-Scholes model driven by general fractional Gaussian processes is in its infancy. The development of stochastic calculus with respect to fractional Gaussian processes allowed us to study such models. In this paper, following the idea of Shiryaev (1998), an arbitrage strategy is constructed for the Black-Scholes model driven by fractional Gaussian processes, when the stochastic integral is interpreted in the Riemann-Stieltjes sense. Arbitrage opportunities in some fractional Gaussian processes, including fractional Brownian motion, sub-fractional Brownian motion, bi-fractional Brownian motion, weighted-fractional Brownian motion and tempered fractional Brownian motion, are also investigated.
The Multilinear Compound Gaussian Distribution
2012-05-01
which we call the Multilinear Compound Gaussian (MCG) distribution, subsumes both GSM [1] and the previously developed MICA [3-4] distributions as...modeling various natural phenomena of interest. Index Terms— GSM, MICA , MCG, Bayesian, Nonlinear I. INTRODUCTION The compound Gaussian (CG) model—also...We will see how the MCG model developed subsumes both CG and the previously developed multilinear ICA ( MICA ) distribution [3-4] as complementary
Pseudospectral Gaussian quantum dynamics: Efficient sampling of potential energy surfaces.
Heaps, Charles W; Mazziotti, David A
2016-04-28
Trajectory-based Gaussian basis sets have been tremendously successful in describing high-dimensional quantum molecular dynamics. In this paper, we introduce a pseudospectral Gaussian-based method that achieves accurate quantum dynamics using efficient, real-space sampling of the time-dependent basis set. As in other Gaussian basis methods, we begin with a basis set expansion using time-dependent Gaussian basis functions guided by classical mechanics. Unlike other Gaussian methods but characteristic of the pseudospectral and collocation methods, the basis set is tested with N Dirac delta functions, where N is the number of basis functions, rather than using the basis function as test functions. As a result, the integration for matrix elements is reduced to function evaluation. Pseudospectral Gaussian dynamics only requires O(N) potential energy calculations, in contrast to O(N(2)) evaluations in a variational calculation. The classical trajectories allow small basis sets to sample high-dimensional potentials. Applications are made to diatomic oscillations in a Morse potential and a generalized version of the Henon-Heiles potential in two, four, and six dimensions. Comparisons are drawn to full analytical evaluation of potential energy integrals (variational) and the bra-ket averaged Taylor (BAT) expansion, an O(N) approximation used in Gaussian-based dynamics. In all cases, the pseudospectral Gaussian method is competitive with full variational calculations that require a global, analytical, and integrable potential energy surface. Additionally, the BAT breaks down when quantum mechanical coherence is particularly strong (i.e., barrier reflection in the Morse oscillator). The ability to obtain variational accuracy using only the potential energy at discrete points makes the pseudospectral Gaussian method a promising avenue for on-the-fly dynamics, where electronic structure calculations become computationally significant.
The design and research of anti-color-noise chaos M-ary communication system
NASA Astrophysics Data System (ADS)
Fu, Yongqing; Li, Xingyuan; Li, Yanan; Zhang, Lin
2016-03-01
Previously a novel chaos M-ary digital communication method based on spatiotemporal chaos Hamilton oscillator has been proposed. Without chaos synchronization circumstance, it has performance improvement in bandwidth efficiency, transmission efficiency and anti-white-noise performance compared with traditional communication method. In this paper, the channel noise influence on chaotic modulation signals and the construction problem of anti-color-noise chaotic M-ary communication system are studied. The formula of zone partition demodulator's boundary in additive white Gaussian noise is derived, besides, the problem about how to determine the boundary of zone partition demodulator in additive color noise is deeply studied; Then an approach on constructing anti-color-noise chaos M-ary communication system is proposed, in which a pre-distortion filter is added after the chaos baseband modulator in the transmitter and whitening filter is added before zone partition demodulator in the receiver. Finally, the chaos M-ary communication system based on Hamilton oscillator is constructed and simulated in different channel noise. The result shows that the proposed method in this paper can improve the anti-color-noise performance of the whole communication system compared with the former system, and it has better anti-fading and resisting disturbance performance than Quadrature Phase Shift Keying system.
Noise generator for tinnitus treatment based on look-up tables
NASA Astrophysics Data System (ADS)
Uriz, Alejandro J.; Agüero, Pablo; Tulli, Juan C.; Castiñeira Moreira, Jorge; González, Esteban; Hidalgo, Roberto; Casadei, Manuel
2016-04-01
Treatment of tinnitus by means of masking sounds allows to obtain a significant improve of the quality of life of the individual that suffer that condition. In view of that, it is possible to develop noise synthesizers based on random number generators in digital signal processors (DSP), which are used in almost any digital hearing aid devices. DSP architecture have limitations to implement a pseudo random number generator, due to it, the noise statistics can be not as good as expectations. In this paper, a technique to generate additive white gaussian noise (AWGN) or other types of filtered noise using coefficients stored in program memory of the DSP is proposed. Also, an implementation of the technique is carried out on a dsPIC from Microchip®. Objective experiments and experimental measurements are performed to analyze the proposed technique.
Least-squares Gaussian beam migration
NASA Astrophysics Data System (ADS)
Yuan, Maolin; Huang, Jianping; Liao, Wenyuan; Jiang, Fuyou
2017-02-01
A theory of least-squares Gaussian beam migration (LSGBM) is presented to optimally estimate a subsurface reflectivity. In the iterative inversion scheme, a Gaussian beam (GB) propagator is used as the kernel of linearized forward modeling (demigration) and its adjoint (migration). Born approximation based GB demigration relies on the calculation of Green’s function by a Gaussian-beam summation for the downward and upward wavefields. The adjoint operator of GB demigration accounts for GB prestack depth migration under the cross-correlation imaging condition, where seismic traces are processed one by one for each shot. A numerical test on the point diffractors model suggests that GB demigration can successfully simulate primary scattered data, while migration (adjoint) can yield a corresponding image. The GB demigration/migration algorithms are used for the least-squares migration scheme to deblur conventional migrated images. The proposed LSGBM is illustrated with two synthetic data for a four-layer model and the Marmousi2 model. Numerical results show that LSGBM, compared to migration (adjoint) with GBs, produces images with more balanced amplitude, higher resolution and even fewer artifacts. Additionally, the LSGBM shows a robust convergence rate.
Quantum correlations in Gaussian states via Gaussian channels: steering, entanglement, and discord
NASA Astrophysics Data System (ADS)
Wang, Zhong-Xiao; Wang, Shuhao; Li, Qiting; Wang, Tie-Jun; Wang, Chuan
2016-06-01
Here we study the quantum steering, quantum entanglement, and quantum discord for Gaussian Einstein-Podolsky-Rosen states via Gaussian channels. And the sudden death phenomena for Gaussian steering and Gaussian entanglement are theoretically observed. We find that some Gaussian states have only one-way steering, which confirms the asymmetry of quantum steering. Also we investigate that the entangled Gaussian states without Gaussian steering and correlated Gaussian states own no Gaussian entanglement. Meanwhile, our results support the assumption that quantum entanglement is intermediate between quantum discord and quantum steering. Furthermore, we give experimental recipes for preparing quantum states with desired types of quantum correlations.
Non-Gaussian corrections to the Gordon-Haus distribution resulting from soliton interactions
NASA Astrophysics Data System (ADS)
Menyuk, C. R.
1995-02-01
In a soliton transmission system, spontaneous emission noise owing to optical amplifiers leads to timing jitter that is usually assumed to be Gaussian distributed. It is shown that the mutual interaction of solitons in neighboring time slots can lead to non-Gaussian tails on the distribution function and to a substantial increase in the bit-error rate. It is argued that the approach used here will also be of use in the study of non-return-to-zero systems.
Entanglement analysis of two-mode Gaussian states in a parametric down-converter
NASA Astrophysics Data System (ADS)
Tahira, Rabia; Ge, Guoqin; Ikram, Manzoor
2017-04-01
Parametric down-conversion has been studied as a source of entangled radiation (Lee et al 2008 J. Phys. B: At. Mol. Opt. Phys. 41 145504). We investigate and quantify the entanglement of this system when the initial cavity modes are taken as two-mode Gaussian states. We study the effect of nonclassicality, purity, noise and leakage through the cavity modes on the two-mode Gaussian state entanglement.
NASA Technical Reports Server (NTRS)
Huston, R. J. (Compiler)
1982-01-01
The establishment of a realistic plan for NASA and the U.S. helicopter industry to develop a design-for-noise methodology, including plans for the identification and development of promising noise reduction technology was discussed. Topics included: noise reduction techniques, scaling laws, empirical noise prediction, psychoacoustics, and methods of developing and validing noise prediction methods.
Oliver, Jasmine A; Budzevich, Mikalai; Hunt, Dylan; Moros, Eduardo G; Latifi, Kujtim; Dilling, Thomas J; Feygelman, Vladimir; Zhang, Geoffrey
2016-08-08
The effect of noise on image features has yet to be studied in depth. Our objective was to explore how significantly image features are affected by the addition of uncorrelated noise to an image. The signal-to-noise ratio and noise power spectrum were calculated for a positron emission tomography/computed tomography scanner using a Ge-68 phantom. The conventional and respiratory-gated positron emission tomography/computed tomography images of 31 patients with lung cancer were retrospectively examined. Multiple sets of noise images were created for each original image by adding Gaussian noise of varying standard deviation equal to 2.5%, 4.0%, and 6.0% of the maximum intensity for positron emission tomography images and 10, 20, 50, 80, and 120 Hounsfield units for computed tomography images. Image features were extracted from all images, and percentage differences between the original image and the noise image feature values were calculated. These features were then categorized according to the noise sensitivity. The contour-dependent shape descriptors averaged below 4% difference in positron emission tomography and below 13% difference in computed tomography between noise and original images. Gray level size zone matrix features were the most sensitive to uncorrelated noise exhibiting average differences >200% for conventional and respiratory-gated images in computed tomography and 90% in positron emission tomography. Image feature differences increased as the noise level increased for shape, intensity, and gray-level co-occurrence matrix features in positron emission tomography and for gray-level co-occurrence matrix and gray-level size zone matrix features in conventional computed tomography. Investigators should be aware of the noise effects on image features.
Information geometry of Gaussian channels
Monras, Alex; Illuminati, Fabrizio
2010-06-15
We define a local Riemannian metric tensor in the manifold of Gaussian channels and the distance that it induces. We adopt an information-geometric approach and define a metric derived from the Bures-Fisher metric for quantum states. The resulting metric inherits several desirable properties from the Bures-Fisher metric and is operationally motivated by distinguishability considerations: It serves as an upper bound to the attainable quantum Fisher information for the channel parameters using Gaussian states, under generic constraints on the physically available resources. Our approach naturally includes the use of entangled Gaussian probe states. We prove that the metric enjoys some desirable properties like stability and covariance. As a by-product, we also obtain some general results in Gaussian channel estimation that are the continuous-variable analogs of previously known results in finite dimensions. We prove that optimal probe states are always pure and bounded in the number of ancillary modes, even in the presence of constraints on the reduced state input in the channel. This has experimental and computational implications. It limits the complexity of optimal experimental setups for channel estimation and reduces the computational requirements for the evaluation of the metric: Indeed, we construct a converging algorithm for its computation. We provide explicit formulas for computing the multiparametric quantum Fisher information for dissipative channels probed with arbitrary Gaussian states and provide the optimal observables for the estimation of the channel parameters (e.g., bath couplings, squeezing, and temperature).
Capacity and optimal collusion attack channels for Gaussian fingerprinting games
NASA Astrophysics Data System (ADS)
Wang, Ying; Moulin, Pierre
2007-02-01
constraints. Under those constraints on the fingerprint embedder and the colluders, fingerprinting capacity is obtained as the solution of a mutual-information game involving probability density functions (pdf's) designed by the embedder and the colluders. We show that the optimal fingerprinting strategy is a Gaussian test channel where the fingerprinted signal is the sum of an attenuated version of the cover signal plus a Gaussian information-bearing noise, and the optimal collusion strategy is to average fingerprinted signals possessed by all the colluders and pass the averaged copy through a Gaussian test channel. The capacity result and the optimal strategies are the same for both the private and public games. In the former scenario, the original covertext is available to the decoder, while in the latter setup, the original covertext is available to the encoder but not to the decoder.
Quantization of Gaussian samples at very low SNR regime in continuous variable QKD applications
NASA Astrophysics Data System (ADS)
Daneshgaran, Fred; Mondin, Marina
2016-09-01
The main problem for information reconciliation in continuous variable Quantum Key Distribution (QKD) at low Signal to Noise Ratio (SNR) is quantization and assignment of labels to the samples of the Gaussian Random Variables (RVs) observed at Alice and Bob. Trouble is that most of the samples, assuming that the Gaussian variable is zero mean which is de-facto the case, tend to have small magnitudes and are easily disturbed by noise. Transmission over longer and longer distances increases the losses corresponding to a lower effective SNR exasperating the problem. This paper looks at the quantization problem of the Gaussian samples at very low SNR regime from an information theoretic point of view. We look at the problem of two bit per sample quantization of the Gaussian RVs at Alice and Bob and derive expressions for the mutual information between the bit strings as a result of this quantization. The quantization threshold for the Most Significant Bit (MSB) should be chosen based on the maximization of the mutual information between the quantized bit strings. Furthermore, while the LSB string at Alice and Bob are balanced in a sense that their entropy is close to maximum, this is not the case for the second most significant bit even under optimal threshold. We show that with two bit quantization at SNR of -3 dB we achieve 75.8% of maximal achievable mutual information between Alice and Bob, hence, as the number of quantization bits increases beyond 2-bits, the number of additional useful bits that can be extracted for secret key generation decreases rapidly. Furthermore, the error rates between the bit strings at Alice and Bob at the same significant bit level are rather high demanding very powerful error correcting codes. While our calculations and simulation shows that the mutual information between the LSB at Alice and Bob is 0.1044 bits, that at the MSB level is only 0.035 bits. Hence, it is only by looking at the bits jointly that we are able to achieve a
A White Noise Theory of Infinite Dimensional Calculus
1989-10-01
a general theory; however it is his hope that this attempt would be the very first step towards the study of Gaussian random fields using variational ... calculus . Contents: White noise; Generalized functionals; Rotation group and harmonic analysis; Applications to Physics; Gaussian random fields. Keywords: Statistic processes.
Core Noise - Increasing Importance
NASA Technical Reports Server (NTRS)
Hultgren, Lennart S.
2011-01-01
This presentation is a technical summary of and outlook for NASA-internal and NASA-sponsored external research on core (combustor and turbine) noise funded by the Fundamental Aeronautics Program Subsonic Fixed Wing (SFW) Project. Sections of the presentation cover: the SFW system-level noise metrics for the 2015, 2020, and 2025 timeframes; turbofan design trends and their aeroacoustic implications; the emerging importance of core noise and its relevance to the SFW Reduced-Perceived-Noise Technical Challenge; and the current research activities in the core-noise area, with additional details given about the development of a high-fidelity combustor-noise prediction capability as well as activities supporting the development of improved reduced-order, physics-based models for combustor-noise prediction. The need for benchmark data for validation of high-fidelity and modeling work and the value of a potential future diagnostic facility for testing of core-noise-reduction concepts are indicated. The NASA Fundamental Aeronautics Program has the principal objective of overcoming today's national challenges in air transportation. The SFW Reduced-Perceived-Noise Technical Challenge aims to develop concepts and technologies to dramatically reduce the perceived aircraft noise outside of airport boundaries. This reduction of aircraft noise is critical to enabling the anticipated large increase in future air traffic. Noise generated in the jet engine core, by sources such as the compressor, combustor, and turbine, can be a significant contribution to the overall noise signature at low-power conditions, typical of approach flight. At high engine power during takeoff, jet and fan noise have traditionally dominated over core noise. However, current design trends and expected technological advances in engine-cycle design as well as noise-reduction methods are likely to reduce non-core noise even at engine-power points higher than approach. In addition, future low-emission combustor
Long, Chengjiang; Hua, Gang; Kapoor, Ashish
2015-01-01
We present a noise resilient probabilistic model for active learning of a Gaussian process classifier from crowds, i.e., a set of noisy labelers. It explicitly models both the overall label noise and the expertise level of each individual labeler with two levels of flip models. Expectation propagation is adopted for efficient approximate Bayesian inference of our probabilistic model for classification, based on which, a generalized EM algorithm is derived to estimate both the global label noise and the expertise of each individual labeler. The probabilistic nature of our model immediately allows the adoption of the prediction entropy for active selection of data samples to be labeled, and active selection of high quality labelers based on their estimated expertise to label the data. We apply the proposed model for four visual recognition tasks, i.e., object category recognition, multi-modal activity recognition, gender recognition, and fine-grained classification, on four datasets with real crowd-sourced labels from the Amazon Mechanical Turk. The experiments clearly demonstrate the efficacy of the proposed model. In addition, we extend the proposed model with the Predictive Active Set Selection Method to speed up the active learning system, whose efficacy is verified by conducting experiments on the first three datasets. The results show our extended model can not only preserve a higher accuracy, but also achieve a higher efficiency. PMID:26924892
Suppressing escape events in maps of the unit interval with demographic noise.
Parra-Rojas, César; Challenger, Joseph D; Fanelli, Duccio; McKane, Alan J
2016-11-01
We explore the properties of discrete-time stochastic processes with a bounded state space, whose deterministic limit is given by a map of the unit interval. We find that, in the mesoscopic description of the system, the large jumps between successive iterates of the process can result in probability leaking out of the unit interval, despite the fact that the noise is multiplicative and vanishes at the boundaries. By including higher-order terms in the mesoscopic expansion, we are able to capture the non-Gaussian nature of the noise distribution near the boundaries, but this does not preclude the possibility of a trajectory leaving the interval. We propose a number of prescriptions for treating these escape events, and we compare the results with those obtained for the metastable behavior of the microscopic model, where escape events are not possible. We find that, rather than truncating the noise distribution, censoring this distribution to prevent escape events leads to results which are more consistent with the microscopic model. The addition of higher moments to the noise distribution does not increase the accuracy of the final results, and it can be replaced by the simpler Gaussian noise.
Suppressing escape events in maps of the unit interval with demographic noise
NASA Astrophysics Data System (ADS)
Parra-Rojas, César; Challenger, Joseph D.; Fanelli, Duccio; McKane, Alan J.
2016-11-01
We explore the properties of discrete-time stochastic processes with a bounded state space, whose deterministic limit is given by a map of the unit interval. We find that, in the mesoscopic description of the system, the large jumps between successive iterates of the process can result in probability leaking out of the unit interval, despite the fact that the noise is multiplicative and vanishes at the boundaries. By including higher-order terms in the mesoscopic expansion, we are able to capture the non-Gaussian nature of the noise distribution near the boundaries, but this does not preclude the possibility of a trajectory leaving the interval. We propose a number of prescriptions for treating these escape events, and we compare the results with those obtained for the metastable behavior of the microscopic model, where escape events are not possible. We find that, rather than truncating the noise distribution, censoring this distribution to prevent escape events leads to results which are more consistent with the microscopic model. The addition of higher moments to the noise distribution does not increase the accuracy of the final results, and it can be replaced by the simpler Gaussian noise.
Truncated Gaussian and derived methods
NASA Astrophysics Data System (ADS)
Beucher, Hélène; Renard, Didier
2016-09-01
The interest of a digital model to represent the geological characteristics of the field is well established. However, the way to obtain it is not straightforward because this translation is necessarily a simplification of the actual field. This paper describes a stochastic model called truncated Gaussian simulations (TGS), which distributes a collection of facies or lithotypes over an area of interest. This method is based on facies proportions, spatial distribution and relationships, which can be easily tuned to produce numerous different textures. Initially developed for ordered facies, this model has been extended to complex organizations, where facies are not sequentially ordered. This method called pluri-Gaussian simulation (PGS) considers several Gaussian random functions, which can be correlated. PGS can produce a large variety of lithotype setups, as illustrated by several examples such as oriented deposits or high frequency layering.
Gaussian entanglement distribution via satellite
NASA Astrophysics Data System (ADS)
Hosseinidehaj, Nedasadat; Malaney, Robert
2015-02-01
In this work we analyze three quantum communication schemes for the generation of Gaussian entanglement between two ground stations. Communication occurs via a satellite over two independent atmospheric fading channels dominated by turbulence-induced beam wander. In our first scheme, the engineering complexity remains largely on the ground transceivers, with the satellite acting simply as a reflector. Although the channel state information of the two atmospheric channels remains unknown in this scheme, the Gaussian entanglement generation between the ground stations can still be determined. On the ground, distillation and Gaussification procedures can be applied, leading to a refined Gaussian entanglement generation rate between the ground stations. We compare the rates produced by this first scheme with two competing schemes in which quantum complexity is added to the satellite, thereby illustrating the tradeoff between space-based engineering complexity and the rate of ground-station entanglement generation.
Non-Gaussian and Multivariate Noise Models for Signal Detection.
1982-09-01
same level and power of the P two detectors as the number of samples goes to infinity. With the above regularity conditions and the Pitman- Noether ... theorem , the ARE is equal to the ratio of the efficacies J2*(z)ARE 2 = J2(X) !i- 98 - An analytic evaluation of the efficacy of these detectors is
Nearly Optimal Detection of Signals in Non-Gaussian Noise
1984-02-01
Princeton NJ, 1974. [19]S. L. Bernstein , et al, "Long-Range Communications at Extremely Low Frequencies," Proc. IEEE, vol. 62, no. 3, pp. 292-312...Laboratories Tech. Report ARL-TP-82-38, Augiist 1982. 5] S.L Bernstein , et al., "Long Range Communications at Extremely Low Frequencies", Proc...775s by simply setting CTQ = 1, and letting af = af/5o. In this case, ARE5fl,jd =2.55 is the estimated performance improvement. Using the switched
Streak image denoising and segmentation using adaptive Gaussian guided filter.
Jiang, Zhuocheng; Guo, Baoping
2014-09-10
In streak tube imaging lidar (STIL), streak images are obtained using a CCD camera. However, noise in the captured streak images can greatly affect the quality of reconstructed 3D contrast and range images. The greatest challenge for streak image denoising is reducing the noise while preserving details. In this paper, we propose an adaptive Gaussian guided filter (AGGF) for noise removal and detail enhancement of streak images. The proposed algorithm is based on a guided filter (GF) and part of an adaptive bilateral filter (ABF). In the AGGF, the details are enhanced by optimizing the offset parameter. AGGF-denoised streak images are significantly sharper than those denoised by the GF. Moreover, the AGGF is a fast linear time algorithm achieved by recursively implementing a Gaussian filter kernel. Experimentally, AGGF demonstrates its capacity to preserve edges and thin structures and outperforms the existing bilateral filter and domain transform filter in terms of both visual quality and peak signal-to-noise ratio performance.
Gaussian-mixture umbrella sampling
van der Vaart, Arjan; Karplus, Martin
2009-01-01
We introduce the Gaussian-mixture umbrella sampling method (GAMUS), a biased molecular dynamics technique based on adaptive umbrella sampling that efficiently escapes free energy minima in multi-dimensional problems. The prior simulation data are reweighted with a maximum likelihood formulation, and the new approximate probability density is fit to a Gaussian-mixture model, augmented by information about the unsampled areas. The method can be used to identify free energy minima in multi-dimensional reaction coordinates. To illustrate GAMUS, we apply it to the alanine dipeptide (2D reaction coordinate) and tripeptide (4D reaction coordinate). PMID:19284746
Non-gaussianity versus nonlinearity of cosmological perturbations.
Verde, L
2001-06-01
Following the discovery of the cosmic microwave background, the hot big-bang model has become the standard cosmological model. In this theory, small primordial fluctuations are subsequently amplified by gravity to form the large-scale structure seen today. Different theories for unified models of particle physics, lead to different predictions for the statistical properties of the primordial fluctuations, that can be divided in two classes: gaussian and non-gaussian. Convincing evidence against or for gaussian initial conditions would rule out many scenarios and point us toward a physical theory for the origin of structures. The statistical distribution of cosmological perturbations, as we observe them, can deviate from the gaussian distribution in several different ways. Even if perturbations start off gaussian, nonlinear gravitational evolution can introduce non-gaussian features. Additionally, our knowledge of the Universe comes principally from the study of luminous material such as galaxies, but galaxies might not be faithful tracers of the underlying mass distribution. The relationship between fluctuations in the mass and in the galaxies distribution (bias), is often assumed to be local, but could well be nonlinear. Moreover, galaxy catalogues use the redshift as third spatial coordinate: the resulting redshift-space map of the galaxy distribution is nonlinearly distorted by peculiar velocities. Nonlinear gravitational evolution, biasing, and redshift-space distortion introduce non-gaussianity, even in an initially gaussian fluctuation field. I investigate the statistical tools that allow us, in principle, to disentangle the above different effects, and the observational datasets we require to do so in practice.
Capacity of Pulse-Position Modulation (PPM) on Gaussian and Webb Channels
NASA Technical Reports Server (NTRS)
Dolinar, S.; Divsalar, D.; Hamkins, J.; Pollara, F.
2000-01-01
This article computes the capacity of various idealized soft-decision channels modeling an optical channel using an avalanche photodiode detector (APD) and pulse-position modulation (PPM). The capacity of this optical channel depends in a complicated way on the physical parameters of the APD and the constraints imposed by the PPM orthogonal signaling set. This article attempts to identify and separate the effects of several fundamental parameters on the capacity of the APD-detected optical PPM channel. First, an overall signal-to-noise ratio (SNR) parameter is de ned such that the capacity as a function of a bit-normalized version of this SNR drops precipitously toward zero at quasi-brick-wall limits on bit SNR that are numerically the same as the well-understood brick-wall limits for the standard additive white Gaussian noise (AWGN) channel. A second parameter is used to quantify the effects on capacity of one unique facet of the optical PPM channel (as compared with the standard AWGN channel) that causes the noise variance to be higher in signal slots than in nonsignal slots. This nonuniform noise variance yields interesting capacity effects even when the channel model is AWGN. A third parameter is used to measure the effects on capacity of the difference between an AWGN model and a non-Gaussian model proposed by Webb (see reference in [2]) for approximating the statistics of the APD-detected optical channel. Finally, a fourth parameter is used to quantify the blending of a Webb model with a pure AWGN model to account for thermal noise. Numerical results show that the capacity of M-ary orthogonal signaling on the Webb channel exhibits the same brick-wall Shannon limit, (M ln 2)=(M 1), as on the AWGN channel ( 1:59 dB for large M). Results also compare the capacity obtained by hard- and soft-output channels and indicate that soft-output channels o er a 3-dB advantage.
Verhulst model with Lévy white noise excitation
NASA Astrophysics Data System (ADS)
Dubkov, A. A.; Spagnolo, B.
2008-10-01
The transient dynamics of the Verhulst model perturbed by arbitrary non-Gaussian white noise is investigated. Based on the infinitely divisible distribution of the Lévy process we study the nonlinear relaxation of the population density for three cases of white non-Gaussian noise: (i) shot noise; (ii) noise with a probability density of increments expressed in terms of Gamma function; and (iii) Cauchy stable noise. We obtain exact results for the probability distribution of the population density in all cases, and for Cauchy stable noise the exact expression of the nonlinear relaxation time is derived. Moreover starting from an initial delta function distribution, we find a transition induced by the multiplicative Lévy noise, from a trimodal probability distribution to a bimodal probability distribution in asymptotics. Finally we find a nonmonotonic behavior of the nonlinear relaxation time as a function of the Cauchy stable noise intensity.
Constraining primordial non-Gaussianity with cosmological weak lensing: shear and flexion
Fedeli, C.; Bartelmann, M.; Moscardini, L. E-mail: bartelmann@uni-heidelberg.de
2012-10-01
We examine the cosmological constraining power of future large-scale weak lensing surveys on the model of the ESA planned mission Euclid, with particular reference to primordial non-Gaussianity. Our analysis considers several different estimators of the projected matter power spectrum, based on both shear and flexion. We review the covariance and Fisher matrix for cosmic shear and evaluate those for cosmic flexion and for the cross-correlation between the two. The bounds provided by cosmic shear alone are looser than previously estimated, mainly due to the reduced sky coverage and background number density of sources for the latest Euclid specifications. New constraints for the local bispectrum shape, marginalized over σ{sub 8}, are at the level of Δf{sub NL} ∼ 100, with the precise value depending on the exact multipole range that is considered in the analysis. We consider three additional bispectrum shapes, for which the cosmic shear constraints range from Δf{sub NL} ∼ 340 (equilateral shape) up to Δf{sub NL} ∼ 500 (orthogonal shape). Also, constraints on the level of non-Gaussianity and on the amplitude of the matter power spectrum σ{sub 8} are almost perfectly anti-correlated, except for the orthogonal bispectrum shape for which they are correlated. The competitiveness of cosmic flexion constraints against cosmic shear ones depends by and large on the galaxy intrinsic flexion noise, that is still virtually unconstrained. Adopting the very high value that has been occasionally used in the literature results in the flexion contribution being basically negligible with respect to the shear one, and for realistic configurations the former does not improve significantly the constraining power of the latter. Since the shear shot noise is white, while the flexion one decreases with decreasing scale, by considering high enough multipoles the two contributions have to become comparable. Extending the analysis up to l{sub max} = 20,000 cosmic flexion, while
Gaussian quantum steering and its asymmetry in curved spacetime
NASA Astrophysics Data System (ADS)
Wang, Jieci; Cao, Haixin; Jing, Jiliang; Fan, Heng
2016-06-01
We study Gaussian quantum steering and its asymmetry in the background of a Schwarzschild black hole. We present a Gaussian channel description of quantum state evolution under the influence of Hawking radiation. We find that thermal noise introduced by the Hawking effect will destroy the steerability between an inertial observer Alice and an accelerated observer Bob who hovers outside the event horizon, while it generates steerability between Bob and a hypothetical observer anti-Bob inside the event horizon. Unlike entanglement behaviors in curved spacetime, here the steering from Alice to Bob suffers from a "sudden death" and the steering from anti-Bob to Bob experiences a "sudden birth" with increasing Hawking temperature. We also find that the Gaussian steering is always asymmetric and the maximum steering asymmetry cannot exceed ln 2 , which means the state never evolves to an extremal asymmetry state. Furthermore, we obtain the parameter settings that maximize steering asymmetry and find that (i) s =arccosh cosh/2r 1 -sinh2r is the critical point of steering asymmetry and (ii) the attainment of maximal steering asymmetry indicates the transition between one-way steerability and both-way steerability for the two-mode Gaussian state under the influence of Hawking radiation.
Non-Gaussian microwave background fluctuations from nonlinear gravitational effects
NASA Technical Reports Server (NTRS)
Salopek, D. S.; Kunstatter, G. (Editor)
1991-01-01
Whether the statistics of primordial fluctuations for structure formation are Gaussian or otherwise may be determined if the Cosmic Background Explorer (COBE) Satellite makes a detection of the cosmic microwave-background temperature anisotropy delta T(sub CMB)/T(sub CMB). Non-Gaussian fluctuations may be generated in the chaotic inflationary model if two scalar fields interact nonlinearly with gravity. Theoretical contour maps are calculated for the resulting Sachs-Wolfe temperature fluctuations at large angular scales (greater than 3 degrees). In the long-wavelength approximation, one can confidently determine the nonlinear evolution of quantum noise with gravity during the inflationary epoch because: (1) different spatial points are no longer in causal contact; and (2) quantum gravity corrections are typically small-- it is sufficient to model the system using classical random fields. If the potential for two scalar fields V(phi sub 1, phi sub 2) possesses a sharp feature, then non-Gaussian fluctuations may arise. An explicit model is given where cold spots in delta T(sub CMB)/T(sub CMB) maps are suppressed as compared to the Gaussian case. The fluctuations are essentially scale-invariant.
2012 Problem 1: Gaussian Cannon
NASA Astrophysics Data System (ADS)
Xia, Qing; Gao, Wenli; Wang, Sihui; Zhou, Huijun
2015-10-01
Using the theory of elasticity, we establish an accurate collision model and quantitatively explain how Gaussian Cannon gains its most powerful shot under certain experimental parameters. The work done by magnetic force on the steel ball is obtained by measuring the magnetic force. Essential factors to acquire higher ejection speed have been found.
General immunity and superadditivity of two-way Gaussian quantum cryptography
Ottaviani, Carlo; Pirandola, Stefano
2016-01-01
We consider two-way continuous-variable quantum key distribution, studying its security against general eavesdropping strategies. Assuming the asymptotic limit of many signals exchanged, we prove that two-way Gaussian protocols are immune to coherent attacks. More precisely we show the general superadditivity of the two-way security thresholds, which are proven to be higher than the corresponding one-way counterparts in all cases. We perform the security analysis first reducing the general eavesdropping to a two-mode coherent Gaussian attack, and then showing that the superadditivity is achieved by exploiting the random on/off switching of the two-way quantum communication. This allows the parties to choose the appropriate communication instances to prepare the key, accordingly to the tomography of the quantum channel. The random opening and closing of the circuit represents, in fact, an additional degree of freedom allowing the parties to convert, a posteriori, the two-mode correlations of the eavesdropping into noise. The eavesdropper is assumed to have no access to the on/off switching and, indeed, cannot adapt her attack. We explicitly prove that this mechanism enhances the security performance, no matter if the eavesdropper performs collective or coherent attacks. PMID:26928053
Gaussian Velocity Distributions in Avalanches
NASA Astrophysics Data System (ADS)
Shattuck, Mark
2004-03-01
Imagine a world where gravity is so strong that if an ice cube is tilted the shear forces melt the surface and water avalanches down. Further imagine that the ambient temperature is so low that the water re-freezes almost immediately. This is the world of granular flows. As a granular solid is tilted the surface undergoes a sublimation phase transition and a granular gas avalanches down the surface, but the inelastic collisions rapidly remove energy from the flow lowering the granular temperature (kinetic energy per particle) until the gas solidifies again. It is under these extreme conditions that we attempt to uncover continuum granular flow properties. Typical continuum theories like Navier-Stokes equation for fluids follow the space-time evolution of the first few moments of the velocity distribution. We study continuously avalanching flow in a rotating two-dimensional granular drum using high-speed video imaging and extract the position and velocities of the particles. We find a universal near Gaussian velocity distribution throughout the flowing regions, which are characterized by a liquid-like radial distribution function. In the remaining regions, in which the radial distribution function develops sharp crystalline peaks, the velocity distribution has a Gaussian peak but is much broader in the tails. In a companion experiment on a vibrated two-dimensional granular fluid under constant pressure, we find a clear gas-solid phase transition in which both the temperature and density change discontinuously. This suggests that a low temperature crystal and a high temperature gas can coexist in steady state. This coexistence could result in a narrower, cooler, Gaussian peak and a broader, warmer, Gaussian tail like the non-Gaussian behavior seen in the crystalline portions of the rotating drum.
Liu, Yushun; Zhou, Wenjun; Li, Pengfei; Yang, Shuai; Tian, Yan
2016-01-01
Due to electromagnetic interference in power substations, the partial discharge (PD) signals detected by ultrahigh frequency (UHF) antenna sensors often contain various background noises, which may hamper high voltage apparatus fault diagnosis and localization. This paper proposes a novel de-noising method based on the generalized S-transform and module time-frequency matrix to suppress noise in UHF PD signals. The sub-matrix maximum module value method is employed to calculate the frequencies and amplitudes of periodic narrowband noise, and suppress noise through the reverse phase cancellation technique. In addition, a singular value decomposition de-noising method is employed to suppress Gaussian white noise in UHF PD signals. Effective singular values are selected by employing the fuzzy c-means clustering method to recover the PD signals. De-noising results of simulated and field detected UHF PD signals prove the feasibility of the proposed method. Compared with four conventional de-noising methods, the results show that the proposed method can suppress background noise in the UHF PD signal effectively, with higher signal-to-noise ratio and less waveform distortion. PMID:27338409
NASA Technical Reports Server (NTRS)
Pendley, R. E.
1982-01-01
The problem of airport noise at several airports and air bases is detailed. Community reactions to the noise, steps taken to reduce jet engine noise, and the effect of airport use restrictions and curfews on air transportation are discussed. The adverse effect of changes in allowable operational noise on airport safety and altenative means for reducing noise pollution are considered. Community-airport relations and public relations are discussed.
NASA Technical Reports Server (NTRS)
Strahle, W. C.
1977-01-01
A review of the subject of combustion generated noise is presented. Combustion noise is an important noise source in industrial furnaces and process heaters, turbopropulsion and gas turbine systems, flaring operations, Diesel engines, and rocket engines. The state-of-the-art in combustion noise importance, understanding, prediction and scaling is presented for these systems. The fundamentals and available theories of combustion noise are given. Controversies in the field are discussed and recommendations for future research are made.
Inseparability of photon-added Gaussian states
Li Hongrong; Li Fuli; Zhu Shiyao
2007-06-15
The inseparability of photon-added Gaussian states which are generated from two-mode Gaussian states by adding photons is investigated. According to the established inseparability conditions [New J. Phys. 7, 211 (2005); Phys. Rev. Lett. 96, 050503 (2006)], we find that even if a two-mode Gaussian state is separable, the photon-added Gaussian state becomes entangled when the purity of the Gaussian state is larger than a certain value. The lower bound of entanglement of symmetric photon-added Gaussian states is derived. The result shows that entanglement of the photon-added Gaussian states is involved with high-order moment correlations. We find that fidelity of teleporting coherent states cannot be raised by employing the photon-added Gaussian states as a quantum channel of teleportation.
Michelson Interferometer characterisation of noise reduction in DFB fibre lasers
NASA Astrophysics Data System (ADS)
Canagasabey, Albert; Jones, David; Mann, David; Canning, John; Fleming, Simon; Holdsworth, John
2012-02-01
A comparison is made between unpackaged and packaged distributed feedback (DFB) fibre lasers using the Michelson interferometer configuration for delayed self-heterodyne interferometery (MIDSHI) to ascertain the improvements to the external environmental noise, quantified by reductions in the Gaussian linewidth. Voigt fitting is used to extract and separate out the Lorentzian and Gaussian linewidth contributions and therefore the associated sources of noise. Significant improvements in the Gaussian linewidth were achieved as a result of significant reductions in the sensitivity of the DFB laser to external perturbations using packaging. However, a broadening of the laser Lorentzian linewidth was observed.
Estimation of nonclassical independent Gaussian processes by classical interferometry
Ruppert, László; Filip, Radim
2017-01-01
We propose classical interferometry with low-intensity thermal radiation for the estimation of nonclassical independent Gaussian processes in material samples. We generally determine the mean square error of the phase-independent parameters of an unknown Gaussian process, considering a noisy source of radiation the phase of which is not locked to the pump of the process. We verify the sufficiency of passive optical elements in the interferometer, active optical elements do not improve the quality of the estimation. We also prove the robustness of the method against the noise and loss in both interferometric channels and the sample. The proposed method is suitable even for the case when a source of radiation sufficient for homodyne detection is not available. PMID:28051094
NASA Technical Reports Server (NTRS)
Vazirani, P.
1995-01-01
The process of combining telemetry signals received at multiple antennas, commonly referred to as arraying, can be used to improve communication link performance in the Deep Space Network (DSN). By coherently adding telemetry from multiple receiving sites, arraying produces an enhancement in signal-to-noise ratio (SNR) over that achievable with any single antenna in the array. A number of different techniques for arraying have been proposed and their performances analyzed in past literature. These analyses have compared different arraying schemes under the assumption that the signals contain additive white Gaussian noise (AWGN) and that the noise observed at distinct antennas is independent. In situations where an unwanted background body is visible to multiple antennas in the array, however, the assumption of independent noises is no longer applicable. A planet with significant radiation emissions in the frequency band of interest can be one such source of correlated noise. For example, during much of Galileo's tour of Jupiter, the planet will contribute significantly to the total system noise at various ground stations. This article analyzes the effects of correlated noise on two arraying schemes currently being considered for DSN applications: full-spectrum combining (FSC) and complex-symbol combining (CSC). A framework is presented for characterizing the correlated noise based on physical parameters, and the impact of the noise correlation on the array performance is assessed for each scheme.
NASA Astrophysics Data System (ADS)
Bera, Aindrila; Saha, Surajit; Ganguly, Jayanta; Ghosh, Manas
2016-08-01
We explore Diamagnetic susceptibility (DMS) of impurity doped quantum dot (QD) in presence of Gaussian white noise introduced to the system additively and multiplicatively. In view of this profiles of DMS have been pursued with variations of geometrical anisotropy and dopant location. We have invoked position-dependent effective mass (PDEM) and position-dependent dielectric screening function (PDDSF) of the system. Presence of noise sometimes suppresses and sometimes amplifies DMS from that of noise-free condition and the extent of suppression/amplification depends on mode of application of noise. It is important to mention that the said suppression/amplification exhibits subtle dependence on use of PDEM, PDDSF and geometrical anisotropy. The study reveals that DMS, or more fundamentally, the effective confinement of LDSS, can be tuned by appropriate mingling of geometrical anisotropy/effective mass/dielectric constant of the system with noise and also on the pathway of application of latter.
NASA Astrophysics Data System (ADS)
Li, Jing-Hui
2008-11-01
In this paper, an electric system with two dichotomous resistors is investigated. It is shown that this system can display two stochastic resonances, which are the amplitude of the periodic response as the functions of the two dichotomous resistors strengthes respectively. In the limits of Gaussian white noise and shot white noise (i.e., the two noises are both Gaussian white noise or shot white noise), no phenomena of resonance appear. By further study, we find that when the system is with three or more multiplicative telegraphic noises, there are three or more stochastic resonances.
Brett, Tobias Galla, Tobias
2014-03-28
We present a heuristic derivation of Gaussian approximations for stochastic chemical reaction systems with distributed delay. In particular, we derive the corresponding chemical Langevin equation. Due to the non-Markovian character of the underlying dynamics, these equations are integro-differential equations, and the noise in the Gaussian approximation is coloured. Following on from the chemical Langevin equation, a further reduction leads to the linear-noise approximation. We apply the formalism to a delay variant of the celebrated Brusselator model, and show how it can be used to characterise noise-driven quasi-cycles, as well as noise-triggered spiking. We find surprisingly intricate dependence of the typical frequency of quasi-cycles on the delay period.
Brett, Tobias; Galla, Tobias
2014-03-28
We present a heuristic derivation of Gaussian approximations for stochastic chemical reaction systems with distributed delay. In particular, we derive the corresponding chemical Langevin equation. Due to the non-Markovian character of the underlying dynamics, these equations are integro-differential equations, and the noise in the Gaussian approximation is coloured. Following on from the chemical Langevin equation, a further reduction leads to the linear-noise approximation. We apply the formalism to a delay variant of the celebrated Brusselator model, and show how it can be used to characterise noise-driven quasi-cycles, as well as noise-triggered spiking. We find surprisingly intricate dependence of the typical frequency of quasi-cycles on the delay period.
Gaussian statistics for palaeomagnetic vectors
Love, J.J.; Constable, C.G.
2003-01-01
With the aim of treating the statistics of palaeomagnetic directions and intensities jointly and consistently, we represent the mean and the variance of palaeomagnetic vectors, at a particular site and of a particular polarity, by a probability density function in a Cartesian three-space of orthogonal magnetic-field components consisting of a single (unimoda) non-zero mean, spherically-symmetrical (isotropic) Gaussian function. For palaeomagnetic data of mixed polarities, we consider a bimodal distribution consisting of a pair of such symmetrical Gaussian functions, with equal, but opposite, means and equal variances. For both the Gaussian and bi-Gaussian distributions, and in the spherical three-space of intensity, inclination, and declination, we obtain analytical expressions for the marginal density functions, the cumulative distributions, and the expected values and variances for each spherical coordinate (including the angle with respect to the axis of symmetry of the distributions). The mathematical expressions for the intensity and off-axis angle are closed-form and especially manageable, with the intensity distribution being Rayleigh-Rician. In the limit of small relative vectorial dispersion, the Gaussian (bi-Gaussian) directional distribution approaches a Fisher (Bingham) distribution and the intensity distribution approaches a normal distribution. In the opposite limit of large relative vectorial dispersion, the directional distributions approach a spherically-uniform distribution and the intensity distribution approaches a Maxwell distribution. We quantify biases in estimating the properties of the vector field resulting from the use of simple arithmetic averages, such as estimates of the intensity or the inclination of the mean vector, or the variances of these quantities. With the statistical framework developed here and using the maximum-likelihood method, which gives unbiased estimates in the limit of large data numbers, we demonstrate how to
Consistency relations for large-scale structures with primordial non-Gaussianities
NASA Astrophysics Data System (ADS)
Valageas, Patrick; Taruya, Atsushi; Nishimichi, Takahiro
2017-01-01
We investigate how the consistency relations of large-scale structures are modified when the initial density field is not Gaussian. We consider both scenarios where the primordial density field can be written as a nonlinear functional of a Gaussian field and more general scenarios where the probability distribution of the primordial density field can be expanded around the Gaussian distribution, up to all orders over δL 0. Working at linear order over the non-Gaussianity parameters fNL(n ) or Sn, we find that the consistency relations for the matter density fields are modified as they include additional contributions that involve all-order mixed linear-nonlinear correlations ⟨∏δL∏δ ⟩. We derive the conditions needed to recover the simple Gaussian form of the consistency relations. This corresponds to scenarios that become Gaussian in the squeezed limit. Our results also apply to biased tracers and velocity or momentum cross-correlations.
Fault diagnosis using noise modeling and a new artificial immune system based algorithm
NASA Astrophysics Data System (ADS)
Abbasi, Farshid; Mojtahedi, Alireza; Ettefagh, Mir Mohammad
2015-12-01
A new fault classification/diagnosis method based on artificial immune system (AIS) algorithms for the structural systems is proposed. In order to improve the accuracy of the proposed method, i.e., higher success rate, Gaussian and non-Gaussian noise generating models are applied to simulate environmental noise. The identification of noise model, known as training process, is based on the estimation of the noise model parameters by genetic algorithms (GA) utilizing real experimental features. The proposed fault classification/diagnosis algorithm is applied to the noise contaminated features. Then, the results are compared to that obtained without noise modeling. The performance of the proposed method is examined using three laboratory case studies in two healthy and damaged conditions. Finally three different types of noise models are studied and it is shown experimentally that the proposed algorithm with non-Gaussian noise modeling leads to more accurate clustering of memory cells as the major part of the fault classification procedure.
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 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. 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.
Robust Gaussian teleportation with attenuation and nonunity gain
NASA Astrophysics Data System (ADS)
de Faria, Alencar J.
2016-12-01
The average fidelity of the teleportation of coherent states is calculated for general Gaussian bipartite systems shared by the partners of the protocol, Alice and Bob. It is considered that the shared Gaussian bipartite modes suffer independent attenuations before the processing of Alice and Bob. In addition, the classical communication between the partners can be controlled by a gain not necessarily unitary. Comparing with the classical fidelity threshold of measure-and-prepare methods, we establish several genuinely quantum teleportation conditions which depend on the gain and the local attenuations. If the gain can be tuned to maximize the bipartite state set capable of performing genuinely quantum teleportation, then a condition for teleportation robust against local attenuations is found. This condition is demonstrated to be essentially equivalent to the condition of robust Gaussian bipartite entanglement, obtained in previous articles, showing that the robustness against attenuations is an entanglement property relevant for characterization and application of bipartite systems. For the derivation of the robust teleportation conditions, the Gaussian operations onto the bipartite system are thoroughly studied, so that the transformations that maintain the fidelity invariant are found. Some scenarios for different Gaussian bipartite states are presented and discussed.
Non-Gaussian bias: insights from discrete density peaks
Desjacques, Vincent; Riotto, Antonio; Gong, Jinn-Ouk E-mail: jinn-ouk.gong@apctp.org
2013-09-01
Corrections induced by primordial non-Gaussianity to the linear halo bias can be computed from a peak-background split or the widespread local bias model. However, numerical simulations clearly support the prediction of the former, in which the non-Gaussian amplitude is proportional to the linear halo bias. To understand better the reasons behind the failure of standard Lagrangian local bias, in which the halo overdensity is a function of the local mass overdensity only, we explore the effect of a primordial bispectrum on the 2-point correlation of discrete density peaks. We show that the effective local bias expansion to peak clustering vastly simplifies the calculation. We generalize this approach to excursion set peaks and demonstrate that the resulting non-Gaussian amplitude, which is a weighted sum of quadratic bias factors, precisely agrees with the peak-background split expectation, which is a logarithmic derivative of the halo mass function with respect to the normalisation amplitude. We point out that statistics of thresholded regions can be computed using the same formalism. Our results suggest that halo clustering statistics can be modelled consistently (in the sense that the Gaussian and non-Gaussian bias factors agree with peak-background split expectations) from a Lagrangian bias relation only if the latter is specified as a set of constraints imposed on the linear density field. This is clearly not the case of standard Lagrangian local bias. Therefore, one is led to consider additional variables beyond the local mass overdensity.
Train noise reduction scenarios for compliance with future noise legislation
NASA Astrophysics Data System (ADS)
Leth, S.
2003-10-01
The Technical Specification for Interoperability (TSI) for high-speed trains on the European market includes limits on noise emission. These and other future restrictions on exterior noise of high-speed and intercity trains will require that train manufacturers implement noise control measures early in the design phase. A fundamental problem faced by manufacturers during the design process is determining how much noise reduction is required for each of the various noise sources on the train in order to achieve an optimal balance. To illustrate this process, estimates are presented of the contributions from different sources on existing Bombardier trains, based on measured data, numerical calculations and empirical formulae. In addition, methods of achieving the required noise reductions for different sources are briefly discussed along with targets for future exterior noise emission. Measurement results presented demonstrate the importance of track quality in noise emission. Noise restrictions, including future legislation, must give proper recognition to this important parameter.
Audio-visual enhancement of speech in noise.
Girin, L; Schwartz, J L; Feng, G
2001-06-01
A key problem for telecommunication or human-machine communication systems concerns speech enhancement in noise. In this domain, a certain number of techniques exist, all of them based on an acoustic-only approach--that is, the processing of the audio corrupted signal using audio information (from the corrupted signal only or additive audio information). In this paper, an audio-visual approach to the problem is considered, since it has been demonstrated in several studies that viewing the speaker's face improves message intelligibility, especially in noisy environments. A speech enhancement prototype system that takes advantage of visual inputs is developed. A filtering process approach is proposed that uses enhancement filters estimated with the help of lip shape information. The estimation process is based on linear regression or simple neural networks using a training corpus. A set of experiments assessed by Gaussian classification and perceptual tests demonstrates that it is indeed possible to enhance simple stimuli (vowel-plosive-vowel sequences) embedded in white Gaussian noise.
Experimental demonstration of macroscopic quantum coherence in Gaussian states
Marquardt, Christoph; Leuchs, Gerd; Andersen, Ulrik L.; Takeno, Yuishi; Yukawa, Mitsuyoshi; Yonezawa, Hidehiro; Furusawa, Akira
2007-09-15
We witness experimentally the presence of macroscopic coherence in Gaussian quantum states using a recently proposed criterion [E. G. Cavalcanti and M. D. Reid, Phys. Rev. Lett. 97 170405 (2006)]. The macroscopic coherence stems from interference between macroscopically distinct states in phase space, and we prove experimentally that a coherent state contains these features with a distance in phase space of 0.51{+-}0.02 shot noise units. This is surprising because coherent states are generally considered being at the border between classical and quantum states, not yet displaying any nonclassical effect. For squeezed and entangled states the effect may be larger but depends critically on the state purity.
The Switch in a Genetic Toggle System with Lévy Noise
Xu, Yong; Li, Yongge; Zhang, Hao; Li, Xiaofan; Kurths, Jürgen
2016-01-01
A bistable toggle switch is a paradigmatic model in the field of biology. The dynamics of the system induced by Gaussian noise has been intensively investigated, but Gaussian noise cannot incorporate large bursts typically occurring in real experiments. This paper aims to examine effects of variations from one protein imposed by a non-Gaussian Lévy noise, which is able to describe even large jumps, on the coherent switch and the on/off switch via the steady-state probability density, the joint steady-state probability density, and the mean first passage time. We find that a large burst of one protein due to the Lévy noises can induce coherent switches even with small noise intensities in contrast to the Gaussian case which requires large intensities for this. The influences of the stability index, skewness parameter and noise intensity on the on/off switch are analyzed, leading to an adjustment of the concentrations of both proteins and a decision which stable point to stay most. The mean first passage times show complex effects under Lévy noise, especially the stability index and skewness parameter. Our results also imply that the presence of non-Gaussian Lévy noises has fundamentally changed the escape mechanism in such a system compared with Gaussian noise. PMID:27539010
NASA Technical Reports Server (NTRS)
Bragdon, C. R.
1982-01-01
Airport and community land use planning as they relate to airport noise reduction are discussed. Legislation, community relations, and the physiological effect of airport noise are considered. Noise at the Logan, Los Angeles, and Minneapolis/St. Paul airports is discussed.
Speckle phase noise in coherent laser ranging: fundamental precision limitations.
Baumann, Esther; Deschênes, Jean-Daniel; Giorgetta, Fabrizio R; Swann, William C; Coddington, Ian; Newbury, Nathan R
2014-08-15
Frequency-modulated continuous-wave laser detection and ranging (FMCW LADAR) measures the range to a surface through coherent detection of the backscattered light from a frequency-swept laser source. The ultimate limit to the range precision of FMCW LADAR, or any coherent LADAR, to a diffusely scattering surface will be determined by the unavoidable speckle phase noise. Here, we demonstrate the two main manifestations of this limit. First, frequency-dependent speckle phase noise leads to a non-Gaussian range distribution having outliers that approach the system range resolution, regardless of the signal-to-noise ratio. These outliers are reduced only through improved range resolution (i.e., higher optical bandwidths). Second, if the range is measured during a continuous lateral scan across a surface, the spatial pattern of speckle phase is converted to frequency noise, which leads to additional excess range uncertainty. We explore these two effects and show that laboratory results agree with analytical expressions and numerical simulations. We also show that at 1 THz optical bandwidth, range precisions below 10 μm are achievable regardless of these effects.
Highway traffic segmentation using super-resolution and Gaussian mixture model
NASA Astrophysics Data System (ADS)
Yousef, Amr Hussein; Flora, Jeff; Iftekharuddin, Khan
2013-09-01
One benefit of employing computer vision techniques to extract individual vehicles from a highway traffic scene is the abundance of networked, traffic surveillance cameras that may be leveraged as the input video. However, the acquisition sensors that are monitoring the highway traffic will have very limited quality. Additionally, video streams are heavily compressed, causing noise and, in some cases, visible artifacts to be introduced into the video. Further challenges are presented by external environmental and weather conditions, such as rain, fog, and snow, that cause video blurring or noise. The resulting output of a segmentation algorithm yields poorer results, with many vehicles undetected or partially detected. Our goal is to extract individual vehicles from a highway traffic scenes using super-resolution and the utilization of Gaussian mixture model algorithm (GMM). We used a speeded-up enhanced stochastic Wiener filter for SR reconstruction and restoration. It can be used to remove artifacts and enhance the visual quality of the reconstructed images and can be implemented efficiently in the frequency domain. The filter derivation depends on the continuous-discrete-continuous (CDC) model that represents most of the degradations encountered during the image-gathering and image-display processes. Then, we use GMM followed by the clustering of individual vehicles. Individual vehicles are detected from the segmented scene through the use of a series of morphological operations, followed by two-dimensional connected component labeling. We evaluate our hybrid approach quantitatively in the segmentation of the extracted vehicles.
Industrial jet noise: Coanda nozzles
NASA Astrophysics Data System (ADS)
Li, P.; Halliwell, N. A.
1985-04-01
Within the U.K. manufacturing industries noise from industrial jets ranks third as a major contributor to industrial deafness. Noise control is hindered because use is made of the air once it has exuded from the nozzle exit. Important tasks include swarf removal, paint spreading, cooling, etc. Nozzles which employ the Coanda effect appear to offer the possibility of significant noise reduction whilst maintaining high thrust efficiency when compared with the commonly used simple open pipe or ordinary convergent nozzle. In this paper the performance of Coanda-type nozzles is examined in detail and an index rating for nozzle performance is introduced. Results show that far field stagnation pressure distributions are Gaussian and similar in all cases with a dispersion coefficient σ = 0·64. Noise reduction and thrust efficiency are shown to be closely related to the design geometry of the central body of the nozzle. Performance is based on four fundamental characteristics, these being the noise level at 1 m from the exit and at a 90° station to the nozzle axis, and the thrust on a chosen profile, the noise reduction and the thrust efficiency. Physically, performance is attributed to flow near field effects where, although all nozzles are choked, shock cell associated noise is absent.
FPGA design and implementation of Gaussian filter
NASA Astrophysics Data System (ADS)
Yang, Zhihui; Zhou, Gang
2015-12-01
In this paper , we choose four different variances of 1,3,6 and 12 to conduct FPGA design with three kinds of Gaussian filtering algorithm ,they are implementing Gaussian filter with a Gaussian filter template, Gaussian filter approximation with mean filtering and Gaussian filter approximation with IIR filtering. By waveform simulation and synthesis, we get the processing results on the experimental image and the consumption of FPGA resources of the three methods. We set the result of Gaussian filter used in matlab as standard to get the result error. By comparing the FPGA resources and the error of FPGA implementation methods, we get the best FPGA design to achieve a Gaussian filter. Conclusions can be drawn based on the results we have already got. When the variance is small, the FPGA resources is enough for the algorithm to implement Gaussian filter with a Gaussian filter template which is the best choice. But when the variance is so large that there is no more FPGA resources, we can chose the mean to approximate Gaussian filter with IIR filtering.
NASA Astrophysics Data System (ADS)
HEINONEN-GUZEJEV, M.; VUORINEN, H. S.; KAPRIO, J.; HEIKKILÄ, K.; MUSSALO-RAUHAMAA, H.; KOSKENVUO, M.
2000-07-01
Self-report of noise exposure was compared with the information on noise maps while taking into account measures of self-reported annoyance and noise sensitivity. Self-report data were analyzed for 1495 subjects participating in a case-control study of hypertension from the Finnish Twin Cohort who had replied to a questionnaire in 1988. In addition, noise map information was included in analyses of the 218 study subjects living in the Metropolitan Area of Helsinki. The results show that: (1) In the factor analysis based on all subjects self-report of transportation noise exposure formed an own factor independent of the annoyance variables or noise sensitivity. Annoyance items loaded on to two different factors termed nighttime and daytime annoyance. Noise sensitivity did not load to either of the factors of annoyance. For the subsample with noise map information, the results indicated that: (2) Noise sensitivity was independent of noise map information. (3) Subjects with high noise sensitivity reported more transportation noise exposure than subjects with low noise sensitivity and they reported aircraft, railway and road traffic noise exposure outside the environmental noise map areas almost twice as often as non-sensitive subjects. (4) Noise map information and self-report of noise exposure were consistently associated when aircraft noise was considered. Self-report of noise related items may supplement noise map information in noise protection.
Noise measurements on the helicopter BK 117 design. Weighted noise levels and influence of airspeed
NASA Astrophysics Data System (ADS)
Splettstoesser, Wolf R.; Anders, Klaus P.; Spiegel, Karl-Heinz
1986-11-01
Noise measurements on the prototype helicopter BK 117 were performed in strict compliance with the proposed international Civil Aviation Organization regulations for noise certification of helicopters. Measurement procedure, noise data acquisition, analysis and reduction as well as applied correction procedures are described. Effective perceived noise levels (EPNL) and other noise descriptors were evaluated and related to the proposed noise limits. Additional level flyover tests with variable airspeed were conducted to investigate the resulting effect on the EPNL and other noise measures.
Non-Gaussian Stochastic Processes.
1986-02-28
Underwriting Risk and Return Paradox Revisited," J. Risk and Insurance .24.L 621-627 (1982). P. Brockett and B. Arnold, "Identifiability for Dependent...Some Ruin Calculations," J. Risk and Insurance 5DIAL 727-731 (1983). P. Brockett, S. Cox, and R. Witt, "Self-Insurance and the Probability of...Financial Regret," J. Risk and Insurance 51(4) 720-729 (1984). P. Brockett, "The Likelihood Ratio Detector for Non-Gaussian Infinitely Divisible and Linear
Gaussian effective potential: Quantum mechanics
NASA Astrophysics Data System (ADS)
Stevenson, P. M.
1984-10-01
We advertise the virtues of the Gaussian effective potential (GEP) as a guide to the behavior of quantum field theories. Much superior to the usual one-loop effective potential, the GEP is a natural extension of intuitive notions familiar from quantum mechanics. A variety of quantum-mechanical examples are studied here, with an eye to field-theoretic analogies. Quantum restoration of symmetry, dynamical mass generation, and "quantum-mechanical resuscitation" are among the phenomena discussed. We suggest how the GEP could become the basis of a systematic approximation procedure. A companion paper will deal with scalar field theory.
Image recovery under nonlinear and non-Gaussian degradations.
Sadhar, S I; Rajagopalan, A N
2005-04-01
A new two-dimensional recursive filter for recovering degraded images is proposed that is based on particle-filter theory. The main contribution of this work lies in evolving a framework that has the potential to recover images suffering from a general class of degradations such as system nonlinearity and non-Gaussian observation noise. Samples of the prior probability distribution of the original image are obtained by propagating the samples through an appropriate state model. Given the measurement model and the degraded image, the weights of the samples are computed. The samples and their corresponding weights are used to calculate the conditional mean that yields an estimate of the original image. The proposed method is validated by demonstrating its effectiveness in recovering images degraded by film-grain noise. Synthetic as well as real examples are considered for this purpose. Performance is also compared with that of an existing scheme.
Laser line shape and spectral density of frequency noise
Stephan, G.M.; Blin, S.; Besnard, P.; Tam, T.T.; Tetu, M.
2005-04-01
Published experimental results show that single-mode laser light is characterized in the microwave range by a frequency noise which essentially includes a white part and a 1/f (flicker) part. We theoretically show that the spectral density (the line shape) which is compatible with these results is a Voigt profile whose Lorentzian part or homogeneous component is linked to the white noise and the Gaussian part to the 1/f noise. We measure semiconductor laser line profiles and verify that they can be fit with Voigt functions. It is also verified that the width of the Lorentzian part varies like 1/P where P is the laser power while the width of the Gaussian part is more of a constant. Finally, we theoretically show from first principles that laser line shapes are also described by Voigt functions where the Lorentzian part is the laser Airy function and the Gaussian part originates from population noise.
Simulation calculation and characteristics analysis of coil motion noise
NASA Astrophysics Data System (ADS)
Meng, Yang; Peng, Cong; Fu, MingYe; Lu, Yiming; Yu, Zining; Zhu, Kaiguang
2017-01-01
Coil motion noise is one of the largest noises in airborne electromagnetic exploration, which results from the variations of magnetic flux in the Earth's magnetic accompanied by the receiver coil's movement during the flight. On the assumption of attitude measurements, coil motion noise is calculated according to roll, pitch and yaw of the receiver coils. Therefore, the characteristics of coil motion noise are analyzed in time domain, frequency domain and time-frequency domain. And the Gaussianity of coil motion noise is also discussed using the histogram of data and its estimated Gaussian function, and another method termed normal probability paper. All of these are to lay the foundation for removal of coil motion noise in airborne electromagnetic detection.
Audience noise in concert halls during musical performances.
Jeong, Cheol-Ho; Marie, Pierre; Brunskog, Jonas; Møller Petersen, Claus
2012-04-01
Noise generated by the audience during musical performances is audible and sometimes disturbing. In this study, an attempt to estimate such audience noise was carried out. From the recordings of performances in five performance spaces (four concert halls and one opera house), probability density functions of the sound pressure levels were obtained in octave bands, which were fitted with three Gaussian distribution curves. The Gaussian distribution curve with the lowest mean value corresponds to a mixture of the technical background noise and audience generated noise, which is named the mixed background noise. Finally, the audience noise distribution is extracted by energy subtraction of the technical background noise levels measured in an empty condition from the mixed background noise levels. As a single index, L(90) of the audience noise distribution is named the audience noise level. Empirical prediction models were made using the four orchestra concert halls, revealing that the audience noise level is significantly correlated with the technical background noise level. It is therefore concluded that a relaxation of the current background noise recommendations for concert halls is not recommended.
The Availability of Logical Operation Induced by Dichotomous Noise for a Nonlinear Bistable System
NASA Astrophysics Data System (ADS)
Xu, Yong; Jin, Xiaoqin; Zhang, Huiqing; Yang, Tingting
2013-08-01
Instead of a continuous system driven by Gaussian white noise, logical stochastic resonance will be investigated in a nonlinear bistable system with two thresholds driven by dichotomous noise, which shows a phenomenon different from Gaussian white noise. We can realize two parallel logical operations by simply adjusting the values of these two thresholds. Besides, to quantify the reliability of obtaining the correct logic output, we numerically calculate the success probability, and effects of dichotomous noise on the success probability are observed, these observations show that the reliability of realizing logical operation in the bistable system can be improved through optimizing parameters of dichotomous noise.
Information bounds for Gaussian copulas
Hoff, Peter D.; Niu, Xiaoyue; Wellner, Jon A.
2013-01-01
Often of primary interest in the analysis of multivariate data are the copula parameters describing the dependence among the variables, rather than the univariate marginal distributions. Since the ranks of a multivariate dataset are invariant to changes in the univariate marginal distributions, rank-based estimators are natural candidates for semiparametric copula estimation. Asymptotic information bounds for such estimators can be obtained from an asymptotic analysis of the rank likelihood, i.e. the probability of the multivariate ranks. In this article, we obtain limiting normal distributions of the rank likelihood for Gaussian copula models. Our results cover models with structured correlation matrices, such as exchangeable or circular correlation models, as well as unstructured correlation matrices. For all Gaussian copula models, the limiting distribution of the rank likelihood ratio is shown to be equal to that of a parametric likelihood ratio for an appropriately chosen multivariate normal model. This implies that the semiparametric information bounds for rank-based estimators are the same as the information bounds for estimators based on the full data, and that the multivariate normal distributions are least favorable. PMID:25313292
Monogamy inequality for distributed gaussian entanglement.
Hiroshima, Tohya; Adesso, Gerardo; Illuminati, Fabrizio
2007-02-02
We show that for all n-mode Gaussian states of continuous variable systems, the entanglement shared among n parties exhibits the fundamental monogamy property. The monogamy inequality is proven by introducing the Gaussian tangle, an entanglement monotone under Gaussian local operations and classical communication, which is defined in terms of the squared negativity in complete analogy with the case of n-qubit systems. Our results elucidate the structure of quantum correlations in many-body harmonic lattice systems.
Fuzzy local Gaussian mixture model for brain MR image segmentation.
Ji, Zexuan; Xia, Yong; Sun, Quansen; Chen, Qiang; Xia, Deshen; Feng, David Dagan
2012-05-01
Accurate brain tissue segmentation from magnetic resonance (MR) images is an essential step in quantitative brain image analysis. However, due to the existence of noise and intensity inhomogeneity in brain MR images, many segmentation algorithms suffer from limited accuracy. In this paper, we assume that the local image data within each voxel's neighborhood satisfy the Gaussian mixture model (GMM), and thus propose the fuzzy local GMM (FLGMM) algorithm for automated brain MR image segmentation. This algorithm estimates the segmentation result that maximizes the posterior probability by minimizing an objective energy function, in which a truncated Gaussian kernel function is used to impose the spatial constraint and fuzzy memberships are employed to balance the contribution of each GMM. We compared our algorithm to state-of-the-art segmentation approaches in both synthetic and clinical data. Our results show that the proposed algorithm can largely overcome the difficulties raised by noise, low contrast, and bias field, and substantially improve the accuracy of brain MR image segmentation.
Extremes of Some Gaussian Random Interfaces
NASA Astrophysics Data System (ADS)
Chiarini, Alberto; Cipriani, Alessandra; Hazra, Rajat Subhra
2016-11-01
In this article we give a general criterion for some dependent Gaussian models to belong to maximal domain of attraction of Gumbel, following an application of the Stein-Chen method studied in Arratia et al. (Ann Probab 17(1):9-25, 1989). We also show the convergence of the associated point process. As an application, we show the conditions are satisfied by some of the well-known supercritical Gaussian interface models, namely, membrane model, massive and massless discrete Gaussian free field, fractional Gaussian free field.
Elegant Gaussian beams for enhanced optical manipulation
Alpmann, Christina Schöler, Christoph; Denz, Cornelia
2015-06-15
Generation of micro- and nanostructured complex light beams attains increasing impact in photonics and laser applications. In this contribution, we demonstrate the implementation and experimental realization of the relatively unknown, but highly versatile class of complex-valued Elegant Hermite- and Laguerre-Gaussian beams. These beams create higher trapping forces compared to standard Gaussian light fields due to their propagation changing properties. We demonstrate optical trapping and alignment of complex functional particles as nanocontainers with standard and Elegant Gaussian light beams. Elegant Gaussian beams will inspire manifold applications in optical manipulation, direct laser writing, or microscopy, where the design of the point-spread function is relevant.
NASA Astrophysics Data System (ADS)
D'Auria, V.; de Lisio, C.; Porzio, A.; Solimeno, S.; Anwar, Javaid; Paris, M. G. A.
2010-03-01
Quantum states with non-Gaussian statistics generated by optical parametric oscillators (OPO) with fluctuating parameters are studied by means of the kurtosis excess of the external field quadratures. The field generated is viewed as the response of a nonlinear device to the fluctuations of pump laser amplitude and frequency, crystal temperature, and cavity detuning, in addition to quantum noise sources. The kurtosis excess has been evaluated perturbatively up to the third order in the strength of the crystal nonlinear coupling factor and the second order in the classical fluctuating parameters. Applied to the device described in Opt. Expr. 13, 948 (2005), the model has given values of the kurtosis excess in good agreement with the measured ones.
D'Auria, V.; Lisio, C. de; Porzio, A.; Solimeno, S.; Anwar, Javaid; Paris, M. G. A.
2010-03-15
Quantum states with non-Gaussian statistics generated by optical parametric oscillators (OPO) with fluctuating parameters are studied by means of the kurtosis excess of the external field quadratures. The field generated is viewed as the response of a nonlinear device to the fluctuations of pump laser amplitude and frequency, crystal temperature, and cavity detuning, in addition to quantum noise sources. The kurtosis excess has been evaluated perturbatively up to the third order in the strength of the crystal nonlinear coupling factor and the second order in the classical fluctuating parameters. Applied to the device described in Opt. Expr. 13, 948 (2005), the model has given values of the kurtosis excess in good agreement with the measured ones.
NASA Technical Reports Server (NTRS)
Mixson, John S.; Wilby, John F.
1991-01-01
The generation and control of flight vehicle interior noise is discussed. Emphasis is placed on the mechanisms of transmission through airborne and structure-borne paths and the control of cabin noise by path modification. Techniques for identifying the relative contributions of the various source-path combinations are also discussed along with methods for the prediction of aircraft interior noise such as those based on the general modal theory and statistical energy analysis.
Generalized phase-shifting algorithms: error analysis and minimization of noise propagation.
Ayubi, Gastón A; Perciante, César D; Di Martino, J Matías; Flores, Jorge L; Ferrari, José A
2016-02-20
Phase shifting is a technique for phase retrieval that requires a series of intensity measurements with certain phase steps. The purpose of the present work is threefold: first we present a new method for generating general phase-shifting algorithms with arbitrarily spaced phase steps. Second, we study the conditions for which the phase-retrieval error due to phase-shift miscalibration can be minimized. Third, we study the phase extraction from interferograms with additive random noise, and deduce the conditions to be satisfied for minimizing the phase-retrieval error. Algorithms with unevenly spaced phase steps are discussed under linear phase-shift errors and additive Gaussian noise, and simulations are presented.
NASA Technical Reports Server (NTRS)
1980-01-01
Environmental Health Systems puts forth an increasing effort in the U.S. to develop ways of controlling noise, particularly in industrial environments due to Federal and State laws, labor union insistence and new findings relative to noise pollution impact on human health. NASA's Apollo guidance control system aided in the development of a noise protection product, SMART. The basis of all SMART products is SMART compound a liquid plastic mixture with exceptional energy/sound absorbing qualities. The basic compound was later refined for noise protection use.
Robustness of composite pulse sequences to time-dependent noise
NASA Astrophysics Data System (ADS)
Kabytayev, Chingiz; Green, Todd J.; Khodjasteh, Kaveh; Viola, Lorenza; Biercuk, Michael J.; Brown, Kenneth R.
2014-03-01
Quantum control protocols can minimize the effect of noise sources that reduce the quality of quantum operations. Originally developed for NMR, composite pulse sequences correct for unknown static control errors . We study these compensating pulses in the general case of time-varying Gaussian control noise using a filter-function approach and detailed numerics. Three different noise models were considered in this work: amplitude noise, detuning noise and simultaneous presence of both noises. Pulse sequences are shown to be robust to noise up to frequencies as high as ~10% of the Rabi frequency. Robustness of pulses designed for amplitude noise is explained using a geometric picture that naturally follows from filter function. We also discuss future directions including new pulses correcting for noise of certain frequency. True J. Merrill and Kenneth R. Brown. arXiv:1203.6392v1. In press Adv. Chem. Phys. (2013)
Classification image weights and internal noise level estimation
NASA Technical Reports Server (NTRS)
Ahumada, Albert J Jr
2002-01-01
For the linear discrimination of two stimuli in white Gaussian noise in the presence of internal noise, a method is described for estimating linear classification weights from the sum of noise images segregated by stimulus and response. The recommended method for combining the two response images for the same stimulus is to difference the average images. Weights are derived for combining images over stimuli and observers. Methods for estimating the level of internal noise are described with emphasis on the case of repeated presentations of the same noise sample. Simple tests for particular hypotheses about the weights are shown based on observer agreement with a noiseless version of the hypothesis.
Matching optics for Gaussian beams
NASA Technical Reports Server (NTRS)
Gunter, William D. (Inventor)
1991-01-01
A system of matching optics for Gaussian beams is described. The matching optics system is positioned between a light beam emitter (such as a laser) and the input optics of a second optics system whereby the output from the light beam emitter is converted into an optimum input for the succeeding parts of the second optical system. The matching optics arrangement includes the combination of a light beam emitter, such as a laser with a movable afocal lens pair (telescope) and a single movable lens placed in the laser's output beam. The single movable lens serves as an input to the telescope. If desired, a second lens, which may be fixed, is positioned in the beam before the adjustable lens to serve as an input processor to the movable lens. The system provides the ability to choose waist diameter and position independently and achieve the desired values with two simple adjustments not requiring iteration.
Cylindrical quasi-Gaussian beams.
Mitri, F G
2013-11-15
Making use of the complex-source-point method in cylindrical coordinates, an exact solution representing a cylindrical quasi-Gaussian beam of arbitrary waist w(0) satisfying both the Helmholtz and Maxwell's equations is introduced. The Cartesian components of the electromagnetic field are derived stemming from different polarizations of the magnetic and electric vector potentials based on Maxwell's vectorial equations and Lorenz's gauge condition, without any approximations. Computations illustrate the theory for tightly focused and quasi-collimated cylindrical beams. The results are particularly useful in beam-forming design using high-aperture or collimated cylindrical laser beams in imaging microscopy, particle manipulation, optical tweezers, and the study of scattering, radiation forces, and torque on cylindrical structures.
Near grazing scattering from non-Gaussian ocean surfaces
NASA Technical Reports Server (NTRS)
Kim, Yunjin; Rodriguez, Ernesto
1993-01-01
We investigate the behavior of the scattered electromagnetic waves from non-Gaussian ocean surfaces at near grazing incidence. Even though the scattering mechanisms at moderate incidence angles are relatively well understood, the same is not true for near grazing rough surface scattering. However, from the experimental ocean scattering data, it has been observed that the backscattering cross section of a horizontally polarized wave can be as large as the vertical counterpart at near grazing incidence. In addition, these returns are highly intermittent in time. There have been some suggestions that these unexpected effects may come from shadowing or feature scattering. Using numerical scattering simulations, it can be shown that the horizontal backscattering cannot be larger than the vertical one for the Gaussian surfaces. Our main objective of this study is to gain a clear understanding of scattering mechanisms underlying the near grazing ocean scattering. In order to evaluate the backscattering cross section from ocean surfaces at near grazing incidence, both the hydrodynamic modeling of ocean surfaces and an accurate near grazing scattering theory are required. For the surface modeling, we generate Gaussian surfaces from the ocean surface power spectrum which is derived using several experimental data. Then, weakly nonlinear large scale ocean surfaces are generated following Longuet-Higgins. In addition, the modulation of small waves by large waves is included using the conservation of wave action. For surface scattering, we use MOM (Method of Moments) to calculate the backscattering from scattering patches with the two scale shadowing approximation. The differences between Gaussian and non-Gaussian surface scattering at near grazing incidence are presented.
Lossy cardiac x-ray image compression based on acquisition noise
NASA Astrophysics Data System (ADS)
de Bruijn, Frederik J.; Slump, Cornelis H.
1997-05-01
In lossy medical image compression, the requirements for the preservation of diagnostic integrity cannot be easily formulated in terms of a perceptual model. Especially since, in reality, human visual perception is dependent on numerous factors such as the viewing conditions and psycho-visual factors. Therefore, we investigate the possibility to develop alternative measures for data loss, based on the characteristics of the acquisition system, in our case, a digital cardiac imaging system. In general, due to the low exposure, cardiac x-ray images tend to be relatively noisy. The main noise contributions are quantum noise and electrical noise. The electrical noise is not correlated with the signal. In addition, the signal can be transformed such that the correlated Poisson-distributed quantum noise is transformed into an additional zero-mean Gaussian noise source which is uncorrelated with the signal. Furthermore, the systems modulation transfer function imposes a known spatial-frequency limitation to the output signal. In the assumption that noise which is not correlated with the signal contains no diagnostic information, we have derived a compression measure based on the acquisition parameters of a digital cardiac imaging system. The measure is used for bit- assignment and quantization of transform coefficients. We present a blockwise-DCT compression algorithm which is based on the conventional JPEG-standard. However, the bit- assignment to the transform coefficients is now determined by an assumed noise variance for each coefficient, for a given set of acquisition parameters. Experiments with the algorithm indicate that a bit rate of 0.6 bit/pixel is feasible, without apparent loss of clinical information.
Wiest-Daesslé, Nicolas; Prima, Sylvain; Coupé, Pierrick; Morrissey, Sean Patrick; Barillot, Christian
2008-01-01
Diffusion-Weighted MRI (DW-MRI) is subject to random noise yielding measures that are different from their real values, and thus biasing the subsequently estimated tensors. The Non-Local Means (NLMeans) filter has recently been proposed to denoise MRI with high signal-to-noise ratio (SNR). This filter has been shown to allow the best restoration of image intensities for the estimation of diffusion tensors (DT) compared to state-of-the-art methods. However, for DW-MR images with high b-values (and thus low SNR), the noise, which is strictly Rician-distributed, can no longer be approximated as additive white Gaussian, as implicitly assumed in the classical formulation of the NLMeans. High b-values are typically used in high angular resolution diffusion imaging (HARDI) or q-space imaging (QSI), for which an optimal restoration is critical. In this paper, we propose to adapt the NLMeans filter to Rician noise corrupted data. Validation is performed on synthetic data and on real data for both conventional MR images and DT images. Our adaptation outperforms the original NLMeans filter in terms of peak-signal-to-noise ratio (PSNR) for DW-MRI.
Improved 3D wavelet-based de-noising of fMRI data
NASA Astrophysics Data System (ADS)
Khullar, Siddharth; Michael, Andrew M.; Correa, Nicolle; Adali, Tulay; Baum, Stefi A.; Calhoun, Vince D.
2011-03-01
Functional MRI (fMRI) data analysis deals with the problem of detecting very weak signals in very noisy data. Smoothing with a Gaussian kernel is often used to decrease noise at the cost of losing spatial specificity. We present a novel wavelet-based 3-D technique to remove noise in fMRI data while preserving the spatial features in the component maps obtained through group independent component analysis (ICA). Each volume is decomposed into eight volumetric sub-bands using a separable 3-D stationary wavelet transform. Each of the detail sub-bands are then treated through the main denoising module. This module facilitates computation of shrinkage factors through a hierarchical framework. It utilizes information iteratively from the sub-band at next higher level to estimate denoised coefficients at the current level. These de-noised sub-bands are then reconstructed back to the spatial domain using an inverse wavelet transform. Finally, the denoised group fMRI data is analyzed using ICA where the data is decomposed in to clusters of functionally correlated voxels (spatial maps) as indicators of task-related neural activity. The proposed method enables the preservation of shape of the actual activation regions associated with the BOLD activity. In addition it is able to achieve high specificity as compared to the conventionally used FWHM (full width half maximum) Gaussian kernels for smoothing fMRI data.
Measurement-induced Nonlocality for Gaussian States
NASA Astrophysics Data System (ADS)
Ma, Ruifen; Hou, Jinchuan; Qi, Xiaofei
2017-04-01
We establish an analytic formula of measurement-induced nonlocality (MIN) for two-mode squeezed thermal states and mixed thermal states. Different from the quantum discord case, we show that there is no Gaussian version of MIN by Gaussian positive operator valued measurements.
Bayesian electron density inference from JET lithium beam emission spectra using Gaussian processes
NASA Astrophysics Data System (ADS)
Kwak, Sehyun; Svensson, J.; Brix, M.; Ghim, Y.-C.; Contributors, JET
2017-03-01
A Bayesian model to infer edge electron density profiles is developed for the JET lithium beam emission spectroscopy (Li-BES) system, measuring Li I (2p-2s) line radiation using 26 channels with ∼1 cm spatial resolution and 10∼ 20 ms temporal resolution. The density profile is modelled using a Gaussian process prior, and the uncertainty of the density profile is calculated by a Markov Chain Monte Carlo (MCMC) scheme. From the spectra measured by the transmission grating spectrometer, the Li I line intensities are extracted, and modelled as a function of the plasma density by a multi-state model which describes the relevant processes between neutral lithium beam atoms and plasma particles. The spectral model fully takes into account interference filter and instrument effects, that are separately estimated, again using Gaussian processes. The line intensities are inferred based on a spectral model consistent with the measured spectra within their uncertainties, which includes photon statistics and electronic noise. Our newly developed method to infer JET edge electron density profiles has the following advantages in comparison to the conventional method: (i) providing full posterior distributions of edge density profiles, including their associated uncertainties, (ii) the available radial range for density profiles is increased to the full observation range (∼26 cm), (iii) an assumption of monotonic electron density profile is not necessary, (iv) the absolute calibration factor of the diagnostic system is automatically estimated overcoming the limitation of the conventional technique and allowing us to infer the electron density profiles for all pulses without preprocessing the data or an additional boundary condition, and (v) since the full spectrum is modelled, the procedure of modulating the beam to measure the background signal is only necessary for the case of overlapping of the Li I line with impurity lines.
Noise contaminated transmittance
Zardecki, A.; McVey, B.D.; Nelson, D.H.
1997-09-01
The authors compare the efficiency of a classifier based on probabilistic neural networks and the general least squares method. Both methods must accommodate noise due to uncertainty in the measured spectrum at each wavelength. The evaluation of both methods is based on a simulated transmittance spectrum, in which the received signal is supplemented by an additive admixture of noise. To obtain a realistic description of the noise model, they generate several hundred laser pulses for each wavelength under consideration. These pulses have a predetermined correlation matrix for different wavelengths; furthermore, they are composed of three components accounting for the randomness of the observed spectrum. The first component is the correlated 1/f noise; the second component is due to uncorrelated 1/f noise; the third one is the uncorrelated white noise. The probabilistic neural network fails to retrieve the species concentration correctly for large noise levels; on the other hand, its predictions being confined to a fixed number of concentration bins, the network produces relatively small variances. To a large extent, the general least square method avoids the false alarms. It reproduces the average concentrations correctly; however, the concentration variances can be large.
Jiang, Tao; Shan, Guogen
2016-01-01
Residue fluctuations in protein structures have been shown to be highly associated with various protein functions. Gaussian network model (GNM), a simple representative coarse-grained model, was widely adopted to reveal function-related protein dynamics. We directly utilized the high frequency modes generated by GNM and further performed Gaussian Naive Bayes (GNB) to identify hot spot residues. Two coding schemes about the feature vectors were implemented with varying distance cutoffs for GNM and sliding window sizes for GNB based on tenfold cross validations: one by using only a single high mode and the other by combining multiple modes with the highest frequency. Our proposed methods outperformed the previous work that did not directly utilize the high frequency modes generated by GNM, with regard to overall performance evaluated using F1 measure. Moreover, we found that inclusion of more high frequency modes for a GNB classifier can significantly improve the sensitivity. The present study provided additional valuable insights into the relation between the hot spots and the residue fluctuations. PMID:27882325
Nonlinear software sensor for monitoring genetic regulation processes with noise and modeling errors
NASA Astrophysics Data System (ADS)
Ibarra-Junquera, V.; Torres, L. A.; Rosu, H. C.; Argüello, G.; Collado-Vides, J.
2005-07-01
Nonlinear control techniques by means of a software sensor that are commonly used in chemical engineering could be also applied to genetic regulation processes. We provide here a realistic formulation of this procedure by introducing an additive white Gaussian noise, which is usually found in experimental data. Besides, we include model errors, meaning that we assume we do not know the nonlinear regulation function of the process. In order to illustrate this procedure, we employ the Goodwin dynamics of the concentrations [B. C. Goodwin, Temporal Oscillations in Cells (Academic, New York, 1963)] in the simple form recently applied to single gene systems and some operon cases [H. De Jong, J. Comput. Biol. 9, 67 (2002)], which involves the dynamics of the mRNA, given protein and metabolite concentrations. Further, we present results for a three gene case in coregulated sets of transcription units as they occur in prokaryotes. However, instead of considering their full dynamics, we use only the data of the metabolites and a designed software sensor. We also show, more generally, that it is possible to rebuild the complete set of nonmeasured concentrations despite the uncertainties in the regulation function or, even more, in the case of not knowing the mRNA dynamics. In addition, the rebuilding of concentrations is not affected by the perturbation due to the additive white Gaussian noise and also we managed to filter the noisy output of the biological system.
Ibarra-Junquera, V; Torres, L A; Rosu, H C; Argüello, G; Collado-Vides, J
2005-07-01
Nonlinear control techniques by means of a software sensor that are commonly used in chemical engineering could be also applied to genetic regulation processes. We provide here a realistic formulation of this procedure by introducing an additive white Gaussian noise, which is usually found in experimental data. Besides, we include model errors, meaning that we assume we do not know the nonlinear regulation function of the process. In order to illustrate this procedure, we employ the Goodwin dynamics of the concentrations [B. C. Goodwin, (Academic, New York, 1963)] in the simple form recently applied to single gene systems and some operon cases [H. De Jong, J. Comput. Biol. 9, 67 (2002)], which involves the dynamics of the mRNA, given protein and metabolite concentrations. Further, we present results for a three gene case in coregulated sets of transcription units as they occur in prokaryotes. However, instead of considering their full dynamics, we use only the data of the metabolites and a designed software sensor. We also show, more generally, that it is possible to rebuild the complete set of nonmeasured concentrations despite the uncertainties in the regulation function or, even more, in the case of not knowing the mRNA dynamics. In addition, the rebuilding of concentrations is not affected by the perturbation due to the additive white Gaussian noise and also we managed to filter the noisy output of the biological system.
NASA Astrophysics Data System (ADS)
Ganguly, Jayanta; Saha, Surajit; Bera, Aindrila; Ghosh, Manas
2016-10-01
We examine the profiles of optical rectification (OR), second harmonic generation (SHG) and third harmonic generation (THG) of impurity doped QDs under the combined influence of hydrostatic pressure (HP) and temperature (T) in presence and absence of Gaussian white noise. Noise has been incorporated to the system additively and multiplicatively. In order to study the above nonlinear optical (NLO) properties the doped dot has been subjected to a polarized monochromatic electromagnetic field. Effect of application of noise is nicely reflected through alteration of peak shift (blue/red) and variation of peak height (increase/decrease) of above NLO properties as temperature and pressure are varied. All such changes again sensitively depends on mode of application (additive/multiplicative) of noise. The remarkable influence of interplay between noise strength and its mode of application on the said profiles has also been addressed. The findings illuminate fascinating role played by noise in tuning above NLO properties of doped QD system under the active presence of both hydrostatic pressure and temperature.
Improved Denoising via Poisson Mixture Modeling of Image Sensor Noise.
Zhang, Jiachao; Hirakawa, Keigo
2017-04-01
This paper describes a study aimed at comparing the real image sensor noise distribution to the models of noise often assumed in image denoising designs. A quantile analysis in pixel, wavelet transform, and variance stabilization domains reveal that the tails of Poisson, signal-dependent Gaussian, and Poisson-Gaussian models are too short to capture real sensor noise behavior. A new Poisson mixture noise model is proposed to correct the mismatch of tail behavior. Based on the fact that noise model mismatch results in image denoising that undersmoothes real sensor data, we propose a mixture of Poisson denoising method to remove the denoising artifacts without affecting image details, such as edge and textures. Experiments with real sensor data verify that denoising for real image sensor data is indeed improved by this new technique.
Non-gaussianity in the strong regime of warm inflation
Moss, Ian G.; Yeomans, Timothy E-mail: timothy.yeomans@ncl.ac.uk
2011-08-01
The bispectrum of scalar mode density perturbations is analysed for the strong regime of warm inflationary models. This analysis generalises previous results by allowing damping terms in the inflaton equation of motion that are dependent on temperature. A significant amount of non-gaussianity emerges with constant (or local) non-linearity parameter f{sub NL} ∼ 20, in addition to the terms with non-constant f{sub NL} which are characteristic of warm inflation.
Okokon, Enembe Oku; Turunen, Anu W.; Ung-Lanki, Sari; Vartiainen, Anna-Kaisa; Tiittanen, Pekka; Lanki, Timo
2015-01-01
Exposure to road-traffic noise commonly engenders annoyance, the extent of which is determined by factors not fully understood. Our aim was to estimate the prevalence and determinants of road-traffic noise annoyance and noise sensitivity in the Finnish adult population, while comparing the perceptions of road-traffic noise to exhausts as environmental health problems. Using a questionnaire that yielded responses from 1112 randomly selected adult Finnish respondents, we estimated road-traffic noise- and exhausts-related perceived exposures, health-risk perceptions, and self-reported annoyance on five-point scales, while noise sensitivity estimates were based on four questions. Determinants of noise annoyance and sensitivity were investigated using multivariate binary logistic regression and linear regression models, respectively. High or extreme noise annoyance was reported by 17% of respondents. Noise sensitivity scores approximated a Gaussian distribution. Road-traffic noise and exhausts were, respectively, considered high or extreme population-health risks by 22% and 27% of respondents. Knowledge of health risks from traffic noise, OR: 2.04 (1.09–3.82) and noise sensitivity, OR: 1.07 (1.00–1.14) were positively associated with annoyance. Knowledge of health risks (p < 0.045) and positive environmental attitudes (p < 000) were associated with higher noise sensitivity. Age and sex were associated with annoyance and sensitivity only in bivariate models. A considerable proportion of Finnish adults are highly annoyed by road-traffic noise, and perceive it to be a significant health risk, almost comparable to traffic exhausts. There is no distinct noise-sensitive population subgroup. Knowledge of health risks of road-traffic noise, and attitudinal variables are associated with noise annoyance and sensitivity. PMID:26016432
Okokon, Enembe Oku; Turunen, Anu W; Ung-Lanki, Sari; Vartiainen, Anna-Kaisa; Tiittanen, Pekka; Lanki, Timo
2015-05-26
Exposure to road-traffic noise commonly engenders annoyance, the extent of which is determined by factors not fully understood. Our aim was to estimate the prevalence and determinants of road-traffic noise annoyance and noise sensitivity in the Finnish adult population, while comparing the perceptions of road-traffic noise to exhausts as environmental health problems. Using a questionnaire that yielded responses from 1112 randomly selected adult Finnish respondents, we estimated road-traffic noise- and exhausts-related perceived exposures, health-risk perceptions, and self-reported annoyance on five-point scales, while noise sensitivity estimates were based on four questions. Determinants of noise annoyance and sensitivity were investigated using multivariate binary logistic regression and linear regression models, respectively. High or extreme noise annoyance was reported by 17% of respondents. Noise sensitivity scores approximated a Gaussian distribution. Road-traffic noise and exhausts were, respectively, considered high or extreme population-health risks by 22% and 27% of respondents. Knowledge of health risks from traffic noise, OR: 2.04 (1.09-3.82) and noise sensitivity, OR: 1.07 (1.00-1.14) were positively associated with annoyance. Knowledge of health risks (p<0.045) and positive environmental attitudes (p<000) were associated with higher noise sensitivity. Age and sex were associated with annoyance and sensitivity only in bivariate models. A considerable proportion of Finnish adults are highly annoyed by road-traffic noise, and perceive it to be a significant health risk, almost comparable to traffic exhausts. There is no distinct noise-sensitive population subgroup. Knowledge of health risks of road-traffic noise, and attitudinal variables are associated with noise annoyance and sensitivity.
Airframe noise prediction evaluation
NASA Technical Reports Server (NTRS)
Yamamoto, Kingo J.; Donelson, Michael J.; Huang, Shumei C.; Joshi, Mahendra C.
1995-01-01
The objective of this study is to evaluate the accuracy and adequacy of current airframe noise prediction methods using available airframe noise measurements from tests of a narrow body transport (DC-9) and a wide body transport (DC-10) in addition to scale model test data. General features of the airframe noise from these aircraft and models are outlined. The results of the assessment of two airframe prediction methods, Fink's and Munson's methods, against flight test data of these aircraft and scale model wind tunnel test data are presented. These methods were extensively evaluated against measured data from several configurations including clean, slat deployed, landing gear-deployed, flap deployed, and landing configurations of both DC-9 and DC-10. They were also assessed against a limited number of configurations of scale models. The evaluation was conducted in terms of overall sound pressure level (OASPL), tone corrected perceived noise level (PNLT), and one-third-octave band sound pressure level (SPL).
Noise and Dynamical Pattern Selection
NASA Technical Reports Server (NTRS)
Kurtze, Douglas A.
1996-01-01
In pattern-forming systems, such as Rayleigh-Benard convection or directional solidification, a large number of linearly stable, patterned steady states exist when the basic, simple steady state is unstable. Which of these steady states will be realized in a given experiment appears to depend on unobservable details of the system's initial conditions. We show, however, that weak, Gaussian white noise drives such a system toward a preferred wave number which depends only on the system parameters and is independent of initial conditions. We give a prescription for calculating this wave number, analytically near the onset of instability and numerically otherwise.
NASA Astrophysics Data System (ADS)
Troncossi, M.; Di Sante, R.; Rivola, A.
2016-10-01
In the field of vibration qualification testing, random excitations are typically imposed on the tested system in terms of a power spectral density (PSD) profile. This is the one of the most popular ways to control the shaker or slip table for durability tests. However, these excitations (and the corresponding system responses) exhibit a Gaussian probability distribution, whereas not all real-life excitations are Gaussian, causing the response to be also non-Gaussian. In order to introduce non-Gaussian peaks, a further parameter, i.e., kurtosis, has to be controlled in addition to the PSD. However, depending on the specimen behaviour and input signal characteristics, the use of non-Gaussian excitations with high kurtosis and a given PSD does not automatically imply a non-Gaussian stress response. For an experimental investigation of these coupled features, suitable measurement methods need to be developed in order to estimate the stress amplitude response at critical failure locations and consequently evaluate the input signals most representative for real-life, non-Gaussian excitations. In this paper, a simple test rig with a notched cantilevered specimen was developed to measure the response and examine the kurtosis values in the case of stationary Gaussian, stationary non-Gaussian, and burst non-Gaussian excitation signals. The laser Doppler vibrometry technique was used in this type of test for the first time, in order to estimate the specimen stress amplitude response as proportional to the differential displacement measured at the notch section ends. A method based on the use of measurements using accelerometers to correct for the occasional signal dropouts occurring during the experiment is described. The results demonstrate the ability of the test procedure to evaluate the output signal features and therefore to select the most appropriate input signal for the fatigue test.
Troncossi, M; Di Sante, R; Rivola, A
2016-10-01
In the field of vibration qualification testing, random excitations are typically imposed on the tested system in terms of a power spectral density (PSD) profile. This is the one of the most popular ways to control the shaker or slip table for durability tests. However, these excitations (and the corresponding system responses) exhibit a Gaussian probability distribution, whereas not all real-life excitations are Gaussian, causing the response to be also non-Gaussian. In order to introduce non-Gaussian peaks, a further parameter, i.e., kurtosis, has to be controlled in addition to the PSD. However, depending on the specimen behaviour and input signal characteristics, the use of non-Gaussian excitations with high kurtosis and a given PSD does not automatically imply a non-Gaussian stress response. For an experimental investigation of these coupled features, suitable measurement methods need to be developed in order to estimate the stress amplitude response at critical failure locations and consequently evaluate the input signals most representative for real-life, non-Gaussian excitations. In this paper, a simple test rig with a notched cantilevered specimen was developed to measure the response and examine the kurtosis values in the case of stationary Gaussian, stationary non-Gaussian, and burst non-Gaussian excitation signals. The laser Doppler vibrometry technique was used in this type of test for the first time, in order to estimate the specimen stress amplitude response as proportional to the differential displacement measured at the notch section ends. A method based on the use of measurements using accelerometers to correct for the occasional signal dropouts occurring during the experiment is described. The results demonstrate the ability of the test procedure to evaluate the output signal features and therefore to select the most appropriate input signal for the fatigue test.
Asymmetric Laguerre-Gaussian beams
NASA Astrophysics Data System (ADS)
Kovalev, A. A.; Kotlyar, V. V.; Porfirev, A. P.
2016-06-01
We introduce a family of asymmetric Laguerre-Gaussian (aLG) laser beams. The beams have been derived via a complex-valued shift of conventional LG beams in the Cartesian plane. While propagating in a uniform medium, the first bright ring of the aLG beam becomes less asymmetric and the energy is redistributed toward peripheral diffraction rings. The projection of the orbital angular momentum (OAM) onto the optical axis is calculated. The OAM is shown to grow quadratically with increasing asymmetry parameter of the aLG beam, which equals the ratio of the shift to the waist radius. Conditions for the OAM becoming equal to the topological charge have been derived. For aLG beams with zero radial index, we have deduced an expression to define the intensity maximum coordinates and shown the crescent-shaped intensity pattern to rotate during propagation. Results of the experimental generation and rotation of aLG beams agree well with theoretical predictions.
Low-Resistant Band-Passing Noise and Its Dynamical Effects
NASA Astrophysics Data System (ADS)
Bai, Zhan-Wu
2007-07-01
We propose an n-order noise, which is realized by driving an n-order linear differential equation with a Gaussian white noise. The time-derivative noise is a low-resistant band-passing noise. If the derivative noise is regarded as a thermal one, the system has a vanishing effective friction and it should induce ballistic diffusion of a free particle at long times. The simulation method for the generalized Langevin equation driven by the n-order noise is discussed systematically. The features of three-order derivative noises are presented when they are applied to a ratchet system.
Noise and mental performance: personality attributes and noise sensitivity.
Belojevic, G; Jakovljevic, B; Slepcevic, V
2003-01-01
The contradictory and confusing results in noise research on humans may partly be due to individual differences between the subjects participating in different studies. This review is based on a twelve year research on the role of neuroticism, extroversion and subjective noise sensitivity during mental work in noisy environment. Neurotic persons might show enhanced "arousability" i.e. their arousal level increases more in stress. Additional unfavorable factors for neurotics are worrying and anxiety, which might prevent them coping successfully with noise, or some other stressors during mental performance. In numerous experiments introverts have showed higher sensitivity to noise during mental performance compared to extroverts, while extroverts often cope with a boring task even by requesting short periods of noise during performance. Correlation analyses have regularly revealed a highly significant negative relation between extroversion and noise annoyance during mental processing. Numerous studies have shown that people with high noise sensitivity may be prevented from achieving the same work results as other people in noisy environment, thus leading to psychosomatic, neurotic or other difficulties. Positive relation between noise annoyance and subjective noise sensitivity might be very strong. Our results have shown, after matching with the results of other relevant studies, that more stable personality, with extroversive tendencies and with a relatively lower subjective noise sensitivity measured with standard questionnaires, may be expected to better adapt to noise during mental performance, compared to people with opposite personality traits.
Noise Analysis on Graphene Devices via Scanning Noise Microscopy
NASA Astrophysics Data System (ADS)
Cho, Duckhyung; Sung, Moon Gyu; Lee, Hyungwoo; Heo, Kwang; Byun, Kyung-Eun; Kim, Taekyeong; Seo, David H.; Seo, Sunae; Hong, Seunghun
2013-03-01
Until now, the studies about low-frequency noises in electronic devices have mostly relied on the scaling behaviour analysis of current noise measured from multiple devices with different resistance values. However, the fabrication of such multiple devices for noise analysis is a labor-intensive and time-consuming work. Herein, we developed the scanning noise microscopy (SNM) method for nanoscale noise analysis of electronic devices, which allowed us to measure the scaling behaviour of electrical current noises in a graphene-strip-based device. In this method, a conductive atomic force microscopy probe made a direct contact on the graphene strip channel in the device to measure the noise spectra through it. The SNM method enabled the investigation of the noise scaling behaviour using only a single device. In addition, the nanoscale noise map was obtained, which allowed us to study the effect of structural defects on the noise characteristics of the graphene strip channel. Our method should be a powerful strategy for nanoscale noise analysis and play a significant role in basic research on nanoscale devices.
Quantum bit commitment under Gaussian constraints
NASA Astrophysics Data System (ADS)
Mandilara, Aikaterini; Cerf, Nicolas J.
2012-06-01
Quantum bit commitment has long been known to be impossible. Nevertheless, just as in the classical case, imposing certain constraints on the power of the parties may enable the construction of asymptotically secure protocols. Here, we introduce a quantum bit commitment protocol and prove that it is asymptotically secure if cheating is restricted to Gaussian operations. This protocol exploits continuous-variable quantum optical carriers, for which such a Gaussian constraint is experimentally relevant as the high optical nonlinearity needed to effect deterministic non-Gaussian cheating is inaccessible.
Motion compensation and noise tolerance in phase-shifting digital in-line holography.
Stenner, Michael D; Neifeld, Mark A
2006-05-15
We present a technique for phase-shifting digital in-line holography which compensates for lateral object motion. By collecting two frames of interference between object and reference fields with identical reference phase, one can estimate the lateral motion that occurred between frames using the cross-correlation. We also describe a very general linear framework for phase-shifting holographic reconstruction which minimizes additive white Gaussian noise (AWGN) for an arbitrary set of reference field amplitudes and phases. We analyze the technique's sensitivity to noise (AWGN, quantization, and shot), errors in the reference fields, errors in motion estimation, resolution, and depth of field. We also present experimental motion-compensated images achieving the expected resolution.
Gaussian measures of entanglement versus negativities: Ordering of two-mode Gaussian states
Adesso, Gerardo; Illuminati, Fabrizio
2005-09-15
We study the entanglement of general (pure or mixed) two-mode Gaussian states of continuous-variable systems by comparing the two available classes of computable measures of entanglement: entropy-inspired Gaussian convex-roof measures and positive partial transposition-inspired measures (negativity and logarithmic negativity). We first review the formalism of Gaussian measures of entanglement, adopting the framework introduced in M. M. Wolf et al., Phys. Rev. A 69, 052320 (2004), where the Gaussian entanglement of formation was defined. We compute explicitly Gaussian measures of entanglement for two important families of nonsymmetric two-mode Gaussian state: namely, the states of extremal (maximal and minimal) negativities at fixed global and local purities, introduced in G. Adesso et al., Phys. Rev. Lett. 92, 087901 (2004). This analysis allows us to compare the different orderings induced on the set of entangled two-mode Gaussian states by the negativities and by the Gaussian measures of entanglement. We find that in a certain range of values of the global and local purities (characterizing the covariance matrix of the corresponding extremal states), states of minimum negativity can have more Gaussian entanglement of formation than states of maximum negativity. Consequently, Gaussian measures and negativities are definitely inequivalent measures of entanglement on nonsymmetric two-mode Gaussian states, even when restricted to a class of extremal states. On the other hand, the two families of entanglement measures are completely equivalent on symmetric states, for which the Gaussian entanglement of formation coincides with the true entanglement of formation. Finally, we show that the inequivalence between the two families of continuous-variable entanglement measures is somehow limited. Namely, we rigorously prove that, at fixed negativities, the Gaussian measures of entanglement are bounded from below. Moreover, we provide some strong evidence suggesting that they
Probabilistic density function method for nonlinear dynamical systems driven by colored noise
NASA Astrophysics Data System (ADS)
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.
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.
The Airframe Noise Reduction Challenge
NASA Technical Reports Server (NTRS)
Lockhard, David P.; Lilley, Geoffrey M.
2004-01-01
The NASA goal of reducing external aircraft noise by 10 dB in the near-term presents the acoustics community with an enormous challenge. This report identifies technologies with the greatest potential to reduce airframe noise. Acoustic and aerodynamic effects will be discussed, along with the likelihood of industry accepting and implementing the different technologies. We investigate the lower bound, defined as noise generated by an aircraft modified with a virtual retrofit capable of eliminating all noise associated with the high lift system and landing gear. However, the airframe noise of an aircraft in this 'clean' configuration would only be about 8 dB quieter on approach than current civil transports. To achieve the NASA goal of 10 dB noise reduction will require that additional noise sources be addressed. Research shows that energy in the turbulent boundary layer of a wing is scattered as it crosses trailing edge. Noise generated by scattering is the dominant noise mechanism on an aircraft flying in the clean configuration. Eliminating scattering would require changes to much of the aircraft, and practical reduction devices have yet to receive serious attention. Evidence suggests that to meet NASA goals in civil aviation noise reduction, we need to employ emerging technologies and improve landing procedures; modified landing patterns and zoning restrictions could help alleviate aircraft noise in communities close to airports.
Enhanced optical flow field of left ventricular motion using quasi-Gaussian DCT filter.
Riyadi, Slamet; Mustafa, Mohd Marzuki; Hussain, Aini; Maskon, Oteh; Nor, Ika Faizura Mohd
2011-01-01
Left ventricular motion estimation is very important for diagnosing cardiac abnormality. One of the popular techniques, optical flow technique, promises useful results for motion quantification. However, optical flow technique often failed to provide smooth vector field due to the complexity of cardiac motion and the presence of speckle noise. This chapter proposed a new filtering technique, called quasi-Gaussian discrete cosine transform (QGDCT)-based filter, to enhance the optical flow field for myocardial motion estimation. Even though Gaussian filter and DCT concept have been implemented in other previous researches, this filter introduces a different approach of Gaussian filter model based on high frequency properties of cosine function. The QGDCT is a customized quasi discrete Gaussian filter in which its coefficients are derived from a selected two-dimensional DCT. This filter was implemented before and after the computation of optical flow to reduce the speckle noise and to improve the flow field smoothness, respectively. The algorithm was first validated on synthetic echocardiography image that simulates a contracting myocardium motion. Subsequently, this method was also implemented on clinical echocardiography images. To evaluate the performance of the technique, several quantitative measurements such as magnitude error, angular error, and standard error of measurement are computed and analyzed. The final motion estimation results were in good agreement with the physician manual interpretation.
Xiao, Zhu; Havyarimana, Vincent; Li, Tong; Wang, Dong
2016-01-01
In this paper, a novel nonlinear framework of smoothing method, non-Gaussian delayed particle smoother (nGDPS), is proposed, which enables vehicle state estimation (VSE) with high accuracy taking into account the non-Gaussianity of the measurement and process noises. Within the proposed method, the multivariate Student’s t-distribution is adopted in order to compute the probability distribution function (PDF) related to the process and measurement noises, which are assumed to be non-Gaussian distributed. A computation approach based on Ensemble Kalman Filter (EnKF) is designed to cope with the mean and the covariance matrix of the proposal non-Gaussian distribution. A delayed Gibbs sampling algorithm, which incorporates smoothing of the sampled trajectories over a fixed-delay, is proposed to deal with the sample degeneracy of particles. The performance is investigated based on the real-world data, which is collected by low-cost on-board vehicle sensors. The comparison study based on the real-world experiments and the statistical analysis demonstrates that the proposed nGDPS has significant improvement on the vehicle state accuracy and outperforms the existing filtering and smoothing methods. PMID:27187405
Stability criterion for Gaussian pulse propagation through negative index materials
Joseph, Ancemma; Porsezian, K.
2010-02-15
We analyze the dynamics of propagation of a Gaussian light pulse through a medium having a negative index of refraction employing the recently reported projection operator technique. The governing modified nonlinear Schroedinger equation, obtained by taking into account the Drude dispersive model, is expressed in terms of the parameters of Gaussian pulse, called collective variables, such as width, amplitude, chirp, and phase. This approach yields a system of ordinary differential equations for the evolution of all the pulse parameters. We demonstrate the dependence of stability of the fixed-point solutions of these ordinary differential equations on the linear and nonlinear dispersion parameters. In addition, we validate the analytical approach numerically utilizing the method of split-step Fourier transform.
Near-unit-fidelity entanglement distribution scheme using Gaussian communication
Praxmeyer, Ludmila; Loock, Peter van
2010-06-15
We show how to distribute with percentage success probabilities almost perfectly entangled qubit memory pairs over repeater channel segments of the order of the optical attenuation distance. In addition to some weak, dispersive light-matter interactions, only Gaussian state transmissions and measurements are needed for this scheme. Our protocol outperforms the existing coherent-state-based schemes for entanglement distribution, even those using error-free non-Gaussian measurements. This is achieved through two innovations: First, optical squeezed states are utilized instead of coherent states. Second, the amplitudes of the bright signal pulses are reamplified at each repeater station. This latter variation is a strategy reminiscent of classical repeaters and would be impossible in single-photon-based schemes.
Galaxy bias and primordial non-Gaussianity
Assassi, Valentin; Baumann, Daniel; Schmidt, Fabian E-mail: D.D.Baumann@uva.nl
2015-12-01
We present a systematic study of galaxy biasing in the presence of primordial non-Gaussianity. For a large class of non-Gaussian initial conditions, we define a general bias expansion and prove that it is closed under renormalization, thereby showing that the basis of operators in the expansion is complete. We then study the effects of primordial non-Gaussianity on the statistics of galaxies. We show that the equivalence principle enforces a relation between the scale-dependent bias in the galaxy power spectrum and that in the dipolar part of the bispectrum. This provides a powerful consistency check to confirm the primordial origin of any observed scale-dependent bias. Finally, we also discuss the imprints of anisotropic non-Gaussianity as motivated by recent studies of higher-spin fields during inflation.
Non-Gaussianities in New Ekpyrotic Cosmology.
Buchbinder, Evgeny I; Khoury, Justin; Ovrut, Burt A
2008-05-02
The new ekpyrotic model is an alternative scenario of the early Universe which relies on a phase of slow contraction before the big bang. We calculate the 3-point and 4-point correlation functions of primordial density perturbations and find a generically large non-Gaussian signal, just below the current sensitivity level of cosmic microwave background experiments. This is in contrast with slow-roll inflation, which predicts negligible non-Gaussianity. The model is also distinguishable from alternative inflationary scenarios that can yield large non-Gaussianity, such as Dirac-Born-Infeld inflation and the simplest curvatonlike models, through the shape dependence of the correlation functions. Non-Gaussianity therefore provides a distinguishing and testable prediction of New Ekpyrotic Cosmology.
Improved Gaussian Beam-Scattering Algorithm
NASA Technical Reports Server (NTRS)
Lock, James A.
1995-01-01
The localized model of the beam-shape coefficients for Gaussian beam-scattering theory by a spherical particle provides a great simplification in the numerical implementation of the theory. We derive an alternative form for the localized coefficients that is more convenient for computer computations and that provides physical insight into the details of the scattering process. We construct a FORTRAN program for Gaussian beam scattering with the localized model and compare its computer run time on a personal computer with that of a traditional Mie scattering program and with three other published methods for computing Gaussian beam scattering. We show that the analytical form of the beam-shape coefficients makes evident the fact that the excitation rate of morphology-dependent resonances is greatly enhanced for far off-axis incidence of the Gaussian beam.
Lecture Notes on Non-Gaussianity
NASA Astrophysics Data System (ADS)
Byrnes, Christian T.
We discuss how primordial non-Gaussianity of the curvature perturbation helps to constrain models of the early universe. Observations are consistent with Gaussian initial conditions, compatible with the predictions of the simplest models of inflation. Deviations are constrained to be at the sub percent level, constraining alternative models such as those with multiple fields, non-canonical kinetic terms or breaking the slow-roll conditions. We introduce some of the most important models of inflation which generate non-Gaussian perturbations and provide practical tools on how to calculate the three-point correlation function for a popular class of non-Gaussian models. The current state of the field is summarised and an outlook is given.
Optimal cloning of mixed Gaussian states
Guta, Madalin; Matsumoto, Keiji
2006-09-15
We construct the optimal one to two cloning transformation for the family of displaced thermal equilibrium states of a harmonic oscillator, with a fixed and known temperature. The transformation is Gaussian and it is optimal with respect to the figure of merit based on the joint output state and norm distance. The proof of the result is based on the equivalence between the optimal cloning problem and that of optimal amplification of Gaussian states which is then reduced to an optimization problem for diagonal states of a quantum oscillator. A key concept in finding the optimum is that of stochastic ordering which plays a similar role in the purely classical problem of Gaussian cloning. The result is then extended to the case of n to m cloning of mixed Gaussian states.
Li, Derong; Lv, Xiaohua; Bowlan, Pamela; Du, Rui; Zeng, Shaoqun; Luo, Qingming
2009-09-14
The evolution of the frequency chirp of a laser pulse inside a classical pulse compressor is very different for plane waves and Gaussian beams, although after propagating through the last (4th) dispersive element, the two models give the same results. In this paper, we have analyzed the evolution of the frequency chirp of Gaussian pulses and beams using a method which directly obtains the spectral phase acquired by the compressor. We found the spatiotemporal couplings in the phase to be the fundamental reason for the difference in the frequency chirp acquired by a Gaussian beam and a plane wave. When the Gaussian beam propagates, an additional frequency chirp will be introduced if any spatiotemporal couplings (i.e. angular dispersion, spatial chirp or pulse front tilt) are present. However, if there are no couplings present, the chirp of the Gaussian beam is the same as that of a plane wave. When the Gaussian beam is well collimated, the introduced frequency chirp predicted by the plane wave and Gaussian beam models are in closer agreement. This work improves our understanding of pulse compressors and should be helpful for optimizing dispersion compensation schemes in many applications of femtosecond laser pulses.
Solenoidal filtering of volumetric velocity measurements using Gaussian process regression
NASA Astrophysics Data System (ADS)
Azijli, Iliass; Dwight, Richard P.
2015-11-01
Volumetric velocity measurements of incompressible flows contain spurious divergence due to measurement noise, despite mass conservation dictating that the velocity field must be divergence-free (solenoidal). We investigate the use of Gaussian process regression to filter spurious divergence, returning analytically solenoidal velocity fields. We denote the filter solenoidal Gaussian process regression (SGPR) and formulate it within the Bayesian framework to allow a natural inclusion of measurement uncertainty. To enable efficient handling of large data sets on regular and near-regular grids, we propose a solution procedure that exploits the Toeplitz structure of the system matrix. We apply SGPR to two synthetic and two experimental test cases and compare it with two other recently proposed solenoidal filters. For the synthetic test cases, we find that SGPR consistently returns more accurate velocity, vorticity and pressure fields. From the experimental test cases, we draw two important conclusions. Firstly, it is found that including an accurate model for the local measurement uncertainty further improves the accuracy of the velocity field reconstructed with SGPR. Secondly, it is found that all solenoidal filters result in an improved reconstruction of the pressure field, as verified with microphone measurements. The results obtained with SGPR are insensitive to correlation length, demonstrating the robustness of the filter to its parameters.
NASA Technical Reports Server (NTRS)
Mashiku, Alinda; Garrison, James L.; Carpenter, J. Russell
2012-01-01
The tracking of space objects requires frequent and accurate monitoring for collision avoidance. As even collision events with very low probability are important, accurate prediction of collisions require the representation of the full probability density function (PDF) of the random orbit state. Through representing the full PDF of the orbit state for orbit maintenance and collision avoidance, we can take advantage of the statistical information present in the heavy tailed distributions, more accurately representing the orbit states with low probability. The classical methods of orbit determination (i.e. Kalman Filter and its derivatives) provide state estimates based on only the second moments of the state and measurement errors that are captured by assuming a Gaussian distribution. Although the measurement errors can be accurately assumed to have a Gaussian distribution, errors with a non-Gaussian distribution could arise during propagation between observations. Moreover, unmodeled dynamics in the orbit model could introduce non-Gaussian errors into the process noise. A Particle Filter (PF) is proposed as a nonlinear filtering technique that is capable of propagating and estimating a more complete representation of the state distribution as an accurate approximation of a full PDF. The PF uses Monte Carlo runs to generate particles that approximate the full PDF representation. The PF is applied in the estimation and propagation of a highly eccentric orbit and the results are compared to the Extended Kalman Filter and Splitting Gaussian Mixture algorithms to demonstrate its proficiency.
Xiao, Changyan; Staring, Marius; Wang, Yaonan; Shamonin, Denis P; Stoel, Berend C
2013-01-01
The intensity or gray-level derivatives have been widely used in image segmentation and enhancement. Conventional derivative filters often suffer from an undesired merging of adjacent objects because of their intrinsic usage of an inappropriately broad Gaussian kernel; as a result, neighboring structures cannot be properly resolved. To avoid this problem, we propose to replace the low-level Gaussian kernel with a bi-Gaussian function, which allows independent selection of scales in the foreground and background. By selecting a narrow neighborhood for the background with regard to the foreground, the proposed method will reduce interference from adjacent objects simultaneously preserving the ability of intraregion smoothing. Our idea is inspired by a comparative analysis of existing line filters, in which several traditional methods, including the vesselness, gradient flux, and medialness models, are integrated into a uniform framework. The comparison subsequently aids in understanding the principles of different filtering kernels, which is also a contribution of this paper. Based on some axiomatic scale-space assumptions, the full representation of our bi-Gaussian kernel is deduced. The popular γ-normalization scheme for multiscale integration is extended to the bi-Gaussian operators. Finally, combined with a parameter-free shape estimation scheme, a derivative filter is developed for the typical applications of curvilinear structure detection and vasculature image enhancement. It is verified in experiments using synthetic and real data that the proposed method outperforms several conventional filters in separating closely located objects and being robust to noise.
Spectral shaping for non-Gaussian source spectra in optical coherence tomography
NASA Astrophysics Data System (ADS)
Tripathi, Renu; Nassif, Nader; Nelson, J. Stuart; Park, Boris Hyle; de Boer, Johannes F.
2002-03-01
We present a digital spectral shaping technique to reduce the sidelobes (ringing) of the axial point-spread function in optical coherence tomography for non-Gaussian-shaped source spectra. The spectra of two superluminescent diodes were combined to generate a spectrum with significant modulation. Images of onion cells demonstrate the improved image quality in a turbid biological sample. A quantitative analysis of the accompanying penalty in signal-to-noise ratio is given.
Gaussian-Beam Laser-Resonator Program
NASA Technical Reports Server (NTRS)
Cross, Patricia L.; Bair, Clayton H.; Barnes, Norman
1989-01-01
Gaussian Beam Laser Resonator Program models laser resonators by use of Gaussian-beam-propagation techniques. Used to determine radii of beams as functions of position in laser resonators. Algorithm used in program has three major components. First, ray-transfer matrix for laser resonator must be calculated. Next, initial parameters of beam calculated. Finally, propagation of beam through optical elements computed. Written in Microsoft FORTRAN (Version 4.01).
Ultrasonic transducer with Gaussian radial pressure distribution
NASA Technical Reports Server (NTRS)
Claus, R. O.; Zerwekh, P. S. (Inventor)
1984-01-01
An ultrasonic transducer that produces an output that is a symmetrical function comprises a piezoelectric crystal with several concentric ring electrodes on one side of the crystal. A resistor network applies different amplitudes of an ac source to each of the several electrodes. A plot of the different amplitudes from the outermost electrode to the innermost electrode is the first half of a Gaussian function. Consequently, the output of the crystal from the side opposite the electrodes has a Gaussian profile.
Generating functionals and Gaussian approximations for interruptible delay reactions
NASA Astrophysics Data System (ADS)
Brett, Tobias; Galla, Tobias
2015-10-01
We develop a generating functional description of the dynamics of non-Markovian individual-based systems in which delay reactions can be terminated before completion. This generalizes previous work in which a path-integral approach was applied to dynamics in which delay reactions complete with certainty. We construct a more widely applicable theory, and from it we derive Gaussian approximations of the dynamics, valid in the limit of large, but finite, population sizes. As an application of our theory we study predator-prey models with delay dynamics due to gestation or lag periods to reach the reproductive age. In particular, we focus on the effects of delay on noise-induced cycles.
Input-output Gaussian channels: theory and application
NASA Astrophysics Data System (ADS)
Tufarelli, Tommaso; Retzker, Alex; Plenio, Martin B.; Serafini, Alessio
2012-09-01
Setting off from the classic input-output formalism, we develop a theoretical framework to characterize the Gaussian quantum channels relating the initial correlations of an open bosonic system to those of properly identified output modes. We then proceed to apply our formalism to the case of quantum harmonic oscillators, such as the motional degrees of freedom of trapped ions or nanomechanical oscillators, interacting with travelling electromagnetic modes through cavity fields and subject to external white noise. We thus determine the degree of squeezing that can be transferred from an intra-cavity oscillator to light and show that the intra-cavity squeezing can be transformed into distributed optical entanglement if one can access both output fields of a two-sided cavity.
Gaussian particle flow implementation of PHD filter
NASA Astrophysics Data System (ADS)
Zhao, Lingling; Wang, Junjie; Li, Yunpeng; Coates, Mark J.
2016-05-01
Particle filter and Gaussian mixture implementations of random finite set filters have been proposed to tackle the issue of jointly estimating the number of targets and their states. The Gaussian mixture PHD (GM-PHD) filter has a closed-form expression for the PHD for linear and Gaussian target models, and extensions using the extended Kalman filter or unscented Kalman Filter have been developed to allow the GM-PHD filter to accommodate mildly nonlinear dynamics. Errors resulting from linearization or model mismatch are unavoidable. A particle filter implementation of the PHD filter (PF-PHD) is more suitable for nonlinear and non-Gaussian target models. The particle filter implementations are much more computationally expensive and performance can suffer when the proposal distribution is not a good match to the posterior. In this paper, we propose a novel implementation of the PHD filter named the Gaussian particle flow PHD filter (GPF-PHD). It employs a bank of particle flow filters to approximate the PHD; these play the same role as the Gaussian components in the GM-PHD filter but are better suited to non-linear dynamics and measurement equations. Using the particle flow filter allows the GPF-PHD filter to migrate particles to the dense regions of the posterior, which leads to higher eﬃciency than the PF-PHD. We explore the performance of the new algorithm through numerical simulations.
Non-Gaussianity and intermittency in an ensemble of Gaussian fields
NASA Astrophysics Data System (ADS)
Wilczek, Michael
2016-12-01
Motivated by the need to capture statistical properties of turbulent systems in simple, analytically tractable models, an ensemble of Gaussian sub-ensembles with varying properties of the correlation function such as variance and length scale is investigated. The ensemble statistics naturally exhibit non-Gaussianity and intermittency. Due to the simplicity of Gaussian random fields, many explicit results can be obtained analytically, revealing the origin of non-Gaussianity in this framework. Potential applications of the proposed model ensemble for the description of non-equilibrium statistical mechanics of complex turbulent systems are briefly discussed.
Uncertainty in perception and the Hierarchical Gaussian Filter.
Mathys, Christoph D; Lomakina, Ekaterina I; Daunizeau, Jean; Iglesias, Sandra; Brodersen, Kay H; Friston, Karl J; Stephan, Klaas E
2014-01-01
In its full sense, perception rests on an agent's model of how its sensory input comes about and the inferences it draws based on this model. These inferences are necessarily uncertain. Here, we illustrate how the Hierarchical Gaussian Filter (HGF) offers a principled and generic way to deal with the several forms that uncertainty in perception takes. The HGF is a recent derivation of one-step update equations from Bayesian principles that rests on a hierarchical generative model of the environment and its (in)stability. It is computationally highly efficient, allows for online estimates of hidden states, and has found numerous applications to experimental data from human subjects. In this paper, we generalize previous descriptions of the HGF and its account of perceptual uncertainty. First, we explicitly formulate the extension of the HGF's hierarchy to any number of levels; second, we discuss how various forms of uncertainty are accommodated by the minimization of variational free energy as encoded in the update equations; third, we combine the HGF with decision models and demonstrate the inversion of this combination; finally, we report a simulation study that compared four optimization methods for inverting the HGF/decision model combination at different noise levels. These four methods (Nelder-Mead simplex algorithm, Gaussian process-based global optimization, variational Bayes and Markov chain Monte Carlo sampling) all performed well even under considerable noise, with variational Bayes offering the best combination of efficiency and informativeness of inference. Our results demonstrate that the HGF provides a principled, flexible, and efficient-but at the same time intuitive-framework for the resolution of perceptual uncertainty in behaving agents.
Thermal Noise Behavior of the Bridge Circuit
2000-03-01
is Gaussian white noise. 37 References [1] C.A. Desoer and E.S. Kuh, Basic Circuit Theory, McGraw-Hill, New York, 1969. [2] E. Polak and E. Wong...86, no. 5, pp. 702-710, 1952. [7] L.O. Chua, C.A. Desoer , and E.S. Kuh, Linear and Nonlinear Circuits, McGraw-Hill, New York, 1987. See in
Non-propulsive aerodynamic noise
NASA Astrophysics Data System (ADS)
Willshire, William L., Jr.; Tracy, Maureen B.
1992-04-01
In the first part of the paper, the contribution of airframe noise to total aircraft noise on approach is assessed for a large current technology transport and for the same airframe powered with bypass ratio 10 engines with an additional 5 dB noise suppression applied to the fan and turbine noise sources. The airframe noise of the envisioned advanced subsonic transport is 2 EPNdB less than the largest contributor to the total aircraft noise, the fan inlet. The noise impact of the airframe noise, as measured by noise contour area, is 1/4 that of fan noise. Further fan noise reduction efforts should not view airframe noise as an absolute noise floor. In the second part of the paper, the results from one recent cavity noise wind tunnel experiment is reported. A cavity of dimensions 11.25 in. (28.58 cm) long, 2.5 in. (6.35 cm) wide, and variable depth was tested in the Mach number range of .20 through .90. Reynolds number varied from 5 to 100 million per foot (16 to 328 million per meter). The 1/d ratio was varied from 4.4 to 20.0. The model was tested at yaw angles from 0 to 15 degrees. In general, the deeper the cavity, the greater the amplitude of the acoustic tones. Reynolds number appeared to have little effect on acoustic tone amplitudes. Tone amplitude and bandwidth changed with Mach number. The effect of yaw on acoustic tones varied with Reynolds number, Mach number, 1/h, and mode number. At Mach number 0.90, increased yaw shifted the tone frequencies of the higher modal frequencies to lower frequencies. As cavity depth decreased, the effect of yaw decreased.
Phase Noise in Photonic Phased-Array Antenna Systems
NASA Technical Reports Server (NTRS)
Logan, Ronald T., Jr.; Maleki, Lute
1998-01-01
The total noise of a phased-array antenna system employing a photonic feed network is analyzed using a model for the individual component noise including both additive and multiplicative equivalent noise generators.
Noise in Neural Networks: Thresholds, Hysteresis, and Neuromodulation of Signal-To-Noise
NASA Astrophysics Data System (ADS)
Keeler, James D.; Pichler, Elgar E.; Ross, John
1989-03-01
We study a neural-network model including Gaussian noise, higher-order neuronal interactions, and neuromodulation. For a first-order network, there is a threshold in the noise level (phase transition) above which the network displays only disorganized behavior and critical slowing down near the noise threshold. The network can tolerate more noise if it has higher-order feedback interactions, which also lead to hysteresis and multistability in the network dynamics. The signal-to-noise ratio can be adjusted in a biological neural network by neuromodulators such as norepinephrine. Comparisons are made to experimental results and further investigations are suggested to test the effects of hysteresis and neuromodulation in pattern recognition and learning. We propose that norepinephrine may ``quench'' the neural patterns of activity to enhance the ability to learn details.
Noise-induced compensation for postural hypotension in primary autonomic failure.
Yamamoto, Yoshiharu; Hidaka, Ichiro; Iso-o, Noriko; Komai, Akira; Soma, Rika; Kwak, Shin
2002-07-26
Noise can have a beneficial effect on sensory neurological systems, enhancing detection of small afferent signals and thereby improve efferent neural responses. We hypothesized whether a similar mechanism would facilitate impaired neural transmission associated with neurological disease, and tested whether addition of external noise to baroreceptor signaling could improve blunted autonomic efferent responses to a postural challenge in patients with primary autonomic failure (PAF). Five PAF patients were tested, one in duplicate and another triplicate, for their transient responses of heart rate (measured from electrocardiographic RR intervals; RRIs) and systolic (SBP) and diastolic (DBP) blood pressures to either 30 degrees or 60 degrees head-up tilt, with and without continuous application of beat-to-beat Gaussian white noise to the carotid sinus baroreceptors. Also, the effects of noise were compared with those by a continuous positive pressure applied to the carotid sinus baroreceptors. The data were fit to a first order model to evaluate the speed (by the time constant; tau) and the magnitudes (by the steady state gains; Gs) of RRI and blood pressure responses. The PAF patients exhibited marked drops in SBP and DBP and a blunted increase in heart rate upon transition from a supine to a head-up position. Addition of noise, not the continuous positive pressure, to the arterial baroreceptors significantly (P<0.05) increased the G in RRI and diminished the Gs in SBP and DBP, though the time courses (taus) of both the RRI and blood pressure responses were unaffected. The addition of external noise to baroreceptor signaling ameliorated the marked postural hypotension seen in patients with PAF.
Synthetic ECG Generation and Bayesian Filtering Using a Gaussian Wave-Based Dynamical Model
Sayadi, Omid; Shamsollahi, Mohammad B.; Clifford, Gari D.
2011-01-01
In this paper, we describe a Gaussian wave-based state space to model the temporal dynamics of electrocardiogram (ECG) signals. It is shown that this model may be effectively used for generating synthetic ECGs as well as separate characteristic waves (CWs) such as the atrial and ventricular complexes. The model uses separate state variables for each CW, i.e. P, QRS and T, and hence is capable of generating individual synthetic CWs as well as realistic ECG signals. The model is therefore useful for generating arrhythmias. Simulations of sinus bradycardia, sinus tachycardia, ventricular flutter, atrial fibrillation, and ventricular tachycardia are presented. In addition, discrete versions of the equations are presented for a model-based Bayesian framework for denoising. This framework, together with an extended Kalman filter (EKF) and extended Kalman smoother (EKS), were used for denoising the ECG for both normal rhythms and arrhythmias. For evaluating the denoising performance the signal-to-noise ratio (SNR) improvement of the filter outputs and clinical parameter stability were studied. The results demonstrate superiority over a wide range of input SNRs, achieving a maximum 12.7 dB improvement. Results indicate that preventing clinically relevant distortion of the ECG is sensitive to the number of model parameters. Models are presented which do not exhibit such distortions. The approach presented in this paper may therefore serve as an effective framework for synthetic ECG generation and model-based filtering of noisy ECG recordings. PMID:20720288
Bayesian soft X-ray tomography using non-stationary Gaussian Processes
Li, Dong; Svensson, J.; Thomsen, H.; Werner, A.; Wolf, R.; Medina, F.
2013-08-15
In this study, a Bayesian based non-stationary Gaussian Process (GP) method for the inference of soft X-ray emissivity distribution along with its associated uncertainties has been developed. For the investigation of equilibrium condition and fast magnetohydrodynamic behaviors in nuclear fusion plasmas, it is of importance to infer, especially in the plasma center, spatially resolved soft X-ray profiles from a limited number of noisy line integral measurements. For this ill-posed inversion problem, Bayesian probability theory can provide a posterior probability distribution over all possible solutions under given model assumptions. Specifically, the use of a non-stationary GP to model the emission allows the model to adapt to the varying length scales of the underlying diffusion process. In contrast to other conventional methods, the prior regularization is realized in a probability form which enhances the capability of uncertainty analysis, in consequence, scientists who concern the reliability of their results will benefit from it. Under the assumption of normally distributed noise, the posterior distribution evaluated at a discrete number of points becomes a multivariate normal distribution whose mean and covariance are analytically available, making inversions and calculation of uncertainty fast. Additionally, the hyper-parameters embedded in the model assumption can be optimized through a Bayesian Occam's Razor formalism and thereby automatically adjust the model complexity. This method is shown to produce convincing reconstructions and good agreements with independently calculated results from the Maximum Entropy and Equilibrium-Based Iterative Tomography Algorithm methods.
Synthetic ECG generation and Bayesian filtering using a Gaussian wave-based dynamical model.
Sayadi, Omid; Shamsollahi, Mohammad B; Clifford, Gari D
2010-10-01
In this paper, we describe a Gaussian wave-based state space to model the temporal dynamics of electrocardiogram (ECG) signals. It is shown that this model may be effectively used for generating synthetic ECGs as well as separate characteristic waves (CWs) such as the atrial and ventricular complexes. The model uses separate state variables for each CW, i.e. P, QRS and T, and hence is capable of generating individual synthetic CWs as well as realistic ECG signals. The model is therefore useful for generating arrhythmias. Simulations of sinus bradycardia, sinus tachycardia, ventricular flutter, atrial fibrillation and ventricular tachycardia are presented. In addition, discrete versions of the equations are presented for a model-based Bayesian framework for denoising. This framework, together with an extended Kalman filter and extended Kalman smoother, was used for denoising the ECG for both normal rhythms and arrhythmias. For evaluating the denoising performance, the signal-to-noise ratio (SNR) improvement of the filter outputs and clinical parameter stability were studied. The results demonstrate superiority over a wide range of input SNRs, achieving a maximum 12.7 dB improvement. Results indicate that preventing clinically relevant distortion of the ECG is sensitive to the number of model parameters. Models are presented which do not exhibit such distortions. The approach presented in this paper may therefore serve as an effective framework for synthetic ECG generation and model-based filtering of noisy ECG recordings.
NASA Technical Reports Server (NTRS)
Misoda, J.; Magliozzi, B.
1973-01-01
The development is described of improved, low noise level fan and pump concepts for the space shuttle. In addition, a set of noise design criteria for small fans and pumps was derived. The concepts and criteria were created by obtaining Apollo hardware test data to correlate and modify existing noise estimating procedures. A set of space shuttle selection criteria was used to determine preliminary fan and pump concepts. These concepts were tested and modified to obtain noise sources and characteristics which yield the design criteria and quiet, efficient space shuttle fan and pump concepts.
NASA Astrophysics Data System (ADS)
Samanta, Sudeshna; Raychaudhuri, A. K.; Zhong, Xing; Gupta, A.
2015-11-01
We have carried out an extensive investigation on the resistance fluctuations (noise) in an epitaxial thin film of VO2 encompassing the metal-insulator transition (MIT) region to investigate the dynamic phase coexistence of metal and insulating phases. Both flicker noise as well as the Nyquist noise (thermal noise) were measured. The experiments showed that flicker noise, which has a 1 /f spectral power dependence, evolves with temperature in the transition region following the evolution of the phase fractions and is governed by activated kinetics. Importantly, closer to the insulating end of the transition, when the metallic phase fraction is low, the magnitude of the noise shows an anomaly and a strong non-Gaussian component of noise develops. In this region, the local electron temperature (as measured through the Nyquist noise thermometry) shows a deviation from the equilibrium bath temperature. It is proposed that this behavior arises due to current crowding where a substantial amount of the current is carried through well separated small metallic islands leading to a dynamic correlated current path redistribution and an enhanced effective local current density. This leads to a non-Gaussian component to the resistance fluctuation and an associated local deviation of the electron temperature from the bath. Our experiment establishes that phase coexistence leads to a strong inhomogeneity in the region of MIT that makes the current transport strongly inhomogeneous and correlated.
Wang, Lu; Xu, Lisheng; Zhao, Dazhe; Yao, Yang; Song, Dan
2015-04-01
Because arterial pulse waves contain vital information related to the condition of the cardiovascular system, considerable attention has been devoted to the study of pulse waves in recent years. Accurate acquisition is essential to investigate arterial pulse waves. However, at the stage of developing equipment for acquiring and analyzing arterial pulse waves, specific pulse signals may be unavailable for debugging and evaluating the system under development. To produce test signals that reflect specific physiological conditions, in this paper, an arterial pulse wave generator has been designed and implemented using a field programmable gate array (FPGA), which can produce the desired pulse waves according to the feature points set by users. To reconstruct a periodic pulse wave from the given feature points, a method known as piecewise Gaussian-cosine fitting is also proposed in this paper. Using a test database that contains four types of typical pulse waves with each type containing 25 pulse wave signals, the maximum residual error of each sampling point of the fitted pulse wave in comparison with the real pulse wave is within 8%. In addition, the function for adding baseline drift and three types of noises is integrated into the developed system because the baseline occasionally wanders, and noise needs to be added for testing the performance of the designed circuits and the analysis algorithms. The proposed arterial pulse wave generator can be considered as a special signal generator with a simple structure, low cost and compact size, which can also provide flexible solutions for many other related research purposes.
Control of absolute negative mobility via noise recycling procedure
NASA Astrophysics Data System (ADS)
Zeng, C. H.; Wang, H.; Qing, S.; Hu, J. H.; Li, K. Z.
2012-10-01
Absolute negative mobility (ANM) is investigated in a spatially-periodic symmetric system under the influence of noise consisting of the superposition of a white Gaussian noise with the same noise delayed by time τ. The effects of the noise intensity σ, the time delay τ and feedback intensity ɛ in the noise recycling are discussed. It is found that the noise intensity σ and time delay τ can induce the phenomenon of ANM, while the feedback intensity ɛ can not induce it. This phenomenon of ANM can be tested in the setup consisting of a resistively and capacitively shunted Josephson junction device by using a vertical cavity surface emitting laser to generate the noise recycling procedure.
Advanced Study for Active Noise Control in Aircraft (ASANCA)
NASA Technical Reports Server (NTRS)
Borchers, Ingo U.; Emborg, Urban; Sollo, Antonio; Waterman, Elly H.; Paillard, Jacques; Larsen, Peter N.; Venet, Gerard; Goeransson, Peter; Martin, Vincent
1992-01-01
Aircraft interior noise and vibration measurements are included in this paper from ground and flight tests. In addition, related initial noise calculations with and without active noise control are conducted. The results obtained to date indicate that active noise control may be an effective means for reducing the critical low frequency aircraft noise.
Stochastic bifurcation in a model of love with colored noise
NASA Astrophysics Data System (ADS)
Yue, Xiaokui; Dai, Honghua; Yuan, Jianping
2015-07-01
In this paper, we wish to examine the stochastic bifurcation induced by multiplicative Gaussian colored noise in a dynamical model of love where the random factor is used to describe the complexity and unpredictability of psychological systems. First, the dynamics in deterministic love-triangle model are considered briefly including equilibrium points and their stability, chaotic behaviors and chaotic attractors. Then, the influences of Gaussian colored noise with different parameters are explored such as the phase plots, top Lyapunov exponents, stationary probability density function (PDF) and stochastic bifurcation. The stochastic P-bifurcation through a qualitative change of the stationary PDF will be observed and bifurcation diagram on parameter plane of correlation time and noise intensity is presented to find the bifurcation behaviors in detail. Finally, the top Lyapunov exponent is computed to determine the D-bifurcation when the noise intensity achieves to a critical value. By comparison, we find there is no connection between two kinds of stochastic bifurcation.
NASA Astrophysics Data System (ADS)
Niu, Sen; Ke, Jun
2016-10-01
In this paper, block-based compressive ultra low-light-level imaging (BCU-imaging) is studied. Objects are divided into blocks. Features, or linear combinations of block pixels, instead of pixels, are measured for each block to improve system measurement SNR and thus object reconstructions. Thermal noise and shot noise are discussed for object reconstruction. The former is modeled as Gaussian noise. The latter is modeled as Poisson noise. Linear Wiener operator and linearized iterative Bregman algorithm are used to reconstruct objects from measurements corrupted by thermal noise. SPIRAL algorithm is used to reconstruct object from measurements with shot noise. Linear Wiener operator is also studied for measurements with shot noise, because Poisson noise is similar to Gaussian noise at large signal level and feature values are large enough to make this assumption feasible. Root mean square error (RMSE) is used to quantify system reconstruction quality.
NASA Astrophysics Data System (ADS)
Yoo, Youngjin; Lee, SeongDeok; Choe, Wonhee; Kim, Chang-Yong
2007-02-01
Digital images captured from CMOS image sensors suffer Gaussian noise and impulsive noise. To efficiently reduce the noise in Image Signal Processor (ISP), we analyze noise feature for imaging pipeline of ISP where noise reduction algorithm is performed. The Gaussian noise reduction and impulsive noise reduction method are proposed for proper ISP implementation in Bayer domain. The proposed method takes advantage of the analyzed noise feature to calculate noise reduction filter coefficients. Thus, noise is adaptively reduced according to the scene environment. Since noise is amplified and characteristic of noise varies while the image sensor signal undergoes several image processing steps, it is better to remove noise in earlier stage on imaging pipeline of ISP. Thus, noise reduction is carried out in Bayer domain on imaging pipeline of ISP. The method is tested on imaging pipeline of ISP and images captured from Samsung 2M CMOS image sensor test module. The experimental results show that the proposed method removes noise while effectively preserves edges.
Molecular Code Division Multiple Access: Gaussian Mixture Modeling
NASA Astrophysics Data System (ADS)
Zamiri-Jafarian, Yeganeh
Communications between nano-devices is an emerging research field in nanotechnology. Molecular Communication (MC), which is a bio-inspired paradigm, is a promising technique for communication in nano-network. In MC, molecules are administered to exchange information among nano-devices. Due to the nature of molecular signals, traditional communication methods can't be directly applied to the MC framework. The objective of this thesis is to present novel diffusion-based MC methods when multi nano-devices communicate with each other in the same environment. A new channel model and detection technique, along with a molecular-based access method, are proposed in here for communication between asynchronous users. In this work, the received molecular signal is modeled as a Gaussian mixture distribution when the MC system undergoes Brownian noise and inter-symbol interference (ISI). This novel approach demonstrates a suitable modeling for diffusion-based MC system. Using the proposed Gaussian mixture model, a simple receiver is designed by minimizing the error probability. To determine an optimum detection threshold, an iterative algorithm is derived which minimizes a linear approximation of the error probability function. Also, a memory-based receiver is proposed to improve the performance of the MC system by considering previously detected symbols in obtaining the threshold value. Numerical evaluations reveal that theoretical analysis of the bit error rate (BER) performance based on the Gaussian mixture model match simulation results very closely. Furthermore, in this thesis, molecular code division multiple access (MCDMA) is proposed to overcome the inter-user interference (IUI) caused by asynchronous users communicating in a shared propagation environment. Based on the selected molecular codes, a chip detection scheme with an adaptable threshold value is developed for the MCDMA system when the proposed Gaussian mixture model is considered. Results indicate that the
Planck 2015 results. XVII. Constraints on primordial non-Gaussianity
NASA Astrophysics Data System (ADS)
Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Arroja, F.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Ballardini, M.; Banday, A. J.; Barreiro, R. B.; Bartolo, N.; Basak, S.; Battaner, E.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bock, J. J.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Boulanger, F.; Bucher, M.; Burigana, C.; Butler, R. C.; Calabrese, E.; Cardoso, J.-F.; Catalano, A.; Challinor, A.; Chamballu, A.; Chiang, H. C.; Christensen, P. R.; Church, S.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Désert, F.-X.; Diego, J. M.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Ducout, A.; Dupac, X.; Efstathiou, G.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Fergusson, J.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Frejsel, A.; Galeotta, S.; Galli, S.; Ganga, K.; Gauthier, C.; Ghosh, T.; Giard, M.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J. E.; Hamann, J.; Hansen, F. K.; Hanson, D.; Harrison, D. L.; Heavens, A.; Helou, G.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huang, Z.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kim, J.; Kisner, T. S.; Knoche, J.; Kunz, M.; Kurki-Suonio, H.; Lacasa, F.; Lagache, G.; Lähteenmäki, A.; Lamarre, J.-M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Leonardi, R.; Lesgourgues, J.; Levrier, F.; Lewis, A.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maggio, G.; Maino, D.; Mandolesi, N.; Mangilli, A.; Marinucci, D.; Maris, M.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; McGehee, P.; Meinhold, P. R.; Melchiorri, A.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Moss, A.; Münchmeyer, M.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Pasian, F.; Patanchon, G.; Peiris, H. V.; Perdereau, O.; Perotto, L.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Popa, L.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Racine, B.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Rossetti, M.; Roudier, G.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Santos, D.; Savelainen, M.; Savini, G.; Scott, D.; Seiffert, M. D.; Shellard, E. P. S.; Shiraishi, M.; Smith, K.; Spencer, L. D.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sunyaev, R.; Sutter, P.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Troja, A.; Tucci, M.; Tuovinen, J.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Wehus, I. K.; Yvon, D.; Zacchei, A.; Zonca, A.
2016-09-01
The Planck full mission cosmic microwave background (CMB) temperature and E-mode polarization maps are analysed to obtain constraints on primordial non-Gaussianity (NG). Using three classes of optimal bispectrum estimators - separable template-fitting (KSW), binned, and modal - we obtain consistent values for the primordial local, equilateral, and orthogonal bispectrum amplitudes, quoting as our final result from temperature alone ƒlocalNL = 2.5 ± 5.7, ƒequilNL= -16 ± 70, , and ƒorthoNL = -34 ± 32 (68% CL, statistical). Combining temperature and polarization data we obtain ƒlocalNL = 0.8 ± 5.0, ƒequilNL= -4 ± 43, and ƒorthoNL = -26 ± 21 (68% CL, statistical). The results are based on comprehensive cross-validation of these estimators on Gaussian and non-Gaussian simulations, are stable across component separation techniques, pass an extensive suite of tests, and are consistent with estimators based on measuring the Minkowski functionals of the CMB. The effect of time-domain de-glitching systematics on the bispectrum is negligible. In spite of these test outcomes we conservatively label the results including polarization data as preliminary, owing to a known mismatch of the noise model in simulations and the data. Beyond estimates of individual shape amplitudes, we present model-independent, three-dimensional reconstructions of the Planck CMB bispectrum and derive constraints on early universe scenarios that generate primordial NG, including general single-field models of inflation, axion inflation, initial state modifications, models producing parity-violating tensor bispectra, and directionally dependent vector models. We present a wide survey of scale-dependent feature and resonance models, accounting for the "look elsewhere" effect in estimating the statistical significance of features. We also look for isocurvature NG, and find no signal, but we obtain constraints that improve significantly with the inclusion of polarization. The primordial
Nonparaxial multi-Gaussian beam models and measurement models for phased array transducers.
Zhao, Xinyu; Gang, Tie
2009-01-01
A nonparaxial multi-Gaussian beam model is proposed in order to overcome the limitation that paraxial Gaussian beam models lose accuracy in simulating the beam steering behavior of phased array transducers. Using this nonparaxial multi-Gaussian beam model, the focusing and steering sound fields generated by an ultrasonic linear phased array transducer are calculated and compared with the corresponding results obtained by paraxial multi-Gaussian beam model and more exact Rayleigh-Sommerfeld integral model. In addition, with help of this novel nonparaxial method, an ultrasonic measurement model is provided to investigate the sensitivity of linear phased array transducers versus steering angles. Also the comparisons of model predictions with experimental results are presented to certify the accuracy of this provided measurement model.
Dynamic generation of Ince-Gaussian modes with a digital micromirror device
Ren, Yu-Xuan; Fang, Zhao-Xiang; Chen, Yue; Lu, Rong-De; Gong, Lei; Huang, Kun
2015-04-07
Ince-Gaussian (IG) beam with elliptical profile, as a connection between Hermite-Gaussian (HG) and Laguerre-Gaussian (LG) beams, has showed unique advantages in some applications such as quantum entanglement and optical micromanipulation. However, its dynamic generation with high switching frequency is still challenging. Here, we experimentally reported the quick generation of Ince-Gaussian beam by using a digital micro-mirror device (DMD), which has the highest switching frequency of 5.2 kHz in principle. The configurable properties of DMD allow us to observe the quasi-smooth variation from LG (with ellipticity ε=0) to IG and HG (ε=∞) beam. This approach might pave a path to high-speed quantum communication in terms of IG beam. Additionally, the characterized axial plane intensity distribution exhibits a 3D mould potentially being employed for optical micromanipulation.
Non-Gaussianity and large-scale structure in a two-field inflationary model
Tseliakhovich, Dmitriy; Hirata, Christopher
2010-08-15
Single-field inflationary models predict nearly Gaussian initial conditions, and hence a detection of non-Gaussianity would be a signature of the more complex inflationary scenarios. In this paper we study the effect on the cosmic microwave background and on large-scale structure from primordial non-Gaussianity in a two-field inflationary model in which both the inflaton and curvaton contribute to the density perturbations. We show that in addition to the previously described enhancement of the galaxy bias on large scales, this setup results in large-scale stochasticity. We provide joint constraints on the local non-Gaussianity parameter f-tilde{sub NL} and the ratio {xi} of the amplitude of primordial perturbations due to the inflaton and curvaton using WMAP and Sloan Digital Sky Survey data.
Non-Gaussianity and Large Scale Structure in a two-field Inflationary model
Tseliakhovich, D.; Slosar, A.; Hirata, C.
2010-08-30
Single-field inflationary models predict nearly Gaussian initial conditions, and hence a detection of non-Gaussianity would be a signature of the more complex inflationary scenarios. In this paper we study the effect on the cosmic microwave background and on large-scale structure from primordial non-Gaussianity in a two-field inflationary model in which both the inflaton and curvaton contribute to the density perturbations. We show that in addition to the previously described enhancement of the galaxy bias on large scales, this setup results in large-scale stochasticity. We provide joint constraints on the local non-Gaussianity parameter f*{sub NL} and the ratio {zeta} of the amplitude of primordial perturbations due to the inflaton and curvaton using WMAP and Sloan Digital Sky Survey data.
From particle counting to Gaussian tomography
NASA Astrophysics Data System (ADS)
Parthasarathy, K. R.; Sengupta, Ritabrata
2015-12-01
The momentum and position observables in an n-mode boson Fock space Γ(ℂn) have the whole real line ℝ as their spectrum. But the total number operator N has a discrete spectrum ℤ+ = {0, 1, 2,…}. An n-mode Gaussian state in Γ(ℂn) is completely determined by the mean values of momentum and position observables and their covariance matrix which together constitute a family of n(2n + 3) real parameters. Starting with N and its unitary conjugates by the Weyl displacement operators and operators from a representation of the symplectic group Sp(2n) in Γ(ℂn), we construct n(2n + 3) observables with spectrum ℤ+ but whose expectation values in a Gaussian state determine all its mean and covariance parameters. Thus measurements of discrete-valued observables enable the tomography of the underlying Gaussian state and it can be done by using five one-mode and four two-mode Gaussian symplectic gates in single and pair mode wires of Γ(ℂn) = Γ(ℂ)⊗n. Thus the tomography protocol admits a simple description in a language similar to circuits in quantum computation theory. Such a Gaussian tomography applied to outputs of a Gaussian channel with coherent input states permit a tomography of the channel parameters. However, in our procedure the number of counting measurements exceeds the number of channel parameters slightly. Presently, it is not clear whether a more efficient method exists for reducing this tomographic complexity. As a byproduct of our approach an elementary derivation of the probability generating function of N in a Gaussian state is given. In many cases the distribution turns out to be infinitely divisible and its underlying Lévy measure can be obtained. However, we are unable to derive the exact distribution in all cases. Whether this property of infinite divisibility holds in general is left as an open problem.
Inflation: Long Wavelength Modes and Non-Gaussianities
NASA Astrophysics Data System (ADS)
Deutsch, Anne-Sylvie; Shandera, Sarah; Bonga, Béatrice; Brahma, Suddhasattwa
2015-04-01
For our work, we assume that the whole inflation process can be separated into two main regimes; one described by a field Φ (the inflaton field) interacting weakly with Σ (in the hidden sector), and another one, at energies Λ2 --> 1 and lower, where the field Σ has been integrated out and we are in a single field Φ model with a small sound speed cs. During the two-field regime, coupling between short and long wavelength can generate non-equilateral non-Gaussianities. Upon imposing some conditions, such a generation of non-Gaussianities is not allowed in a single field regime. Our objective is to include the contribution of these long and short wavelength couplings in the single effective field model. For that, we derived an effective Lagrangian and studied the influence of each interaction term on the physics of inflation. We saw that both terms would lead to a similar sound speed and non-Gaussianities. Open questions remain concerning the effect of the splitting, which we are currently investigating. One could expect a different background evolution of the theory, or additional terms in the effective Lagrangian for the fluctuations Leff . Another possibility would be to also consider a modified initial state.
NON-GAUSSIAN SCATTER IN CLUSTER SCALING RELATIONS
Shaw, Laurie D.; Holder, Gilbert P.; Dudley, Jonathan
2010-06-10
We investigate the impact of non-Gaussian scatter in the cluster mass-observable scaling relation on the mass and redshift distribution of clusters detected by wide area surveys. We parameterize non-Gaussian scatter by incorporating the third and fourth moments (skewness and kurtosis) into the distribution P(M {sub obs}|M). We demonstrate that the effect of the higher order moments becomes important when the product of the standard deviation of P(M {sub obs}|M) and the slope of the mass function is greater than unity. For high scatter mass indicators it is therefore necessary for the survey, limiting mass threshold to be less than 10{sup 14} h {sup -1} M {sub sun}, to prevent the skewness from having a significant impact on the observed number counts, particularly at high redshift. We also show that an unknown level of non-Gaussianity in the scatter is equivalent to an additional uncertainty on the variance in P(M {sub obs}|M) and thus may limit the constraints that can be placed on {sigma}{sub 8} and the dark energy equation of state parameter w.
Hamiltonian approach to Ehrenfest expectation values and Gaussian quantum states.
Bonet-Luz, Esther; Tronci, Cesare
2016-05-01
The dynamics of quantum expectation values is considered in a geometric setting. First, expectation values of the canonical observables are shown to be equivariant momentum maps for the action of the Heisenberg group on quantum states. Then, the Hamiltonian structure of Ehrenfest's theorem is shown to be Lie-Poisson for a semidirect-product Lie group, named the Ehrenfest group. The underlying Poisson structure produces classical and quantum mechanics as special limit cases. In addition, quantum dynamics is expressed in the frame of the expectation values, in which the latter undergo canonical Hamiltonian motion. In the case of Gaussian states, expectation values dynamics couples to second-order moments, which also enjoy a momentum map structure. Eventually, Gaussian states are shown to possess a Lie-Poisson structure associated with another semidirect-product group, which is called the Jacobi group. This structure produces the energy-conserving variant of a class of Gaussian moment models that have previously appeared in the chemical physics literature.
Relativistic corrections and non-Gaussianity in radio continuum surveys
Maartens, Roy; Zhao, Gong-Bo; Bacon, David; Koyama, Kazuya; Raccanelli, Alvise E-mail: Gong-bo.Zhao@port.ac.uk E-mail: Kazuya.Koyama@port.ac.uk
2013-02-01
Forthcoming radio continuum surveys will cover large volumes of the observable Universe and will reach to high redshifts, making them potentially powerful probes of dark energy, modified gravity and non-Gaussianity. We consider the continuum surveys with LOFAR, WSRT and ASKAP, and examples of continuum surveys with the SKA. We extend recent work on these surveys by including redshift space distortions and lensing convergence in the radio source auto-correlation. In addition we compute the general relativistic (GR) corrections to the angular power spectrum. These GR corrections to the standard Newtonian analysis of the power spectrum become significant on scales near and beyond the Hubble scale at each redshift. We find that the GR corrections are at most percent-level in LOFAR, WODAN and EMU surveys, but they can produce O(10%) changes for high enough sensitivity SKA continuum surveys. The signal is however dominated by cosmic variance, and multiple-tracer techniques will be needed to overcome this problem. The GR corrections are suppressed in continuum surveys because of the integration over redshift — we expect that GR corrections will be enhanced for future SKA HI surveys in which the source redshifts will be known. We also provide predictions for the angular power spectra in the case where the primordial perturbations have local non-Gaussianity. We find that non-Gaussianity dominates over GR corrections, and rises above cosmic variance when f{sub NL}∼>5 for SKA continuum surveys.
Hamiltonian approach to Ehrenfest expectation values and Gaussian quantum states
NASA Astrophysics Data System (ADS)
Bonet-Luz, Esther; Tronci, Cesare
2016-05-01
The dynamics of quantum expectation values is considered in a geometric setting. First, expectation values of the canonical observables are shown to be equivariant momentum maps for the action of the Heisenberg group on quantum states. Then, the Hamiltonian structure of Ehrenfest's theorem is shown to be Lie-Poisson for a semidirect-product Lie group, named the Ehrenfest group. The underlying Poisson structure produces classical and quantum mechanics as special limit cases. In addition, quantum dynamics is expressed in the frame of the expectation values, in which the latter undergo canonical Hamiltonian motion. In the case of Gaussian states, expectation values dynamics couples to second-order moments, which also enjoy a momentum map structure. Eventually, Gaussian states are shown to possess a Lie-Poisson structure associated with another semidirect-product group, which is called the Jacobi group. This structure produces the energy-conserving variant of a class of Gaussian moment models that have previously appeared in the chemical physics literature.
NASA Astrophysics Data System (ADS)
Xu, Shaoping; Hu, Lingyan; Yang, Xiaohui
2016-01-01
The performance of conventional denoising algorithms is usually controlled by one or several parameters whose optimal settings depend on the contents of the processed images and the characteristics of the noises. Among these parameters, noise level is a fundamental parameter that is always assumed to be known by most of the existing denoising algorithms (so-called nonblind denoising algorithms), which largely limits the applicability of these nonblind denoising algorithms in many applications. Moreover, these nonblind algorithms do not always achieve the best denoised images in visual quality even when fed with the actual noise level parameter. To address these shortcomings, in this paper we propose a new quality-aware features-based noise level estimator (NLE), which consists of quality-aware features extraction and optimal noise level parameter prediction. First, considering that image local contrast features convey important structural information that is closely related to image perceptual quality, we utilize the marginal statistics of two local contrast operators, i.e., the gradient magnitude and the Laplacian of Gaussian (LOG), to extract quality-aware features. The proposed quality-aware features have very low computational complexity, making them well suited for time-constrained applications. Then we propose a learning-based framework where the noise level parameter is estimated based on the quality-aware features. Based on the proposed NLE, we develop a blind block matching and three-dimensional filtering (BBM3D) denoising algorithm which is capable of effectively removing additive white Gaussian noise, even coupled with impulse noise. The noise level parameter of the BBM3D algorithm is automatically tuned according to the quality-aware features, guaranteeing the best performance. As such, the classical block matching and three-dimensional algorithm can be transformed into a blind one in an unsupervised manner. Experimental results demonstrate that the
Signal-to-Noise Ratio Analysis of a Phase-Sensitive Voltmeter for Electrical Impedance Tomography.
Murphy, Ethan K; Takhti, Mohammad; Skinner, Joseph; Halter, Ryan J; Odame, Kofi
2017-04-01
In this paper, thorough analysis along with mathematical derivations of the matched filter for a voltmeter used in electrical impedance tomography systems are presented. The effect of the random noise in the system prior to the matched filter, generated by other components, are considered. Employing the presented equations allow system/circuit designers to find the maximum tolerable noise prior to the matched filter that leads to the target signal-to-noise ratio (SNR) of the voltmeter, without having to over-design internal components. A practical model was developed that should fall within 2 dB and 5 dB of the median SNR measurements of signal amplitude and phase, respectively. In order to validate our claims, simulation and experimental measurements have been performed with an analog-to-digital converter (ADC) followed by a digital matched filter, while the noise of the whole system was modeled as the input referred at the ADC input. The input signal was contaminated by a known value of additive white Gaussian noise (AWGN) noise, and the noise level was swept from 3% to 75% of the least significant bit (LSB) of the ADC. Differences between experimental and both simulated and analytical SNR values were less than 0.59 and 0.35 dB for RMS values ≥ 20% of an LSB and less than 1.45 and 2.58 dB for RMS values < 20% of an LSB for the amplitude and phase, respectively. Overall, this study provides a practical model for circuit designers in EIT, and a more accurate error analysis that was previously missing in EIT literature.
NASA Astrophysics Data System (ADS)
Griesbach, J.; Wetterer, C.; Sydney, P.; Gerber, J.
Photometric processing of non-resolved Electro-Optical (EO) images has commonly required the use of dark and flat calibration frames that are obtained to correct for charge coupled device (CCD) dark (thermal) noise and CCD quantum efficiency/optical path vignetting effects respectively. It is necessary to account/calibrate for these effects so that the brightness of objects of interest (e.g. stars or resident space objects (RSOs)) may be measured in a consistent manner across the CCD field of view. Detected objects typically require further calibration using aperture photometry to compensate for sky background (shot noise). For this, annuluses are measured around each detected object whose contained pixels are used to estimate an average background level that is subtracted from the detected pixel measurements. In a new photometric calibration software tool developed for AFRL/RD, called Efficient Photometry In-Frame Calibration (EPIC), an automated background normalization technique is proposed that eliminates the requirement to capture dark and flat calibration images. The proposed technique simultaneously corrects for dark noise, shot noise, and CCD quantum efficiency/optical path vignetting effects. With this, a constant detection threshold may be applied for constant false alarm rate (CFAR) object detection without the need for aperture photometry corrections. The detected pixels may be simply summed (without further correction) for an accurate instrumental magnitude estimate. The noise distribution associated with each pixel is assumed to be sampled from a Poisson distribution. Since Poisson distributed data closely resembles Gaussian data for parameterized means greater than 10, the data may be corrected by applying bias subtraction and standard-deviation division. EPIC performs automated background normalization on rate-tracked satellite images using the following technique. A deck of approximately 50-100 images is combined by performing an independent median
NASA Technical Reports Server (NTRS)
Biswas, Rahul; Blackburn, Lindy L.; Cao, Junwei; Essick, Reed; Hodge, Kari Alison; Katsavounidis, Erotokritos; Kim, Kyungmin; Young-Min, Kim; Le Bigot, Eric-Olivier; Lee, Chang-Hwan; Oh, John J.; Oh, Sang Hoon; Son, Edwin J.; Vaulin, Ruslan; Wang, Xiaoge; Ye, Tao
2014-01-01
The sensitivity of searches for astrophysical transients in data from the Laser Interferometer Gravitationalwave Observatory (LIGO) is generally limited by the presence of transient, non-Gaussian noise artifacts, which occur at a high-enough rate such that accidental coincidence across multiple detectors is non-negligible. Furthermore, non-Gaussian noise artifacts typically dominate over the background contributed from stationary noise. These "glitches" can easily be confused for transient gravitational-wave signals, and their robust identification and removal will help any search for astrophysical gravitational-waves. We apply Machine Learning Algorithms (MLAs) to the problem, using data from auxiliary channels within the LIGO detectors that monitor degrees of freedom unaffected by astrophysical signals. Terrestrial noise sources may manifest characteristic disturbances in these auxiliary channels, inducing non-trivial correlations with glitches in the gravitational-wave data. The number of auxiliary-channel parameters describing these disturbances may also be extremely large; high dimensionality is an area where MLAs are particularly well-suited. We demonstrate the feasibility and applicability of three very different MLAs: Artificial Neural Networks, Support Vector Machines, and Random Forests. These classifiers identify and remove a substantial fraction of the glitches present in two very different data sets: four weeks of LIGO's fourth science run and one week of LIGO's sixth science run. We observe that all three algorithms agree on which events are glitches to within 10% for the sixth science run data, and support this by showing that the different optimization criteria used by each classifier generate the same decision surface, based on a likelihood-ratio statistic. Furthermore, we find that all classifiers obtain similar limiting performance, suggesting that most of the useful information currently contained in the auxiliary channel parameters we extract
Hydraulic conductivity fields: Gaussian or not?
NASA Astrophysics Data System (ADS)
Meerschaert, Mark M.; Dogan, Mine; Dam, Remke L.; Hyndman, David W.; Benson, David A.
2013-08-01
Hydraulic conductivity (K) fields are used to parameterize groundwater flow and transport models. Numerical simulations require a detailed representation of the K field, synthesized to interpolate between available data. Several recent studies introduced high-resolution K data (HRK) at the Macro Dispersion Experiment (MADE) site, and used ground-penetrating radar (GPR) to delineate the main structural features of the aquifer. This paper describes a statistical analysis of these data, and the implications for K field modeling in alluvial aquifers. Two striking observations have emerged from this analysis. The first is that a simple fractional difference filter can have a profound effect on data histograms, organizing non-Gaussian ln K data into a coherent distribution. The second is that using GPR facies allows us to reproduce the significantly non-Gaussian shape seen in real HRK data profiles, using a simulated Gaussian ln K field in each facies. This illuminates a current controversy in the literature, between those who favor Gaussian ln K models, and those who observe non-Gaussian ln K fields. Both camps are correct, but at different scales.
Temperature modes for nonlinear Gaussian beams.
Myers, Matthew R; Soneson, Joshua E
2009-07-01
In assessing the influence of nonlinear acoustic propagation on thermal bioeffects, approximate methods for quickly estimating the temperature rise as operational parameters are varied can be very useful. This paper provides a formula for the transient temperature rise associated with nonlinear propagation of Gaussian beams. The pressure amplitudes for the Gaussian modes can be obtained rapidly using a method previously published for simulating nonlinear propagation of Gaussian beams. The temperature-mode series shows that the nth temperature mode generated by nonlinear propagation, when normalized by the fundamental, is weaker than the nth heat-rate mode (also normalized by the fundamental in the heat-rate series) by a factor of log(n)/n, where n is the mode number. Predictions of temperature rise and thermal dose were found to be in close agreement with full, finite-difference calculations of the pressure fields, temperature rise, and thermal dose. Applications to non-Gaussian beams were made by fitting the main lobe of the significant modes to Gaussian functions.
Hydraulic Conductivity Fields: Gaussian or Not?
Meerschaert, Mark M; Dogan, Mine; Van Dam, Remke L; Hyndman, David W; Benson, David A
2013-08-01
Hydraulic conductivity (K) fields are used to parameterize groundwater flow and transport models. Numerical simulations require a detailed representation of the K field, synthesized to interpolate between available data. Several recent studies introduced high resolution K data (HRK) at the Macro Dispersion Experiment (MADE) site, and used ground-penetrating radar (GPR) to delineate the main structural features of the aquifer. This paper describes a statistical analysis of these data, and the implications for K field modeling in alluvial aquifers. Two striking observations have emerged from this analysis. The first is that a simple fractional difference filter can have a profound effect on data histograms, organizing non-Gaussian ln K data into a coherent distribution. The second is that using GPR facies allows us to reproduce the significantly non-Gaussian shape seen in real HRK data profiles, using a simulated Gaussian ln K field in each facies. This illuminates a current controversy in the literature, between those who favor Gaussian ln K models, and those who observe non-Gaussian ln K fields. Both camps are correct, but at different scales.
Comparison of Gaussian and super Gaussian laser beams for addressing atomic qubits
NASA Astrophysics Data System (ADS)
Gillen-Christandl, Katharina; Gillen, Glen D.; Piotrowicz, M. J.; Saffman, M.
2016-05-01
We study the fidelity of single-qubit quantum gates performed with two-frequency laser fields that have a Gaussian or super Gaussian spatial mode. Numerical simulations are used to account for imperfections arising from atomic motion in an optical trap, spatially varying Stark shifts of the trapping and control beams, and transverse and axial misalignment of the control beams. Numerical results that account for the three-dimensional distribution of control light show that a super Gaussian mode with intensity I˜ e^{-2(r/w_0)^n} provides reduced sensitivity to atomic motion and beam misalignment. Choosing a super Gaussian with n=6 the decay time of finite temperature Rabi oscillations can be increased by a factor of 60 compared to an n=2 Gaussian beam, while reducing crosstalk to neighboring qubit sites.
Lagae, Ares; Lefebvre, Sylvain; Dutré, Philip
2011-08-01
We have recently proposed a new procedural noise function, Gabor noise, which offers a combination of properties not found in the existing noise functions. In this paper, we present three significant improvements to Gabor noise: 1) an isotropic kernel for Gabor noise, which speeds up isotropic Gabor noise with a factor of roughly two, 2) an error analysis of Gabor noise, which relates the kernel truncation radius to the relative error of the noise, and 3) spatially varying Gabor noise, which enables spatial variation of all noise parameters. These improvements make Gabor noise an even more attractive alternative for the existing noise functions.
NASA Astrophysics Data System (ADS)
Ganguly, Jayanta; Saha, Surajit; Bera, Aindrila; Ghosh, Manas
2017-03-01
We study the profiles of electro-optic effect (EOE) and third-order nonlinear optical susceptibility (TONOS) of impurity doped GaAs quantum dots (QDs) under the combined influence of hydrostatic pressure (HP) and temperature (T) taking into account the presence of Gaussian white noise. Noise has been introduced to the system additively and multiplicatively. The doped dot has been subjected to a polarized monochromatic electromagnetic field. Effect of application of noise is elegantly reflected through prominent change of peak shift (blue/red) and variation of peak height (increase/ıdecrease) of above nonlinear optical (NLO) properties as temperature and pressure are varied over a range. Interestingly, all such changes subtly depend on mode of application (additive/multiplicative) of noise. The noteworthy influence of the interplay between noise strength and its mode of application on the said NLO properties has also been critically scrutinized. The findings highlight remarkable role played by noise in tuning above NLO properties of doped QD system under the prominent presence of both hydrostatic pressure and temperature.
Optimal application of Morrison's iterative noise removal for deconvolution. Appendices
NASA Technical Reports Server (NTRS)
Ioup, George E.; Ioup, Juliette W.
1987-01-01
Morrison's iterative method of noise removal, or Morrison's smoothing, is applied in a simulation to noise-added data sets of various noise levels to determine its optimum use. Morrison's smoothing is applied for noise removal alone, and for noise removal prior to deconvolution. For the latter, an accurate method is analyzed to provide confidence in the optimization. The method consists of convolving the data with an inverse filter calculated by taking the inverse discrete Fourier transform of the reciprocal of the transform of the response of the system. Various length filters are calculated for the narrow and wide Gaussian response functions used. Deconvolution of non-noisy data is performed, and the error in each deconvolution calculated. Plots are produced of error versus filter length; and from these plots the most accurate length filters determined. The statistical methodologies employed in the optimizations of Morrison's method are similar. A typical peak-type input is selected and convolved with the two response functions to produce the data sets to be analyzed. Both constant and ordinate-dependent Gaussian distributed noise is added to the data, where the noise levels of the data are characterized by their signal-to-noise ratios. The error measures employed in the optimizations are the L1 and L2 norms. Results of the optimizations for both Gaussians, both noise types, and both norms include figures of optimum iteration number and error improvement versus signal-to-noise ratio, and tables of results. The statistical variation of all quantities considered is also given.
Computed tomography perfusion imaging denoising using Gaussian process regression
NASA Astrophysics Data System (ADS)
Zhu, Fan; Carpenter, Trevor; Rodriguez Gonzalez, David; Atkinson, Malcolm; Wardlaw, Joanna
2012-06-01
Brain perfusion weighted images acquired using dynamic contrast studies have an important clinical role in acute stroke diagnosis and treatment decisions. However, computed tomography (CT) images suffer from low contrast-to-noise ratios (CNR) as a consequence of the limitation of the exposure to radiation of the patient. As a consequence, the developments of methods for improving the CNR are valuable. The majority of existing approaches for denoising CT images are optimized for 3D (spatial) information, including spatial decimation (spatially weighted mean filters) and techniques based on wavelet and curvelet transforms. However, perfusion imaging data is 4D as it also contains temporal information. Our approach using Gaussian process regression (GPR), which takes advantage of the temporal information, to reduce the noise level. Over the entire image, GPR gains a 99% CNR improvement over the raw images and also improves the quality of haemodynamic maps allowing a better identification of edges and detailed information. At the level of individual voxel, GPR provides a stable baseline, helps us to identify key parameters from tissue time-concentration curves and reduces the oscillations in the curve. GPR is superior to the comparable techniques used in this study.
Investigations of internal noise levels for different target sizes, contrasts, and noise structures
NASA Astrophysics Data System (ADS)
Han, Minah; Choi, Shinkook; Baek, Jongduk
2014-03-01
To describe internal noise levels for different target sizes, contrasts, and noise structures, Gaussian targets with four different sizes (i.e., standard deviation of 2,4,6 and 8) and three different noise structures(i.e., white, low-pass, and highpass) were generated. The generated noise images were scaled to have standard deviation of 0.15. For each noise type, target contrasts were adjusted to have the same detectability based on NPW, and the detectability of CHO was calculated accordingly. For human observer study, 3 trained observers performed 2AFC detection tasks, and correction rate, Pc, was calculated for each task. By adding proper internal noise level to numerical observer (i.e., NPW and CHO), detectability of human observer was matched with that of numerical observers. Even though target contrasts were adjusted to have the same detectability of NPW observer, detectability of human observer decreases as the target size increases. The internal noise level varies for different target sizes, contrasts, and noise structures, demonstrating different internal noise levels should be considered in numerical observer to predict the detection performance of human observer.
Reducing Noise by Repetition: Introduction to Signal Averaging
ERIC Educational Resources Information Center
Hassan, Umer; Anwar, Muhammad Sabieh
2010-01-01
This paper describes theory and experiments, taken from biophysics and physiological measurements, to illustrate the technique of signal averaging. In the process, students are introduced to the basic concepts of signal processing, such as digital filtering, Fourier transformation, baseline correction, pink and Gaussian noise, and the cross- and…
Majorization preservation of Gaussian bosonic channels
NASA Astrophysics Data System (ADS)
Jabbour, Michael G.; García-Patrón, Raúl; Cerf, Nicolas J.
2016-07-01
It is shown that phase-insensitive Gaussian bosonic channels are majorization-preserving over the set of passive states of the harmonic oscillator. This means that comparable passive states under majorization are transformed into equally comparable passive states by any phase-insensitive Gaussian bosonic channel. Our proof relies on a new preorder relation called Fock-majorization, which coincides with regular majorization for passive states but also induces another order relation in terms of mean boson number, thereby connecting the concepts of energy and disorder of a quantum state. The consequences of majorization preservation are discussed in the context of the broadcast communication capacity of Gaussian bosonic channels. Because most of our results are independent of the specific nature of the system under investigation, they could be generalized to other quantum systems and Hamiltonians, providing a new tool that may prove useful in quantum information theory and especially quantum thermodynamics.
CMB non-gaussianity from vector fields
Peloso, Marco
2014-01-01
The Planck satellite has recently measured the CMB temperature anisotropies with unprecedented accuracy, and it has provided strong bounds on primordial non-gaussianity. Such bounds constrain models of inflation, and mechanisms that produce the primordial perturbations. We discuss the non-gaussian signatures from the interactions of the inflation φ with spin-1 fields. We study the two different cases in which the inflaton is (i) a pseudo-scalar field with a (φ)/(fa) F·F interaction with a vector field, and (ii) a scalar field with a f (φ)F² interaction. In the first case we obtain the strong limit f{sub a} ≥ 10¹⁶GeV on the decay constant. In the second case, specific choices of the function f (φ) can lead to a non-gaussianity with a characteristic shape not encountered in standard models of scalar field inflation, and which has also been constrained by Planck.
Gaussian state for the bouncing quantum cosmology
NASA Astrophysics Data System (ADS)
Mielczarek, Jakub; Piechocki, Włodzimierz
2012-10-01
We present results concerning propagation of the Gaussian state across the cosmological quantum bounce. The reduced phase space quantization of loop quantum cosmology is applied to the Friedman-Robertson-Walker universe with a free massless scalar field. Evolution of quantum moments of the canonical variables is investigated. The covariance turns out to be a monotonic function so it may be used as an evolution parameter having quantum origin. We show that for the Gaussian state the Universe is least quantum at the bounce. We propose explanation of this counter-intuitive feature using the entropy of squeezing. The obtained time dependence of entropy is in agreement with qualitative predictions based on von Neumann entropy for mixed states. We show that, for the considered Gaussian state, semiclassicality is preserved across the bounce, so there is no cosmic forgetfulness.
Index Distribution of Gaussian Random Matrices
Majumdar, Satya N.; Nadal, Celine; Scardicchio, Antonello; Vivo, Pierpaolo
2009-11-27
We compute analytically, for large N, the probability distribution of the number of positive eigenvalues (the index N{sub +}) of a random NxN matrix belonging to Gaussian orthogonal (beta=1), unitary (beta=2) or symplectic (beta=4) ensembles. The distribution of the fraction of positive eigenvalues c=N{sub +}/N scales, for large N, as P(c,N){approx_equal}exp[-betaN{sup 2}PHI(c)] where the rate function PHI(c), symmetric around c=1/2 and universal (independent of beta), is calculated exactly. The distribution has non-Gaussian tails, but even near its peak at c=1/2 it is not strictly Gaussian due to an unusual logarithmic singularity in the rate function.
Community noise sources and noise control issues
NASA Technical Reports Server (NTRS)
Nihart, Gene L.
1992-01-01
The topics covered include the following: community noise sources and noise control issues; noise components for turbine bypass turbojet engine (TBE) turbojet; engine cycle selection and noise; nozzle development schedule; NACA nozzle design; NACA nozzle test results; nearly fully mixed (NFM) nozzle design; noise versus aspiration rate; peak noise test results; nozzle test in the Low Speed Aeroacoustic Facility (LSAF); and Schlieren pictures of NACA nozzle.
Semisupervised Gaussian Process for Automated Enzyme Search.
Mellor, Joseph; Grigoras, Ioana; Carbonell, Pablo; Faulon, Jean-Loup
2016-06-17
Synthetic biology is today harnessing the design of novel and greener biosynthesis routes for the production of added-value chemicals and natural products. The design of novel pathways often requires a detailed selection of enzyme sequences to import into the chassis at each of the reaction steps. To address such design requirements in an automated way, we present here a tool for exploring the space of enzymatic reactions. Given a reaction and an enzyme the tool provides a probability estimate that the enzyme catalyzes the reaction. Our tool first considers the similarity of a reaction to known biochemical reactions with respect to signatures around their reaction centers. Signatures are defined based on chemical transformation rules by using extended connectivity fingerprint descriptors. A semisupervised Gaussian process model associated with the similar known reactions then provides the probability estimate. The Gaussian process model uses information about both the reaction and the enzyme in providing the estimate. These estimates were validated experimentally by the application of the Gaussian process model to a newly identified metabolite in Escherichia coli in order to search for the enzymes catalyzing its associated reactions. Furthermore, we show with several pathway design examples how such ability to assign probability estimates to enzymatic reactions provides the potential to assist in bioengineering applications, providing experimental validation to our proposed approach. To the best of our knowledge, the proposed approach is the first application of Gaussian processes dealing with biological sequences and chemicals, the use of a semisupervised Gaussian process framework is also novel in the context of machine learning applied to bioinformatics. However, the ability of an enzyme to catalyze a reaction depends on the affinity between the substrates of the reaction and the enzyme. This affinity is generally quantified by the Michaelis constant KM
Gaussian Process Regression for Uncertainty Estimation on Ecosystem Data
NASA Astrophysics Data System (ADS)
Menzer, O.; Moffat, A.; Lasslop, G.; Reichstein, M.
2011-12-01
The flow of carbon between terrestrial ecosystems and the atmosphere is mainly driven by nonlinear, complex and time-lagged processes. Understanding the associated ecosystem responses and climatic feedbacks is a key challenge regarding climate change questions such as increasing atmospheric CO2 levels. Usually, the underlying relationships are implemented in models as prescribed functions which interlink numerous meteorological, radiative and gas exchange variables. In contrast, supervised Machine Learning algorithms, such as Artificial Neural Networks or Gaussian Processes, allow for an insight into the relationships directly from a data perspective. Micrometeorological, high resolution measurements at flux towers of the FLUXNET observational network are an essential tool for obtaining quantifications of the ecosystem variables, as they continuously record e.g. CO2 exchange, solar radiation and air temperature. In order to facilitate the investigation of the interactions and feedbacks between these variables, several challenging data properties need to be taken into account: noisy, multidimensional and incomplete (Moffat, Accepted). The task of estimating uncertainties in such micrometeorological measurements can be addressed by Gaussian Processes (GPs), a modern nonparametric method for nonlinear regression. The GP approach has recently been shown to be a powerful modeling tool, regardless of the input dimensionality, the degree of nonlinearity and the noise level (Rasmussen and Williams, 2006). Heteroscedastic Gaussian Processes (HGPs) are a specialized GP method for data with a varying, inhomogeneous noise variance (Goldberg et al., 1998; Kersting et al., 2007), as usually observed in CO2 flux measurements (Richardson et al., 2006). Here, we showed by an evaluation of the HGP performance in several artificial experiments and a comparison to existing nonlinear regression methods, that their outstanding ability is to capture measurement noise levels, concurrently
Suggested noise criteria for plumbing systems
NASA Astrophysics Data System (ADS)
Lilly, Jerry
2005-09-01
The issue of noise that is generated by plumbing systems has been addressed in several articles and texts in the acoustic literature, but most of this information deals with a description of the various noise generation mechanisms and recommended methods of controlling noise from plumbing fixtures and piping. As with any noise source that has the potential for generating annoyance, the question of how much noise is too much noise eventually arises. Chapter 47 of the 2003 ASHRAE Applications Handbook contains newly published guidelines for plumbing noise criteria as it impacts building occupants. This paper discusses the ASHRAE guidelines, and it also suggests additional noise criteria for other plumbing-related sources of noise in multitenant buildings.
Catlin, F.I.
1986-03-01
Hearing loss affects 30 million people in the United States; of these, 21 million are over the age of 65 years. This disorder may have several causes: heredity, noise, aging, and disease. Hearing loss from noise has been recognized for centuries but was generally ignored until some time after the Industrial Revolution. Hearing loss from occupational exposure to hazardous noise was identified as a compensable disability by the United States courts in 1948 to 1959. Development of noisy jet engines and supersonic aircraft created additional claims for personal and property damage in the 1950s and 1960s. These conditions led to legislation for noise control in the form of the Occupational Safety and Health Act of 1970 and the Noise Control Act of 1972. Protection of the noise-exposed employee was also an objective of the Hearing Conservation Act of 1971. Subsequent studies have confirmed the benefits of periodic hearing tests for workers exposed to hazardous noise and of otologic evaluation as part of the hearing conservation process. Research studies in laboratory animals, using scanning electron microscopical techniques, have demonstrated that damage to the inner ear and organ of hearing can occur even though subjective (conditioned) response to sound stimuli remains unaffected. Some investigators have employed an epidemiologic approach to identify risk factors and to develop profiles to susceptibility to noise-induced hearing loss. The need for joint involvement of workers and employers in the reduction and control of occupational noise hazards is evident. 19 references.
Chen, Yunjie; Zhan, Tianming; Zhang, Ji; Wang, Hongyuan
2016-01-01
We propose a novel segmentation method based on regional and nonlocal information to overcome the impact of image intensity inhomogeneities and noise in human brain magnetic resonance images. With the consideration of the spatial distribution of different tissues in brain images, our method does not need preestimation or precorrection procedures for intensity inhomogeneities and noise. A nonlocal information based Gaussian mixture model (NGMM) is proposed to reduce the effect of noise. To reduce the effect of intensity inhomogeneity, the multigrid nonlocal Gaussian mixture model (MNGMM) is proposed to segment brain MR images in each nonoverlapping multigrid generated by using a new multigrid generation method. Therefore the proposed model can simultaneously overcome the impact of noise and intensity inhomogeneity and automatically classify 2D and 3D MR data into tissues of white matter, gray matter, and cerebral spinal fluid. To maintain the statistical reliability and spatial continuity of the segmentation, a fusion strategy is adopted to integrate the clustering results from different grid. The experiments on synthetic and clinical brain MR images demonstrate the superior performance of the proposed model comparing with several state-of-the-art algorithms.
Invariant measures on multimode quantum Gaussian states
Lupo, C.; Mancini, S.; De Pasquale, A.; Facchi, P.; Florio, G.; Pascazio, S.
2012-12-15
We derive the invariant measure on the manifold of multimode quantum Gaussian states, induced by the Haar measure on the group of Gaussian unitary transformations. To this end, by introducing a bipartition of the system in two disjoint subsystems, we use a parameterization highlighting the role of nonlocal degrees of freedom-the symplectic eigenvalues-which characterize quantum entanglement across the given bipartition. A finite measure is then obtained by imposing a physically motivated energy constraint. By averaging over the local degrees of freedom we finally derive the invariant distribution of the symplectic eigenvalues in some cases of particular interest for applications in quantum optics and quantum information.
Cosmological Applications of the Gaussian Kinematic Formula
NASA Astrophysics Data System (ADS)
Fantaye, Yabebal T.; Marinucci, Domenico
2014-05-01
The Gaussian Kinematic Formula (GKF, see Adler and Taylor (2007,2011)) is an extremely powerful tool allowing for explicit analytic predictions of expected values of Minkowski functionals under realistic experimental conditions for cosmological data collections. In this paper, we implement Minkowski functionals on multipoles and needlet components of CMB fields, thus allowing a better control of cosmic variance and extraction of information on both harmonic and real domains; we then exploit the GKF to provide their expected values on spherical maps, in the presence of arbitrary sky masks, and under nonGaussian circumstances.
Invariant measures on multimode quantum Gaussian states
NASA Astrophysics Data System (ADS)
Lupo, C.; Mancini, S.; De Pasquale, A.; Facchi, P.; Florio, G.; Pascazio, S.
2012-12-01
We derive the invariant measure on the manifold of multimode quantum Gaussian states, induced by the Haar measure on the group of Gaussian unitary transformations. To this end, by introducing a bipartition of the system in two disjoint subsystems, we use a parameterization highlighting the role of nonlocal degrees of freedom—the symplectic eigenvalues—which characterize quantum entanglement across the given bipartition. A finite measure is then obtained by imposing a physically motivated energy constraint. By averaging over the local degrees of freedom we finally derive the invariant distribution of the symplectic eigenvalues in some cases of particular interest for applications in quantum optics and quantum information.
Investigation of Noises in GPS Time Series: Case Study on Epn Weekly Solutions
NASA Astrophysics Data System (ADS)
Klos, Anna; Bogusz, Janusz; Figurski, Mariusz; Kosek, Wieslaw; Gruszczynski, Maciej
2014-05-01
The noises in GPS time series are stated to be described the best by the combination of white (Gaussian) and power-law processes. They are mainly the effect of mismodelled satellite orbits, Earth orientation parameters, atmospheric effects, antennae phase centre effects, or of monument instability. Due to the fact, that velocities of permanent stations define the kinematic reference frame, they have to fulfil the requirement of being stable at 0.1 mm/yr. The previously performed researches showed, that the wrong assumption of noise model leads to the underestimation of velocities and their uncertainties from 2 up to even 11, especially in the Up direction. This presentation focuses on more than 200 EPN (EUREF Permanent Network) stations from the area of Europe with various monument types (concrete pillars, buildings, metal masts, with or without domes, placed on the ground or on the rock) and coordinates of weekly changes (GPS weeks 0834-1459). The topocentric components (North, East, Up) in ITRF2005 which come from the EPN Re-Processing made by the Military University of Technology Local Analysis Centre (MUT LAC) were processed with Maximum Likelihood Estimation (MLE) using CATS software. We have assumed the existence of few combinations of noise models (these are: white, flicker and random walk noise with integer spectral indices and power-law noise models with fractional spectral indices) and investigated which of them EPN weekly time series are likely to follow. The results show, that noises in GPS time series are described the best by the combination of white and flicker noise model. It is strictly related to the so-called common mode error (CME) that is spatially correlated error being one of the dominant error source in GPS solutions. We have assumed CME as spatially uniform, what was a good approximation for stations located hundreds of kilometres one to another. Its removal with spatial filtering reduces the amplitudes of white and flicker noise by a
Semiconductor Laser Low Frequency Noise Characterization
NASA Technical Reports Server (NTRS)
Maleki, Lute; Logan, Ronald T.
1996-01-01
This work summarizes the efforts in identifying the fundamental noise limit in semiconductor optical sources (lasers) to determine the source of 1/F noise and it's associated behavior. In addition, the study also addresses the effects of this 1/F noise on RF phased arrays. The study showed that the 1/F noise in semiconductor lasers has an ultimate physical limit based upon similar factors to fundamental noise generated in other semiconductor and solid state devices. The study also showed that both additive and multiplicative noise can be a significant detriment to the performance of RF phased arrays especially in regard to very low sidelobe performance and ultimate beam steering accuracy. The final result is that a noise power related term must be included in a complete analysis of the noise spectrum of any semiconductor device including semiconductor lasers.
Noise-sustained synchronization between electrically coupled FitzHugh-Nagumo networks
NASA Astrophysics Data System (ADS)
Cascallares, Guadalupe; Sánchez, Alejandro D.; dell'Erba, Matías G.; Izús, Gonzalo G.
2015-09-01
We investigate the capability of electrical synapses to transmit the noise-sustained network activity from one network to another. The particular setup we consider is two identical rings with excitable FitzHugh-Nagumo cell dynamics and nearest-neighbor antiphase intra-ring coupling, electrically coupled between corresponding nodes. The whole system is submitted to independent local additive Gaussian white noises with common intensity η, but only one ring is externally forced by a global adiabatic subthreshold harmonic signal. We then seek conditions for a particular noise level to promote synchronized stable firing patterns. By running numerical integrations with increasing η, we observe the excitation activity to become spatiotemporally self-organized, until η is so strong that spoils sync between networks for a given value of the electric coupling strength. By means of a four-cell model and calculating the stationary probability distribution, we obtain a (signal-dependent) non-equilibrium potential landscape which explains qualitatively the observed regimes, and whose barrier heights give a good estimate of the optimal noise intensity for the sync between networks.
Karakida, Ryo; Okada, Masato; Amari, Shun-Ichi
2016-07-01
The restricted Boltzmann machine (RBM) is an essential constituent of deep learning, but it is hard to train by using maximum likelihood (ML) learning, which minimizes the Kullback-Leibler (KL) divergence. Instead, contrastive divergence (CD) learning has been developed as an approximation of ML learning and widely used in practice. To clarify the performance of CD learning, in this paper, we analytically derive the fixed points where ML and CDn learning rules converge in two types of RBMs: one with Gaussian visible and Gaussian hidden units and the other with Gaussian visible and Bernoulli hidden units. In addition, we analyze the stability of the fixed points. As a result, we find that the stable points of CDn learning rule coincide with those of ML learning rule in a Gaussian-Gaussian RBM. We also reveal that larger principal components of the input data are extracted at the stable points. Moreover, in a Gaussian-Bernoulli RBM, we find that both ML and CDn learning can extract independent components at one of stable points. Our analysis demonstrates that the same feature components as those extracted by ML learning are extracted simply by performing CD1 learning. Expanding this study should elucidate the specific solutions obtained by CD learning in other types of RBMs or in deep networks.
Non-Gaussian Analysis of Turbulent Boundary Layer Fluctuating Pressure on Aircraft Skin Panels
NASA Technical Reports Server (NTRS)
Rizzi, Stephen A.; Steinwolf, Alexander
2005-01-01
The purpose of the study is to investigate the probability density function (PDF) of turbulent boundary layer fluctuating pressures measured on the outer sidewall of a supersonic transport aircraft and to approximate these PDFs by analytical models. Experimental flight results show that the fluctuating pressure PDFs differ from the Gaussian distribution even for standard smooth surface conditions. The PDF tails are wider and longer than those of the Gaussian model. For pressure fluctuations in front of forward-facing step discontinuities, deviations from the Gaussian model are more significant and the PDFs become asymmetrical. There is a certain spatial pattern of the skewness and kurtosis behavior depending on the distance upstream from the step. All characteristics related to non-Gaussian behavior are highly dependent upon the distance from the step and the step height, less dependent on aircraft speed, and not dependent on the fuselage location. A Hermite polynomial transform model and a piecewise-Gaussian model fit the flight data well both for the smooth and stepped conditions. The piecewise-Gaussian approximation can be additionally regarded for convenience in usage after the model is constructed.
Hermite-Gaussian Vector soliton in strong nonlocal media
NASA Astrophysics Data System (ADS)
Wang, Qing; Li, JingZhen
2014-12-01
The propagation of two mutually incoherent Hermite-Gaussian (HG) beams in strong nonlocal media was studied. We obtained the evolution equations for the parameters of the two beams and found the condition of forming a HG Vector soliton by variational approach. The numerical result, which accords with the analytical solution very well, shows that a series of vector solitons which consisted of different-order HG beam pairs can be formed in strong nonlocal media. In addition, we found that the phase shifts are not only related to the total incident power, but also related to the orders of the two HG beams.
Experimental characterization of Gaussian quantum-communication channels
Di Guglielmo, James; Hage, Boris; Franzen, Alexander; Schnabel, Roman; Fiurasek, Jaromir
2007-07-15
We present a full experimental characterization of continuous-variable quantum-communication channels established by shared entanglement together with local operations and classical communication. The resulting teleportation channel was fully characterized by measuring all elements of the covariance matrix of the shared two-mode squeezed Gaussian state. From the experimental data we determined the lower bound to the quantum channel capacity, the teleportation fidelity of coherent states, and the logarithmic negativity and purity of the shared state. Additionally, a positive secret key rate was obtained for two of the established channels.
Noise Modeling of SDO AIA Images
NASA Astrophysics Data System (ADS)
Kirk, M. S.; Young, C. A.
2014-12-01
All digital images are corrupted by noise. In most solar imaging, we have the luxury of high photon counts and low background contamination, which when combined with carful calibration, minimize much of the impact noise has on the measurement. Outside high-intensity regions, such as in coronal holes, the noise component can become significant and complicate feature recognition and segmentation. We create a practical estimate of noise in the AIA images across the detector CCD. A Poisson-Gaussian model of noise is well suited in the digital imaging environment due to the statistical distributions of photons and the characteristics of the CCD. Using the dark and flat field calibration images, the level-1 AIA images, and readout noise measurements, we construct a maximum-a-posteriori estimation of the expected error in the AIA images. These estimations of noise not only provide a clearer view of solar features in AIA, but they are also relevant to error characterizations of other solar images.
Control of Environmental Noise
ERIC Educational Resources Information Center
Jensen, Paul
1973-01-01
Discusses the physical properties, sources, physiological effects, and legislation pertaining to noise, especially noise characteristics in the community. Indicates that noise reduction steps can be taken more intelligently after determination of the true noise sources and paths. (CC)
NASA Astrophysics Data System (ADS)
Ji, Se-Wan; Kim, M. S.; Nha, Hyunchul
2015-04-01
It is a topic of fundamental and practical importance how a quantum correlated state can be reliably distributed through a noisy channel for quantum information processing. The concept of quantum steering recently defined in a rigorous manner is relevant to study it under certain circumstances and here we address quantum steerability of Gaussian states to this aim. In particular, we attempt to reformulate the criterion for Gaussian steering in terms of local and global purities and show that it is sufficient and necessary for the case of steering a 1-mode system by an N-mode system. It subsequently enables us to reinforce a strong monogamy relation under which only one party can steer a local system of 1-mode. Moreover, we show that only a negative partial-transpose state can manifest quantum steerability by Gaussian measurements in relation to the Peres conjecture. We also discuss our formulation for the case of distributing a two-mode squeezed state via one-way quantum channels making dissipation and amplification effects, respectively. Finally, we extend our approach to include non-Gaussian measurements, more precisely, all orders of higher-order squeezing measurements, and find that this broad set of non-Gaussian measurements is not useful to demonstrate steering for Gaussian states beyond Gaussian measurements.
Analysis and removing noise from speech using wavelet transform
NASA Astrophysics Data System (ADS)
Tomala, Karel; Voznak, Miroslav; Partila, Pavol; Rezac, Filip; Safarik, Jakub
2013-05-01
The paper discusses the use of Discrete Wavelet Transform (DWT) and Stationary Wavelet Transform (SWT) wavelet in removing noise from voice samples and evaluation of its impact on speech quality. One significant part of Quality of Service (QoS) in communication technology is the speech quality assessment. However, this part is seriously overlooked as telecommunication providers often focus on increasing network capacity, expansion of services offered and their enforcement in the market. Among the fundamental factors affecting the transmission properties of the communication chain is noise, either at the transmitter or the receiver side. A wavelet transform (WT) is a modern tool for signal processing. One of the most significant areas in which wavelet transforms are used is applications designed to suppress noise in signals. To remove noise from the voice sample in our experiment, we used the reference segment of the voice which was distorted by Gaussian white noise. An evaluation of the impact on speech quality was carried out by an intrusive objective algorithm Perceptual Evaluation of Speech Quality (PESQ). DWT and SWT transformation was applied to voice samples that were devalued by Gaussian white noise. Afterwards, we determined the effectiveness of DWT and SWT by means of objective algorithm PESQ. The decisive criterion for determining the quality of a voice sample once the noise had been removed was Mean Opinion Score (MOS) which we obtained in PESQ. The contribution of this work lies in the evaluation of efficiency of wavelet transformation to suppress noise in voice samples.
Ghosh, Pradipta; Shit, Anindita; Chattopadhyay, Sudip; Chaudhuri, Jyotipratim Ray
2011-03-15
This work explores the observation that, even in the absence of a net externally applied bias, a symmetric homogeneous system coupled linearly to two heat baths is capable of producing unidirectional motion simply by nonlinearly driving one of the heat baths by an external Gaussian white noise. This is quite contrary to the traditional observation that, in order to obtain a net drift current, a state-dependent dissipation, which is a consequence of nonlinear system-bath coupling, is ubiquitous.
Non-Gaussian states from continuous-wave Gaussian light sources
NASA Astrophysics Data System (ADS)
Mølmer, Klaus
2006-06-01
We present a general analysis of the state obtained by subjecting a continuous-wave (cw) Gaussian field to non-Gaussian measurements. The generic multimode state of a cw Gaussian field is fully characterized by the time dependent mean values and variances and the two-time covariances of the field quadrature variables. We present a general theory to extract from this information the results of detection and quantum state reduction within specific temporal output modes. The formalism is applied to schemes for heralded production of propagating light pulses with single photon and Schrödinger kitten states from a cw squeezed beam of light.
NASA Astrophysics Data System (ADS)
Wang, Chao-Jie; Long, Fei; Zhang, Pei; Nie, Lin-Ru
2017-04-01
Stochastic resonance (SR) and noise enhanced stability (NES) in a bistable system driven by an additive harmonic noise and a multiplicative harmonic noise is investigated. Through numerical simulation, we obtained the power spectrum by the Fourier transformation on time series. The results indicate that (i) for certain values of the parameters of additive harmonic noise Γ, Ω and the noise intensity D, the SR phenomenon occurs. It means we can control the SR phenomenon by modulating the parameters of harmonic noise; (ii) the NES phenomenon occurs at certain values of the parameters of multiplicative harmonic noise Γ, Ω and the multiplicative noise intensity Q. Most important, the NES phenomenon can also be controlled by modulating the parameters of harmonic noise.
Noise pollution resources compendium
NASA Technical Reports Server (NTRS)
1973-01-01
Abstracts of reports concerning noise pollution are presented. The abstracts are grouped in the following areas of activity: (1) sources of noise, (2) noise detection and measurement, (3) noise abatement and control, (4) physical effects of noise and (5) social effects of noise.
Ma, Rubao; Xu, Weichao; Zhang, Yun; Ye, Zhongfu
2014-01-01
This paper investigates the robustness properties of Pearson's rank-variate correlation coefficient (PRVCC) in scenarios where one channel is corrupted by impulsive noise and the other is impulsive noise-free. As shown in our previous work, these scenarios that frequently encountered in radar and/or sonar, can be well emulated by a particular bivariate contaminated Gaussian model (CGM). Under this CGM, we establish the asymptotic closed forms of the expectation and variance of PRVCC by means of the well known Delta method. To gain a deeper understanding, we also compare PRVCC with two other classical correlation coefficients, i.e., Spearman's rho (SR) and Kendall's tau (KT), in terms of the root mean squared error (RMSE). Monte Carlo simulations not only verify our theoretical findings, but also reveal the advantage of PRVCC by an example of estimating the time delay in the particular impulsive noise environment.
Gravitational-Wave Data Analysis. Formalism and Sample Applications: The Gaussian Case.
Jaranowski, Piotr; Królak, Andrzej
2012-01-01
The article reviews the statistical theory of signal detection in application to analysis of deterministic gravitational-wave signals in the noise of a detector. Statistical foundations for the theory of signal detection and parameter estimation are presented. Several tools needed for both theoretical evaluation of the optimal data analysis methods and for their practical implementation are introduced. They include optimal signal-to-noise ratio, Fisher matrix, false alarm and detection probabilities, [Formula: see text]-statistic, template placement, and fitting factor. These tools apply to the case of signals buried in a stationary and Gaussian noise. Algorithms to efficiently implement the optimal data analysis techniques are discussed. Formulas are given for a general gravitational-wave signal that includes as special cases most of the deterministic signals of interest.
Ma, Rubao; Xu, Weichao; Zhang, Yun; Ye, Zhongfu
2014-01-01
This paper investigates the robustness properties of Pearson's rank-variate correlation coefficient (PRVCC) in scenarios where one channel is corrupted by impulsive noise and the other is impulsive noise-free. As shown in our previous work, these scenarios that frequently encountered in radar and/or sonar, can be well emulated by a particular bivariate contaminated Gaussian model (CGM). Under this CGM, we establish the asymptotic closed forms of the expectation and variance of PRVCC by means of the well known Delta method. To gain a deeper understanding, we also compare PRVCC with two other classical correlation coefficients, i.e., Spearman's rho (SR) and Kendall's tau (KT), in terms of the root mean squared error (RMSE). Monte Carlo simulations not only verify our theoretical findings, but also reveal the advantage of PRVCC by an example of estimating the time delay in the particular impulsive noise environment. PMID:25393286
Adaptive conductance filtering for spatially varying noise in PET images
NASA Astrophysics Data System (ADS)
Padfield, Dirk R.; Manjeshwar, Ravindra
2006-03-01
PET images that have been reconstructed with unregularized algorithms are commonly smoothed with linear Gaussian filters to control noise. Since these filters are spatially invariant, they degrade feature contrast in the image, compromising lesion detectability. Edge-preserving smoothing filters can differentially preserve edges and features while smoothing noise. These filters assume spatially uniform noise models. However, the noise in PET images is spatially variant, approximately following a Poisson behavior. Therefore, different regions of a PET image need smoothing by different amounts. In this work, we introduce an adaptive filter, based on anisotropic diffusion, designed specifically to overcome this problem. In this algorithm, the diffusion is varied according to a local estimate of the noise using either the local median or the grayscale image opening to weight the conductance parameter. The algorithm is thus tailored to the task of smoothing PET images, or any image with Poisson-like noise characteristics, by adapting itself to varying noise while preserving significant features in the image. This filter was compared with Gaussian smoothing and a representative anisotropic diffusion method using three quantitative task-relevant metrics calculated on simulated PET images with lesions in the lung and liver. The contrast gain and noise ratio metrics were used to measure the ability to do accurate quantitation; the Channelized Hotelling Observer lesion detectability index was used to quantify lesion detectability. The adaptive filter improved the signal-to-noise ratio by more than 45% and lesion detectability by more than 55% over the Gaussian filter while producing "natural" looking images and consistent image quality across different anatomical regions.
A real-time multi-scale 2D Gaussian filter based on FPGA
NASA Astrophysics Data System (ADS)
Luo, Haibo; Gai, Xingqin; Chang, Zheng; Hui, Bin
2014-11-01
Multi-scale 2-D Gaussian filter has been widely used in feature extraction (e.g. SIFT, edge etc.), image segmentation, image enhancement, image noise removing, multi-scale shape description etc. However, their computational complexity remains an issue for real-time image processing systems. Aimed at this problem, we propose a framework of multi-scale 2-D Gaussian filter based on FPGA in this paper. Firstly, a full-hardware architecture based on parallel pipeline was designed to achieve high throughput rate. Secondly, in order to save some multiplier, the 2-D convolution is separated into two 1-D convolutions. Thirdly, a dedicate first in first out memory named as CAFIFO (Column Addressing FIFO) was designed to avoid the error propagating induced by spark on clock. Finally, a shared memory framework was designed to reduce memory costs. As a demonstration, we realized a 3 scales 2-D Gaussian filter on a single ALTERA Cyclone III FPGA chip. Experimental results show that, the proposed framework can computing a Multi-scales 2-D Gaussian filtering within one pixel clock period, is further suitable for real-time image processing. Moreover, the main principle can be popularized to the other operators based on convolution, such as Gabor filter, Sobel operator and so on.
Primordial non-Gaussianity and reionization
NASA Astrophysics Data System (ADS)
Lidz, Adam; Baxter, Eric J.; Adshead, Peter; Dodelson, Scott
2013-07-01
The statistical properties of the primordial perturbations contain clues about their origins. Although the Planck collaboration has recently obtained tight constraints on primordial non-Gaussianity from cosmic microwave background measurements, it is still worthwhile to mine upcoming data sets in an effort to place independent or competitive limits. The ionized bubbles that formed at redshift z˜6-20 during the epoch of reionization were seeded by primordial overdensities, and so the statistics of the ionization field at high redshift are related to the statistics of the primordial field. Here we model the effect of primordial non-Gaussianity on the reionization field. The epoch and duration of reionization are affected, as are the sizes of the ionized bubbles, but these changes are degenerate with variations in the properties of the ionizing sources and the surrounding intergalactic medium. A more promising signature is the power spectrum of the spatial fluctuations in the ionization field, which may be probed by upcoming 21 cm surveys. This has the expected 1/k2 dependence on large scales, characteristic of a biased tracer of the matter field. We project how well upcoming 21 cm observations will be able to disentangle this signal from foreground contamination. Although foreground cleaning inevitably removes the large-scale modes most impacted by primordial non-Gaussianity, we find that primordial non-Gaussianity can be separated from foreground contamination for a narrow range of length scales. In principle, futuristic redshifted 21 cm surveys may allow constraints competitive with Planck.
Diffusion of Super-Gaussian Profiles
ERIC Educational Resources Information Center
Rosenberg, C.-J.; Anderson, D.; Desaix, M.; Johannisson, P.; Lisak, M.
2007-01-01
The present analysis describes an analytically simple and systematic approximation procedure for modelling the free diffusive spreading of initially super-Gaussian profiles. The approach is based on a self-similar ansatz for the evolution of the diffusion profile, and the parameter functions involved in the modelling are determined by suitable…
How Gaussian can our Universe be?
NASA Astrophysics Data System (ADS)
Cabass, G.; Pajer, E.; Schmidt, F.
2017-01-01
Gravity is a non-linear theory, and hence, barring cancellations, the initial super-horizon perturbations produced by inflation must contain some minimum amount of mode coupling, or primordial non-Gaussianity. In single-field slow-roll models, where this lower bound is saturated, non-Gaussianity is controlled by two observables: the tensor-to-scalar ratio, which is uncertain by more than fifty orders of magnitude; and the scalar spectral index, or tilt, which is relatively well measured. It is well known that to leading and next-to-leading order in derivatives, the contributions proportional to the tilt disappear from any local observable, and suspicion has been raised that this might happen to all orders, allowing for an arbitrarily low amount of primordial non-Gaussianity. Employing Conformal Fermi Coordinates, we show explicitly that this is not the case. Instead, a contribution of order the tilt appears in local observables. In summary, the floor of physical primordial non-Gaussianity in our Universe has a squeezed-limit scaling of kl2/ks2, similar to equilateral and orthogonal shapes, and a dimensionless amplitude of order 0.1 × (ns‑1).
Transitional behavior of quantum Gaussian memory channels
NASA Astrophysics Data System (ADS)
Lupo, C.; Mancini, S.
2010-05-01
We address the question of optimality of entangled input states in quantum Gaussian memory channels. For a class of such channels, which can be traced back to the memoryless setting, we state a criterion which relates the optimality of entangled inputs to the symmetry properties of the channels’ action. Several examples of channel models belonging to this class are discussed.
Non-Gaussianity effects in petrophysical quantities
NASA Astrophysics Data System (ADS)
Koohi Lai, Z.; Jafari, G. R.
2013-10-01
It has been proved that there are many indicators (petrophysical quantities) for the estimation of petroleum reservoirs. The value of information contained in each indicator is yet to be addressed. In this work, the most famous and applicable petrophysical quantities for a reservoir, which are the gamma emission (GR), sonic transient time (DT), neutron porosity (NPHI), bulk density (RHOB), and deep induced resistivity (ILD), have been analyzed in order to characterize a reservoir. The implemented technique is the well-logging method. Based on the log-normal model defined in random multiplicative processes, the probability distribution function (PDF) for the data sets is described. The shape of the PDF depends on the parameter λ2 which determines the efficiency of non-Gaussianity. When non-Gaussianity appears, it is a sign of uncertainty and phase transition in the critical regime. The large value and scale-invariant behavior of the non-Gaussian parameter λ2 is an indication of a new phase which proves adequate for the existence of petroleum reservoirs. Our results show that one of the indicators (GR) is more non-Gaussian than the other indicators, scale wise. This means that GR is a continuously critical indicator. But by moving windows with various scales, the estimated λ2 shows that the most appropriate indicator for distinguishing the critical regime is ILD, which shows an increase at the end of the measured region of the well.
NASA Technical Reports Server (NTRS)
1983-01-01
SMART, Sound Modification and Regulated Temperature compound, is a liquid plastic mixture with exceptional energy and sound absorbing qualities. It is derived from a very elastic plastic which was an effective noise abatement material in the Apollo Guidance System. Discovered by a NASA employee, it is marketed by Environmental Health Systems, Inc. (EHS). The product has been successfully employed by a diaper company with noisy dryers and a sugar company with noisy blowers. The company also manufactures an audiometric test booth and acoustical office partitions.
Interim prediction method for low frequency core engine noise
NASA Technical Reports Server (NTRS)
Huff, R. G.; Clark, B. J.; Dorsch, R. G.
1974-01-01
A literature survey on low-frequency core engine noise is presented. Possible sources of low frequency internally generated noise in core engines are discussed with emphasis on combustion and component scrubbing noise. An interim method is recommended for predicting low frequency core engine noise that is dominant when jet velocities are low. Suggestions are made for future research on low frequency core engine noise that will aid in improving the prediction method and help define possible additional internal noise sources.
Automatic fitting of Gaussian peaks using abductive machine learning
Abdel-Aal, R.E.
1998-02-01
Analytical techniques have been used for many years for fitting Gaussian peaks in nuclear spectroscopy. However, the complexity of the approach warrants looking for machine-learning alternatives where intensive computations are required only once (during training), while actual analysis on individual spectra is greatly simplified and quickened. This should allow the use of simple portable systems for fast and automated analysis of large numbers of spectra, particularly in situations where accuracy may be traded for speed and simplicity. This paper proposes the use of abductive networks machine learning for this purpose. The Abductory Induction Mechanism (AIM) tool was used to build models for analyzing both single and double Gaussian peaks in the presence of noise depicting statistical uncertainties in collected spectra. AIM networks were synthesized by training on 1,000 representative simulated spectra and evaluated on 500 new spectra. A classifier network determines the multiplicity of single/double peaks with an accuracy of 98%. With statistical uncertainties corresponding to a peak count of 100, average percentage absolute errors for the height, position, and width of single peaks are 4.9, 2.9, and 4.2%, respectively. For double peaks, these average errors are within 7.0, 3.1, and 5.9%, respectively. Models have been developed which account for the effect of a linear background on a single peak. Performance is compared with a neural network application and with an analytical curve-fitting routine, and the new technique is applied to actual data of an alpha spectrum.
Contrastive divergence in gaussian diffusions.
Movellan, Javier R
2008-09-01
This letter presents an analysis of the contrastive divergence (CD) learning algorithm when applied to continuous-time linear stochastic neural networks. For this case, powerful techniques exist that allow a detailed analysis of the behavior of CD. The analysis shows that CD converges to maximum likelihood solutions only when the network structure is such that it can match the first moments of the desired distribution. Otherwise, CD can converge to solutions arbitrarily different from the log-likelihood solutions, or they can even diverge. This result suggests the need to improve our theoretical understanding of the conditions under which CD is expected to be well behaved and the conditions under which it may fail. In, addition the results point to practical ideas on how to improve the performance of CD.
Radiation pressure acceleration of corrugated thin foils by Gaussian and super-Gaussian beams
Adusumilli, K.; Goyal, D.; Tripathi, V. K.
2012-01-15
Rayleigh-Taylor instability of radiation pressure accelerated ultrathin foils by laser having Gaussian and super-Gaussian intensity distribution is investigated using a single fluid code. The foil is allowed to have ring shaped surface ripples. The radiation pressure force on such a foil is non-uniform with finite transverse component F{sub r}; F{sub r} varies periodically with r. Subsequently, the ripple grows as the foil moves ahead along z. With a Gaussian beam, the foil acquires an overall curvature due to non-uniformity in radiation pressure and gets thinner. In the process, the ripple perturbation is considerably washed off. With super-Gaussian beam, the ripple is found to be more strongly washed out. In order to avoid transmission of the laser through the thinning foil, a criterion on the foil thickness is obtained.
NASA Astrophysics Data System (ADS)
Mazer, Susan
2005-09-01
The argument is made that design does not stop when the fixed architectural and acoustical components are in place. Spaces live and breathe with the people who reside in them. Research and examples are presented that show that noise, auditory clutter, thrives on itself in hospitals. Application of the Lombard reflex studies fit into the hospital setting, but do not offer solutions as to how one might reduce the impact. In addition, the basis for looking at the noise component as a physical as well cultural dynamic will be addressed. Whether the result of the wrong conversation in the wrong place or the right conversation in an unfortunate place, talk mixed with sounds of technology is shown to cause its own symptoms. From heightened anxiety and stress to medical errors, staff burnout, or HIPAA violations, the case is made that noise is pandemic in hospitals and demands financial and operational investment. An explanation of how to reduce noise by design of the dynamic environment - equipment, technology, staff protocols is also provided.
Nguyen, Nha; Huang, Heng; Oraintara, Soontorn; Vo, An
2010-01-01
Motivation: Peaks are the key information in mass spectrometry (MS) which has been increasingly used to discover diseases-related proteomic patterns. Peak detection is an essential step for MS-based proteomic data analysis. Recently, several peak detection algorithms have been proposed. However, in these algorithms, there are three major deficiencies: (i) because the noise is often removed, the true signal could also be removed; (ii) baseline removal step may get rid of true peaks and create new false peaks; (iii) in peak quantification step, a threshold of signal-to-noise ratio (SNR) is usually used to remove false peaks; however, noise estimations in SNR calculation are often inaccurate in either time or wavelet domain. In this article, we propose new algorithms to solve these problems. First, we use bivariate shrinkage estimator in stationary wavelet domain to avoid removing true peaks in denoising step. Second, without baseline removal, zero-crossing lines in multi-scale of derivative Gaussian wavelets are investigated with mixture of Gaussian to estimate discriminative parameters of peaks. Third, in quantification step, the frequency, SD, height and rank of peaks are used to detect both high and small energy peaks with robustness to noise. Results: We propose a novel Gaussian Derivative Wavelet (GDWavelet) method to more accurately detect true peaks with a lower false discovery rate than existing methods. The proposed GDWavelet method has been performed on the real Surface-Enhanced Laser Desorption/Ionization Time-Of-Flight (SELDI-TOF) spectrum with known polypeptide positions and on two synthetic data with Gaussian and real noise. All experimental results demonstrate that our method outperforms other commonly used methods. The standard receiver operating characteristic (ROC) curves are used to evaluate the experimental results. Availability: http://ranger.uta.edu/∼heng/MS/GDWavelet.html or http://www.naaan.org/nhanguyen/archive.htm Contact: heng
NASA Astrophysics Data System (ADS)
Bajić, Buda; Lindblad, Joakim; Sladoje, Nataša
2016-07-01
Most energy minimization-based restoration methods are developed for signal-independent Gaussian noise. The assumption of Gaussian noise distribution leads to a quadratic data fidelity term, which is appealing in optimization. When an image is acquired with a photon counting device, it contains signal-dependent Poisson or mixed Poisson-Gaussian noise. We quantify the loss in performance that occurs when a restoration method suited for Gaussian noise is utilized for mixed noise. Signal-dependent noise can be treated by methods based on either classical maximum a posteriori (MAP) probability approach or on a variance stabilization approach (VST). We compare performances of these approaches on a large image material and observe that VST-based methods outperform those based on MAP in both quality of restoration and in computational efficiency. We quantify improvement achieved by utilizing Huber regularization instead of classical total variation regularization. The conclusion from our study is a recommendation to utilize a VST-based approach combined with regularization by Huber potential for restoration of images degraded by blur and signal-dependent noise. This combination provides a robust and flexible method with good performance and high speed.
Shamis, Mira
2013-11-15
We use the supersymmetric formalism to derive an integral formula for the density of states of the Gaussian Orthogonal Ensemble, and then apply saddle-point analysis to give a new derivation of the 1/N-correction to Wigner's law. This extends the work of Disertori on the Gaussian Unitary Ensemble. We also apply our method to the interpolating ensembles of Mehta–Pandey.
Propagation of modified Bessel-Gaussian beams in turbulence
NASA Astrophysics Data System (ADS)
Eyyuboğlu, Halil Tanyer; Hardalaç, Fırat
2008-03-01
We investigate the propagation characteristics of modified Bessel-Gaussian beams traveling in a turbulent atmosphere. The source beam formulation comprises a Gaussian exponential and the summation of modified Bessel functions. Based on an extended Huygens-Fresnel principle, the receiver plane intensity is formulated and solved down to a double integral stage. Source beam illustrations show that modified Bessel-Gaussian beams, except the lowest order case, will have well-like shapes. Modified Bessel-Gaussian beams with summations will experience lobe slicing and will display more or less the same profile regardless of order content. After propagating in turbulent atmosphere, it is observed that a modified Bessel-Gaussian beam will transform into a Bessel-Gaussian beam. Furthermore it is seen that modified Bessel-Gaussian beams with different Bessel function combinations, but possessing nearly the same profile, will differentiate during propagation. Increasing turbulence strength is found to accelerate the beam transformation toward the eventual Gaussian shape.
Bingi, Jayachandra; Murukeshan, Vadakke Matham
2015-01-01
Laser speckle pattern is a granular structure formed due to random coherent wavelet interference and generally considered as noise in optical systems including photolithography. Contrary to this, in this paper, we use the speckle pattern to generate predictable and controlled Gaussian random structures and quasi-random structures photo-lithographically. The random structures made using this proposed speckle lithography technique are quantified based on speckle statistics, radial distribution function (RDF) and fast Fourier transform (FFT). The control over the speckle size, density and speckle clustering facilitates the successful fabrication of black silicon with different surface structures. The controllability and tunability of randomness makes this technique a robust method for fabricating predictable 2D Gaussian random structures and black silicon structures. These structures can enhance the light trapping significantly in solar cells and hence enable improved energy harvesting. Further, this technique can enable efficient fabrication of disordered photonic structures and random media based devices. PMID:26679513
Bingi, Jayachandra; Murukeshan, Vadakke Matham
2015-12-18
Laser speckle pattern is a granular structure formed due to random coherent wavelet interference and generally considered as noise in optical systems including photolithography. Contrary to this, in this paper, we use the speckle pattern to generate predictable and controlled Gaussian random structures and quasi-random structures photo-lithographically. The random structures made using this proposed speckle lithography technique are quantified based on speckle statistics, radial distribution function (RDF) and fast Fourier transform (FFT). The control over the speckle size, density and speckle clustering facilitates the successful fabrication of black silicon with different surface structures. The controllability and tunability of randomness makes this technique a robust method for fabricating predictable 2D Gaussian random structures and black silicon structures. These structures can enhance the light trapping significantly in solar cells and hence enable improved energy harvesting. Further, this technique can enable efficient fabrication of disordered photonic structures and random media based devices.
Active Control of Fan Noise in Ducts Using Magnetic Bearings
2007-11-02
of magnetic bearings. An axial flow fan creates tonal noise related to its rotational rate. Additional noise exists due to harmonics of this frequency...magnetic bearings. An axial flow fan creates tonal noise related to its rotational rate. Additional noise exists due to harmonics of this frequency as well...systems typically have fans that will move air from the heating or cooling system to any desired space. Fan noise is characterized first by tonal
Modeling phase noise in multifunction subassemblies.
Driscoll, Michael
2012-03-01
Obtaining requisite phase noise performance in hardware containing multifunction circuitry requires accurate modeling of the phase noise characteristics of each signal path component, including both absolute (oscillator) and residual (non-oscillator) circuit contributors. This includes prediction of both static and vibration-induced phase noise. The model (usually in spreadsheet form) is refined as critical components are received and evaluated. Additive (KTBF) phase noise data can be reasonably estimated, based on device drive level and noise figure. However, accurate determination of component near-carrier (multiplicative) and vibration-induced noise usually must be determined via measurement. The model should also include the effects of noise introduced by IC voltage regulators and properly discriminate between common versus independent signal path residual noise contributors. The modeling can be easily implemented using a spreadsheet.
Construction noise decreases reproductive efficiency in mice.
Rasmussen, Skye; Glickman, Gary; Norinsky, Rada; Quimby, Fred W; Tolwani, Ravi J
2009-07-01
Excessive noise is well known to impair rodent health. To better understand the effect of construction noise and to establish effective noise limits during a planned expansion of our vivarium, we analyzed the effects of construction noise on mouse gestation and neonatal growth. Our hypothesis was that high levels of construction noise would reduce the number of live births and retard neonatal growth. Female Swiss Webster mice were individually implanted with 15 B6CBAF1/J embryos and then exposed to 70- and 90-dBA concrete saw cutting noise samples at defined time points during gestation. In addition, groups of mice with litters were exposed to noise at 70, 80, or 90 dBA for 1 h daily during the first week after parturition. Litter size, birth weight, incidence of stillborn pups, and rate of neonatal weight gain were analyzed. Noise decreased reproductive efficiency by decreasing live birth rates and increasing the number of stillborn pups.
NASA Astrophysics Data System (ADS)
Valente, P.; Auyuanet, A.; Barreiro, S.; Failache, H.; Lezama, A.
2015-05-01
We show that the description of light in terms of Stokes operators in combination with the assumption of Gaussian statistics results in a dramatic simplification of the experimental study of fluctuations in the light transmitted through an atomic vapor: no local oscillator is required, the detected quadrature is easily selected by a wave-plate angle, and the complete noise ellipsis reconstruction is obtained via matrix diagonalization. We provide empirical support for the assumption of Gaussian statistics in quasiresonant light transmitted through an 87Rb vapor cell and we illustrate the suggested approach by studying the evolution of the fluctuation ellipsis as a function of laser detuning. Applying the method to two light beams obtained by parting squeezed light in a beam splitter, we have measured the entanglement and quantum Gaussian discord.
Spin noise in the anisotropic central spin model
NASA Astrophysics Data System (ADS)
Hackmann, Johannes; Anders, Frithjof B.
2014-01-01
Spin-noise measurements can serve as a direct probe for the microscopic decoherence mechanism of an electronic spin in semiconductor quantum dots (QDs). We have calculated the spin-noise spectrum in the anisotropic central spin model using a Chebyshev expansion technique which exactly accounts for the dynamics up to an arbitrary long but fixed time in a finite-size system. In the isotropic case, describing QD charge with a single electron, the short-time dynamics is in good agreement with quasistatic approximations for the thermodynamic limit. The spin-noise spectrum, however, shows strong deviations at low frequencies with a power-law behavior of ω-3/4 corresponding to a t-1/4 decay at intermediate and long times. In the Ising limit, applicable to QDs with heavy-hole spins, the spin-noise spectrum exhibits a threshold behavior of (ω-ωL)-1/2 above the Larmor frequency ωL=gμBB. In the generic anisotropic central spin model we have found a crossover from a Gaussian type of spin-noise spectrum to a more Ising-type spectrum with increasing anisotropy in a finite magnetic field. In order to make contact with experiments, we present ensemble averaged spin-noise spectra for QD ensembles charged with single electrons or holes. The Gaussian-type noise spectrum evolves to a more Lorentzian shape spectrum with increasing spread of characteristic time scales and g factors of the individual QDs.
Landau-Zener transition driven by slow noise
NASA Astrophysics Data System (ADS)
Luo, Zhu-Xi; Raikh, M. E.
2017-02-01
The effect of a slow noise in nondiagonal matrix element J (t ) that describes the diabatic level coupling on the probability of the Landau-Zener transition is studied. For slow noise, the correlation time τc of J (t ) is much longer than the characteristic time of the transition. Existing theory for this case suggests that the average transition probability is the result of averaging of the conventional Landau-Zener probability, calculated for a given constant J , over the distribution of J . We calculate a finite-τc correction for this classical result. Our main finding is that this correction is dominated by sparse realizations of noise for which J (t ) passes through zero within a narrow time interval near the level crossing. Two models of noise, random telegraph noise and Gaussian noise, are considered. Naturally, in both models the average probability of transition decreases upon decreasing τc. For Gaussian noise we identify two domains of this falloff with specific dependencies of average transition probability on τc.
Mapping Urban Environmental Noise Using Smartphones
Zuo, Jinbo; Xia, Hao; Liu, Shuo; Qiao, Yanyou
2016-01-01
Noise mapping is an effective method of visualizing and accessing noise pollution. In this paper, a noise-mapping method based on smartphones to effectively and easily measure environmental noise is proposed. By using this method, a noise map of an entire area can be created using limited measurement data. To achieve the measurement with certain precision, a set of methods was designed to calibrate the smartphones. Measuring noise with mobile phones is different from the traditional static observations. The users may be moving at any time. Therefore, a method of attaching an additional microphone with a windscreen is proposed to reduce the wind effect. However, covering an entire area is impossible. Therefore, an interpolation method is needed to achieve full coverage of the area. To reduce the influence of spatial heterogeneity and improve the precision of noise mapping, a region-based noise-mapping method is proposed in this paper, which is based on the distribution of noise in different region types tagged by volunteers, to interpolate and combine them to create a noise map. To validate the effect of the method, a comparison of the interpolation results was made to analyse our method and the ordinary Kriging method. The result shows that our method is more accurate in reflecting the local distribution of noise and has better interpolation precision. We believe that the proposed noise-mapping method is a feasible and low-cost noise-mapping solution. PMID:27754359
Analytic Matrix Elements and Gradients with Shifted Correlated Gaussians
NASA Astrophysics Data System (ADS)
Fedorov, D. V.
2017-01-01
Matrix elements between shifted correlated Gaussians of various potentials with several form-factors are shown to be analytic. Their gradients with respect to the non-linear parameters of the Gaussians are also analytic. Analytic matrix elements are of importance for the correlated Gaussian method in quantum few-body physics.
On the classical capacity of quantum Gaussian channels
NASA Astrophysics Data System (ADS)
Lupo, Cosmo; Pirandola, Stefano; Aniello, Paolo; Mancini, Stefano
2011-02-01
The set of quantum Gaussian channels acting on one bosonic mode can be classified according to the action of the group of Gaussian unitaries. We look for bounds on the classical capacity for channels belonging to such a classification. Lower bounds can be efficiently calculated by restricting the study to Gaussian encodings, for which we provide analytical expressions.
Continuous-variable entanglement distillation of non-Gaussian mixed states
Dong Ruifang; Lassen, Mikael; Heersink, Joel; Marquardt, Christoph; Leuchs, Gerd; Andersen, Ulrik L.
2010-07-15
Many different quantum-information communication protocols such as teleportation, dense coding, and entanglement-based quantum key distribution are based on the faithful transmission of entanglement between distant location in an optical network. The distribution of entanglement in such a network is, however, hampered by loss and noise that is inherent in all practical quantum channels. Thus, to enable faithful transmission one must resort to the protocol of entanglement distillation. In this paper we present a detailed theoretical analysis and an experimental realization of continuous variable entanglement distillation in a channel that is inflicted by different kinds of non-Gaussian noise. The continuous variable entangled states are generated by exploiting the third order nonlinearity in optical fibers, and the states are sent through a free-space laboratory channel in which the losses are altered to simulate a free-space atmospheric channel with varying losses. We use linear optical components, homodyne measurements, and classical communication to distill the entanglement, and we find that by using this method the entanglement can be probabilistically increased for some specific non-Gaussian noise channels.
Mukherjee, S; Yao, W
2015-06-15
Purpose: To study different noise-reduction algorithms and to improve the image quality of low dose cone beam CT for patient positioning in radiation therapy. Methods: In low-dose cone-beam CT, the reconstructed image is contaminated with excessive quantum noise. In this study, three well-developed noise reduction algorithms namely, a) penalized weighted least square (PWLS) method, b) split-Bregman total variation (TV) method, and c) compressed sensing (CS) method were studied and applied to the images of a computer–simulated “Shepp-Logan” phantom and a physical CATPHAN phantom. Up to 20% additive Gaussian noise was added to the Shepp-Logan phantom. The CATPHAN phantom was scanned by a Varian OBI system with 100 kVp, 4 ms and 20 mA. For comparing the performance of these algorithms, peak signal-to-noise ratio (PSNR) of the denoised images was computed. Results: The algorithms were shown to have the potential in reducing the noise level for low-dose CBCT images. For Shepp-Logan phantom, an improvement of PSNR of 2 dB, 3.1 dB and 4 dB was observed using PWLS, TV and CS respectively, while for CATPHAN, the improvement was 1.2 dB, 1.8 dB and 2.1 dB, respectively. Conclusion: Penalized weighted least square, total variation and compressed sensing methods were studied and compared for reducing the noise on a simulated phantom and a physical phantom scanned by low-dose CBCT. The techniques have shown promising results for noise reduction in terms of PSNR improvement. However, reducing the noise without compromising the smoothness and resolution of the image needs more extensive research.
NASA Astrophysics Data System (ADS)
Meerburg, P. Daniel; Meyers, Joel; van Engelen, Alexander; Ali-Haïmoud, Yacine
2016-06-01
We study the degree to which the cosmic microwave background (CMB) can be used to constrain primordial non-Gaussianity involving one tensor and two scalar fluctuations, focusing on the correlation of one polarization B mode with two temperature modes. In the simplest models of inflation, the tensor-scalar-scalar primordial bispectrum is nonvanishing and is of the same order in slow-roll parameters as the scalar-scalar-scalar bispectrum. We calculate the ⟨B T T ⟩ correlation arising from a primordial tensor-scalar-scalar bispectrum, and show that constraints from an experiment like CMB-Stage IV using this observable are more than an order of magnitude better than those on the same primordial coupling obtained from temperature measurements alone. We argue that B -mode non-Gaussianity opens up an as-yet-unexplored window into the early Universe, demonstrating that significant information on primordial physics remains to be harvested from CMB anisotropies.
Quantum Fidelity for Arbitrary Gaussian States.
Banchi, Leonardo; Braunstein, Samuel L; Pirandola, Stefano
2015-12-31
We derive a computable analytical formula for the quantum fidelity between two arbitrary multimode Gaussian states which is simply expressed in terms of their first- and second-order statistical moments. We also show how such a formula can be written in terms of symplectic invariants and used to derive closed forms for a variety of basic quantities and tools, such as the Bures metric, the quantum Fisher information, and various fidelity-based bounds. Our result can be used to extend the study of continuous-variable protocols, such as quantum teleportation and cloning, beyond the current one-mode or two-mode analyses, and paves the way to solve general problems in quantum metrology and quantum hypothesis testing with arbitrary multimode Gaussian resources.
A Fast Incremental Gaussian Mixture Model
Pinto, Rafael Coimbra; Engel, Paulo Martins
2015-01-01
This work builds upon previous efforts in online incremental learning, namely the Incremental Gaussian Mixture Network (IGMN). The IGMN is capable of learning from data streams in a single-pass by improving its model after analyzing each data point and discarding it thereafter. Nevertheless, it suffers from the scalability point-of-view, due to its asymptotic time complexity of O(NKD3) for N data points, K Gaussian components and D dimensions, rendering it inadequate for high-dimensional data. In this work, we manage to reduce this complexity to O(NKD2) by deriving formulas for working directly with precision matrices instead of covariance matrices. The final result is a much faster and scalable algorithm which can be applied to high dimensional tasks. This is confirmed by applying the modified algorithm to high-dimensional classification datasets. PMID:26444880
Fock expansion of multimode pure Gaussian states
Cariolaro, Gianfranco; Pierobon, Gianfranco
2015-12-15
The Fock expansion of multimode pure Gaussian states is derived starting from their representation as displaced and squeezed multimode vacuum states. The approach is new and appears to be simpler and more general than previous ones starting from the phase-space representation given by the characteristic or Wigner function. Fock expansion is performed in terms of easily evaluable two-variable Hermite–Kampé de Fériet polynomials. A relatively simple and compact expression for the joint statistical distribution of the photon numbers in the different modes is obtained. In particular, this result enables one to give a simple characterization of separable and entangled states, as shown for two-mode and three-mode Gaussian states.
Large Non-Gaussianity in Axion Inflation
Barnaby, Neil; Peloso, Marco
2011-05-06
The inflationary paradigm has enjoyed phenomenological success; however, a compelling particle physics realization is still lacking. Axions are among the best-motivated inflaton candidates, since the flatness of their potential is naturally protected by a shift symmetry. We reconsider the cosmological perturbations in axion inflation, consistently accounting for the coupling to gauge fields c{phi}FF-tilde, which is generically present in these models. This coupling leads to production of gauge quanta, which provide a new source of inflaton fluctuations, {delta}{phi}. For c > or approx. 10{sup 2}M{sub p}{sup -1}, these dominate over the vacuum fluctuations, and non-Gaussianity exceeds the current observational bound. This regime is typical for concrete realizations that admit a UV completion; hence, large non-Gaussianity is easily obtained in minimal and natural realizations of inflation.
Gaussian quadrature for multiple orthogonal polynomials
NASA Astrophysics Data System (ADS)
Coussement, Jonathan; van Assche, Walter
2005-06-01
We study multiple orthogonal polynomials of type I and type II, which have orthogonality conditions with respect to r measures. These polynomials are connected by their recurrence relation of order r+1. First we show a relation with the eigenvalue problem of a banded lower Hessenberg matrix Ln, containing the recurrence coefficients. As a consequence, we easily find that the multiple orthogonal polynomials of type I and type II satisfy a generalized Christoffel-Darboux identity. Furthermore, we explain the notion of multiple Gaussian quadrature (for proper multi-indices), which is an extension of the theory of Gaussian quadrature for orthogonal polynomials and was introduced by Borges. In particular, we show that the quadrature points and quadrature weights can be expressed in terms of the eigenvalue problem of Ln.
Quantum Fidelity for Arbitrary Gaussian States
NASA Astrophysics Data System (ADS)
Banchi, Leonardo; Braunstein, Samuel L.; Pirandola, Stefano
2015-12-01
We derive a computable analytical formula for the quantum fidelity between two arbitrary multimode Gaussian states which is simply expressed in terms of their first- and second-order statistical moments. We also show how such a formula can be written in terms of symplectic invariants and used to derive closed forms for a variety of basic quantities and tools, such as the Bures metric, the quantum Fisher information, and various fidelity-based bounds. Our result can be used to extend the study of continuous-variable protocols, such as quantum teleportation and cloning, beyond the current one-mode or two-mode analyses, and paves the way to solve general problems in quantum metrology and quantum hypothesis testing with arbitrary multimode Gaussian resources.
Energy pumping in electrical circuits under avalanche noise
NASA Astrophysics Data System (ADS)
Kanazawa, Kiyoshi; Sagawa, Takahiro; Hayakawa, Hisao
2014-07-01
We theoretically study energy pumping processes in an electrical circuit with avalanche diodes, where non-Gaussian athermal noise plays a crucial role. We show that a positive amount of energy (work) can be extracted by an external manipulation of the circuit in a cyclic way, even when the system is spatially symmetric. We discuss the properties of the energy pumping process for both quasistatic and finite-time cases, and analytically obtain formulas for the amounts of the work and the power. Our results demonstrate the significance of the non-Gaussianity in energetics of electrical circuits.
Energy pumping in electrical circuits under avalanche noise.
Kanazawa, Kiyoshi; Sagawa, Takahiro; Hayakawa, Hisao
2014-07-01
We theoretically study energy pumping processes in an electrical circuit with avalanche diodes, where non-Gaussian athermal noise plays a crucial role. We show that a positive amount of energy (work) can be extracted by an external manipulation of the circuit in a cyclic way, even when the system is spatially symmetric. We discuss the properties of the energy pumping process for both quasistatic and finite-time cases, and analytically obtain formulas for the amounts of the work and the power. Our results demonstrate the significance of the non-Gaussianity in energetics of electrical circuits.
Entanglement Rate for Gaussian Continuous Variable Beams
2016-08-24
e.g. when cavities are involved. To exemplify itsmeaning and potential, we apply it to a four-mode optomechanical setup that enables the simultaneous up...natural characteristics of such a source is obviously the rate at which it generates entanglement. If the source sends out pairs of entangled particles...entanglement rate in such nontrivial situations. It will turn out that our general definition, when applied to stationaryGaussianCVbeams, gives rise to a
Non-Markovianity of Gaussian Channels.
Torre, G; Roga, W; Illuminati, F
2015-08-14
We introduce a necessary and sufficient criterion for the non-Markovianity of Gaussian quantum dynamical maps based on the violation of divisibility. The criterion is derived by defining a general vectorial representation of the covariance matrix which is then exploited to determine the condition for the complete positivity of partial maps associated with arbitrary time intervals. Such construction does not rely on the Choi-Jamiolkowski representation and does not require optimization over states.
Entropic Fluctuations in Gaussian Dynamical Systems
NASA Astrophysics Data System (ADS)
Jakšić, V.; Pillet, C.-A.; Shirikyan, A.
2016-06-01
We study nonequilibrium statistical mechanics of a Gaussian dynamical system and compute in closed form the large deviation functionals describing the fluctuations of the entropy production observable with respect to the reference state and the nonequilibrium steady state. The entropy production observable of this model is an unbounded function on the phase space, and its large deviation functionals have a surprisingly rich structure. We explore this structure in some detail.
Airframe noise: A design and operating problem
NASA Technical Reports Server (NTRS)
Hardin, J. C.
1976-01-01
A critical assessment of the state of the art in airframe noise is presented. Full-scale data on the intensity, spectra, and directivity of this noise source are evaluated in light of the comprehensive theory developed by Ffowcs Williams and Hawkings. Vibration of panels on the aircraft is identified as a possible additional source of airframe noise. The present understanding and methods for prediction of other component sources - airfoils, struts, and cavities - are discussed. Operating problems associated with airframe noise as well as potential design methods for airframe noise reduction are identified.
NASA Astrophysics Data System (ADS)
Fidell, Sandy
The primary effects of community noise on residential populations are speech interference, sleep disturbance, and annoyance. This chapter focuses on transportation noise in general and on aircraft noise in particular because aircraft noise is one of the most prominent community noise sources, because airport/community controversies are often the most contentious and widespread, and because industrial and other specialized formsofcommunitynoise generally posemorelocalized problems.
Unitarily localizable entanglement of Gaussian states
Serafini, Alessio; Adesso, Gerardo; Illuminati, Fabrizio
2005-03-01
We consider generic (mxn)-mode bipartitions of continuous-variable systems, and study the associated bisymmetric multimode Gaussian states. They are defined as (m+n)-mode Gaussian states invariant under local mode permutations on the m-mode and n-mode subsystems. We prove that such states are equivalent, under local unitary transformations, to the tensor product of a two-mode state and of m+n-2 uncorrelated single-mode states. The entanglement between the m-mode and the n-mode blocks can then be completely concentrated on a single pair of modes by means of local unitary operations alone. This result allows us to prove that the PPT (positivity of the partial transpose) condition is necessary and sufficient for the separability of (m+n)-mode bisymmetric Gaussian states. We determine exactly their negativity and identify a subset of bisymmetric states whose multimode entanglement of formation can be computed analytically. We consider explicit examples of pure and mixed bisymmetric states and study their entanglement scaling with the number of modes.
NASA Technical Reports Server (NTRS)
Hubbard, Harvey H. (Editor)
1993-01-01
In the conference over 100 papers were presented in eight sessions: (1) Emission: Noise Sources; (2) Physical Phenomena; (3) Noise ControlElements; (4) Vibration and Shock: Generation, Transmission, Isolation, and Reduction; (5) Immission: Physical Aspects of Environmental Noise; (6) Immission: Effects of Noise; (7) Analysis; and (8) Requirements. In addition, the distinguished lecture series included presentations on the High Speed Civil Transport and on research from the United Kingdom on aircraft noise effects.
Latifoğlu, Fatma
2013-09-01
In this study a novel approach based on 2D FIR filters is presented for denoising digital images. In this approach the filter coefficients of 2D FIR filters were optimized using the Artificial Bee Colony (ABC) algorithm. To obtain the best filter design, the filter coefficients were tested with different numbers (3×3, 5×5, 7×7, 11×11) and connection types (cascade and parallel) during optimization. First, the speckle noise with variances of 1, 0.6, 0.8 and 0.2 respectively was added to the synthetic test image. Later, these noisy images were denoised with both the proposed approach and other well-known filter types such as Gaussian, mean and average filters. For image quality determination metrics such as mean square error (MSE), peak signal-to-noise ratio (PSNR) and signal-to-noise ratio (SNR) were used. Even in the case of noise having maximum variance (the most noisy), the proposed approach performed better than other filtering methods did on the noisy test images. In addition to test images, speckle noise with a variance of 1 was added to a fetal ultrasound image, and this noisy image was denoised with very high PSNR and SNR values. The performance of the proposed approach was also tested on several clinical ultrasound images such as those obtained from ovarian, abdomen and liver tissues. The results of this study showed that the 2D FIR filters designed based on ABC optimization can eliminate speckle noise quite well on noise added test images and intrinsically noisy ultrasound images.
Local Gaussian operations can enhance continuous-variable entanglement distillation
Zhang Shengli; Loock, Peter van
2011-12-15
Entanglement distillation is a fundamental building block in long-distance quantum communication. Though known to be useless on their own for distilling Gaussian entangled states, local Gaussian operations may still help to improve non-Gaussian entanglement distillation schemes. Here we show that by applying local squeezing operations both the performance and the efficiency of existing distillation protocols can be enhanced. We find that such an enhancement through local Gaussian unitaries can be obtained even when the initially shared Gaussian entangled states are mixed, as, for instance, after their distribution through a lossy-fiber communication channel.
Transport driven by biharmonic forces: Impact of correlated thermal noise
NASA Astrophysics Data System (ADS)
Machura, L.; Łuczka, J.
2010-09-01
We study an inertial Brownian particle moving in a symmetric periodic substrate, driven by a zero-mean biharmonic force and correlated thermal noise. The Brownian motion is described in terms of a generalized Langevin equation with an exponentially correlated Gaussian noise term, obeying the fluctuation-dissipation theorem. We analyze impact of nonzero correlation time of thermal noise on transport properties of the Brownian particle. We identify regimes where the increase of the correlation time intensifies long-time transport of the Brownian particle. The opposite effect is also found: longer correlation time reduces the stationary velocity of the particle. The correlation time induced multiple current reversal is detected. We reveal that thermal noise of nonzero correlation time can radically enhance long-time velocity of the Brownian particle in regimes where in the white noise limit the velocity is extremely small. All transport properties can be tested in the setup consisting of a resistively and capacitively shunted Josephson junction device.
Numerical Fitting of Molecular Properties to Hermite Gaussians
Cisneros, G. Andrés; Elking, Dennis; Piquemal, Jean-Philip; Darden, Thomas A.
2008-01-01
A procedure is presented to fit gridded molecular properties to auxiliary basis sets (ABSs) of Hermite Gaussians, analogous to the density fitting (DF) method (Dunlap; et al. J. Chem. Phys. 1979, 71, 4993). In this procedure, the ab initio calculated properties (density, electrostatic potential, and/or electric field) are fitted via a linear- or nonlinear-least-squares procedure to auxiliary basis sets (ABS). The calculated fitting coefficients from the numerical grids are shown to be more robust than analytic density fitting due to the neglect of the core contributions. The fitting coefficients are tested by calculating intermolecular Coulomb and exchange interactions for a set of dimers. It is shown that the numerical instabilities observed in DF are caused by the attempt of the ABS to fit the core contributions. In addition, this new approach allows us to reduce the number of functions required to obtain an accurate fit. This results in decreased computational cost, which is shown by calculating the Coulomb energy of a 4096 water box in periodic boundary conditions. Using atom centered Hermite Gaussians, this calculation is only 1 order of magnitude slower than conventional atom–centered point charges. PMID:17973464
Electronically nonadiabatic wave packet propagation using frozen Gaussian scattering
Kondorskiy, Alexey D.; Nanbu, Shinkoh
2015-09-21
We present an approach, which allows to employ the adiabatic wave packet propagation technique and semiclassical theory to treat the nonadiabatic processes by using trajectory hopping. The approach developed generates a bunch of hopping trajectories and gives all additional information to incorporate the effect of nonadiabatic coupling into the wave packet dynamics. This provides an interface between a general adiabatic frozen Gaussian wave packet propagation method and the trajectory surface hopping technique. The basic idea suggested in [A. D. Kondorskiy and H. Nakamura, J. Chem. Phys. 120, 8937 (2004)] is revisited and complemented in the present work by the elaboration of efficient numerical algorithms. We combine our approach with the adiabatic Herman-Kluk frozen Gaussian approximation. The efficiency and accuracy of the resulting method is demonstrated by applying it to popular benchmark model systems including three Tully’s models and 24D model of pyrazine. It is shown that photoabsorption spectrum is successfully reproduced by using a few hundreds of trajectories. We employ the compact finite difference Hessian update scheme to consider feasibility of the ab initio “on-the-fly” simulations. It is found that this technique allows us to obtain the reliable final results using several Hessian matrix calculations per trajectory.
Tridiagonal realization of the antisymmetric Gaussian {beta}-ensemble
Dumitriu, Ioana; Forrester, Peter J.
2010-09-15
The Householder reduction of a member of the antisymmetric Gaussian unitary ensemble gives an antisymmetric tridiagonal matrix with all independent elements. The random variables permit the introduction of a positive parameter {beta}, and the eigenvalue probability density function of the corresponding random matrices can be computed explicitly, as can the distribution of (q{sub i}), the first components of the eigenvectors. Three proofs are given. One involves an inductive construction based on bordering of a family of random matrices which are shown to have the same distributions as the antisymmetric tridiagonal matrices. This proof uses the Dixon-Anderson integral from Selberg integral theory. A second proof involves the explicit computation of the Jacobian for the change of variables between real antisymmetric tridiagonal matrices, its eigenvalues, and (q{sub i}). The third proof maps matrices from the antisymmetric Gaussian {beta}-ensemble to those realizing particular examples of the Laguerre {beta}-ensemble. In addition to these proofs, we note some simple properties of the shooting eigenvector and associated Pruefer phases of the random matrices.
On the orbital stability of Gaussian solitary waves in the log-KdV equation
NASA Astrophysics Data System (ADS)
Carles, Rémi; Pelinovsky, Dmitry
2014-12-01
We consider the logarithmic Korteweg-de Vries (log-KdV) equation, which models solitary waves in anharmonic chains with Hertzian interaction forces. By using an approximating sequence of global solutions of the regularized generalized KdV equation in H^1({R}) with conserved L2 norm and energy, we construct a weak global solution of the log-KdV equation in a subset of H^1({R}) . This construction yields conditional orbital stability of Gaussian solitary waves of the log-KdV equation, provided that uniqueness and continuous dependence of the constructed solution holds. Furthermore, we study the linearized log-KdV equation at the Gaussian solitary wave and prove that the associated linearized operator has a purely discrete spectrum consisting of simple purely imaginary eigenvalues in addition to the double zero eigenvalue. The eigenfunctions, however, do not decay like Gaussian functions but have algebraic decay. Using numerical approximations, we show that the Gaussian initial data do not spread out but produce visible radiation at the left slope of the Gaussian-like pulse in the time evolution of the linearized log-KdV equation.
Experimental Studies with Spatial Gaussian-Cut Laser for the LCLS Photocathode Gun
Zhou, F.; Brachmann, A.; Emma, P.; Gilevich, S.; Huang, Z.; /SLAC
2011-12-13
To simplify the LCLS operation and further enhance the injector performances, we are evaluating the various parameters including the photocathode drive laser system. Extensive simulations show that both the projected and time-sliced emittances with spatial Gaussian profiles having reasonable tail-cut are better than those with uniform one. The simulated results are also supported by theoretical analyses. In the LCLS, the spatial uniform or Gaussian-cut laser profiles are conveniently obtained by adjusting the optics of the telescope upstream of an iris, used to define laser size on the cathode. Preliminary beam studies at the LCLS injector show that both the projected and time-sliced emittances with spatial Gaussian-cut laser are almost as good as, although not better than, those with uniform one. In addition, the laser transmission through the iris with the Gaussian-cut profile is twice with uniform one, which can significantly ease LCLS copper cathode/laser operations and thus improve the LCLS operation efficiency. More beam studies are planned to measure FEL performances with the Gaussian-cut in comparison with the uniform one. All simulations and measurements are presented in the paper.
NASA Astrophysics Data System (ADS)
Groeneweg, John F.; Sofrin, Thomas G.; Rice, Edward J.; Gliebe, Phillip R.
1991-08-01
Summarized here are key advances in experimental techniques and theoretical applications which point the way to a broad understanding and control of turbomachinery noise. On the experimental side, the development of effective inflow control techniques makes it possible to conduct, in ground based facilities, definitive experiments in internally controlled blade row interactions. Results can now be valid indicators of flight behavior and can provide a firm base for comparison with analytical results. Inflow control coupled with detailed diagnostic tools such as blade pressure measurements can be used to uncover the more subtle mechanisms such as rotor strut interaction, which can set tone levels for some engine configurations. Initial mappings of rotor wake-vortex flow fields have provided a data base for a first generation semiempirical flow disturbance model. Laser velocimetry offers a nonintrusive method for validating and improving the model. Digital data systems and signal processing algorithms are bringing mode measurement closer to a working tool that can be frequently applied to a real machine such as a turbofan engine. On the analytical side, models of most of the links in the chain from turbomachine blade source to far field observation point have been formulated. Three dimensional lifting surface theory for blade rows, including source noncompactness and cascade effects, blade row transmission models incorporating mode and frequency scattering, and modal radiation calculations, including hybrid numerical-analytical approaches, are tools which await further application.
NASA Technical Reports Server (NTRS)
Groeneweg, John F.; Sofrin, Thomas G.; Rice, Edward J.; Gliebe, Phillip R.
1991-01-01
Summarized here are key advances in experimental techniques and theoretical applications which point the way to a broad understanding and control of turbomachinery noise. On the experimental side, the development of effective inflow control techniques makes it possible to conduct, in ground based facilities, definitive experiments in internally controlled blade row interactions. Results can now be valid indicators of flight behavior and can provide a firm base for comparison with analytical results. Inflow control coupled with detailed diagnostic tools such as blade pressure measurements can be used to uncover the more subtle mechanisms such as rotor strut interaction, which can set tone levels for some engine configurations. Initial mappings of rotor wake-vortex flow fields have provided a data base for a first generation semiempirical flow disturbance model. Laser velocimetry offers a nonintrusive method for validating and improving the model. Digital data systems and signal processing algorithms are bringing mode measurement closer to a working tool that can be frequently applied to a real machine such as a turbofan engine. On the analytical side, models of most of the links in the chain from turbomachine blade source to far field observation point have been formulated. Three dimensional lifting surface theory for blade rows, including source noncompactness and cascade effects, blade row transmission models incorporating mode and frequency scattering, and modal radiation calculations, including hybrid numerical-analytical approaches, are tools which await further application.
On the relationship between Gaussian stochastic blockmodels and label propagation algorithms
NASA Astrophysics Data System (ADS)
Zhang, Junhao; Chen, Tongfei; Hu, Junfeng
2015-03-01
The problem of community detection has received great attention in recent years. Many methods have been proposed to discover communities in networks. In this paper, we propose a Gaussian stochastic blockmodel that uses Gaussian distributions to fit weight of edges in networks for non-overlapping community detection. The maximum likelihood estimation of this model has the same objective function as general label propagation with node preference. The node preference of a specific vertex turns out to be a value proportional to the intra-community eigenvector centrality (the corresponding entry in principal eigenvector of the adjacency matrix of the subgraph inside that vertex's community) under maximum likelihood estimation. Additionally, the maximum likelihood estimation of a constrained version of our model is highly related to another extension of the label propagation algorithm, namely, the label propagation algorithm under constraint. Experiments show that the proposed Gaussian stochastic blockmodel performs well on various benchmark networks.
NASA Technical Reports Server (NTRS)
Frehlich, Rod
1993-01-01
Calculations of the exact Cramer-Rao Bound (CRB) for unbiased estimates of the mean frequency, signal power, and spectral width of Doppler radar/lidar signals (a Gaussian random process) are presented. Approximate CRB's are derived using the Discrete Fourier Transform (DFT). These approximate results are equal to the exact CRB when the DFT coefficients are mutually uncorrelated. Previous high SNR limits for CRB's are shown to be inaccurate because the discrete summations cannot be approximated with integration. The performance of an approximate maximum likelihood estimator for mean frequency approaches the exact CRB for moderate signal to noise ratio and moderate spectral width.
Gaussian process regression for sensor networks under localization uncertainty
Jadaliha, M.; Xu, Yunfei; Choi, Jongeun; Johnson, N.S.; Li, Weiming
2013-01-01
In this paper, we formulate Gaussian process regression with observations under the localization uncertainty due to the resource-constrained sensor networks. In our formulation, effects of observations, measurement noise, localization uncertainty, and prior distributions are all correctly incorporated in the posterior predictive statistics. The analytically intractable posterior predictive statistics are proposed to be approximated by two techniques, viz., Monte Carlo sampling and Laplace's method. Such approximation techniques have been carefully tailored to our problems and their approximation error and complexity are analyzed. Simulation study demonstrates that the proposed approaches perform much better than approaches without considering the localization uncertainty properly. Finally, we have applied the proposed approaches on the experimentally collected real data from a dye concentration field over a section of a river and a temperature field of an outdoor swimming pool to provide proof of concept tests and evaluate the proposed schemes in real situations. In both simulation and experimental results, the proposed methods outperform the quick-and-dirty solutions often used in practice.
Error Thresholds in Single-Peak Gaussian Distributed Fitness Landscapes
NASA Astrophysics Data System (ADS)
Feng, Xiao-Li; Gu, Jian-Zhong; Li, Yu-Xiao; Zhuo, Yi-Zhong
2007-10-01
Based on the Eigen and Crow-Kimura models with a single-peak fitness landscape, we propose the fitness values of all sequence types to be Gaussian distributed random variables to incorporate the effects of the fluctuations of the fitness landscapes (noise of environments) and investigate the concentration distribution and error threshold of quasispecies by performing an ensemble average within this theoretical framework. We find that a small fluctuation of the fitness landscape causes only a slight change in the concentration distribution and error threshold, which implies that the error threshold is stable against small perturbations. However, for a sizable fluctuation, quite different from the previous deterministic models, our statistical results show that the transition from quasi-species to error catastrophe is not so sharp, indicating that the error threshold is located within a certain range and has a shift toward a larger value. Our results are qualitatively in agreement with the experimental data and provide a new implication for antiviral strategies.
NASA Astrophysics Data System (ADS)
Adesso, Gerardo; Serafini, Alessio; Illuminati, Fabrizio
2006-03-01
We present a complete analysis of the multipartite entanglement of three-mode Gaussian states of continuous-variable systems. We derive standard forms which characterize the covariance matrix of pure and mixed three-mode Gaussian states up to local unitary operations, showing that the local entropies of pure Gaussian states are bound to fulfill a relationship which is stricter than the general Araki-Lieb inequality. Quantum correlations can be quantified by a proper convex roof extension of the squared logarithmic negativity, the continuous-variable tangle, or contangle. We review and elucidate in detail the proof that in multimode Gaussian states the contangle satisfies a monogamy inequality constraint [G. Adesso and F. Illuminati, New J. Phys8, 15 (2006)]. The residual contangle, emerging from the monogamy inequality, is an entanglement monotone under Gaussian local operations and classical communications and defines a measure of genuine tripartite entanglements. We determine the analytical expression of the residual contangle for arbitrary pure three-mode Gaussian states and study in detail the distribution of quantum correlations in such states. This analysis yields that pure, symmetric states allow for a promiscuous entanglement sharing, having both maximum tripartite entanglement and maximum couplewise entanglement between any pair of modes. We thus name these states GHZ/W states of continuous-variable systems because they are simultaneous continuous-variable counterparts of both the GHZ and the W states of three qubits. We finally consider the effect of decoherence on three-mode Gaussian states, studying the decay of the residual contangle. The GHZ/W states are shown to be maximally robust against losses and thermal noise.