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Sparse linear inverse problems appear in a variety of settings, but often the noise contaminating observations cannot accurately be described as bounded by or arising from a Gaussian distribution. Poisson observations in particular are a…

Statistics Theory · Mathematics 2018-02-14 Xin Jiang , Patricia Reynaud-Bouret , Vincent Rivoirard , Laure Sansonnet , Rebecca Willett

In this paper, we consider stochastic Schroedinger equations with two-dimensional white noise. Such equations are used to describe the evolution of an open quantum system undergoing a process of continuous measurement. Representations are…

Mathematical Physics · Physics 2011-08-17 J. Gough , O. O. Obrezkov , O. G. Smolyanov

Stochastic resonance is a phenomenon where a noise of appropriate intensity enhances the input signal strength. In this work, by employing the recently developed convex optimization methods in the context of dynamical systems and stochastic…

Dynamical Systems · Mathematics 2023-09-22 Minjae Cho

A solvable model of noise effects on globally coupled limit cycle oscillators is proposed. The oscillators are under the influence of independent and additive white Gaussian noise. The averaged motion equation of the system with infinitely…

Chaotic Dynamics · Physics 2019-09-20 Keiji Okumura , Akihisa Ichiki

In this paper we study the linear stochastic heat equation, also known as parabolic Anderson model, in multidimension driven by a Gaussian noise which is white in time and it has a correlated spatial covariance. Examples of such covariance…

Probability · Mathematics 2016-03-22 Jingyu Huang , Khoa Lê , David Nualart

We consider the problem of controlling an unstable scalar linear plant over a power-constrained additive white Gaussian noise (AWGN) channel, where the controller/receiver has access to an additional noisy measurement of the state of the…

Systems and Control · Electrical Eng. & Systems 2020-04-09 Omri Lev , Anatoly Khina

A continuous approximation framework for non-linear stochastic as well as deterministic discrete maps is developed. For the stochastic map with uncorelated Gaussian noise, by successively applying the It\^o lemma, we obtain a Langevin type…

Statistical Mechanics · Physics 2017-10-25 David A. Kessler , Stanislav Burov

We analyze the influence of classical Gaussian noise on Landau-Zener transitions during a two-level crossing in a time-dependent regular external field. Transition probabilities and coherence factors become random due to the noise. We…

Statistical Mechanics · Physics 2009-11-10 V. L. Pokrovsky , S. Scheidl

Gravitational wave backgrounds generate correlated noises to separated detectors. This correlation can induce statistical losses to actual detector networks, compared with idealized noise-independent networks. Assuming that the backgrounds…

General Relativity and Quantum Cosmology · Physics 2021-09-29 Naoki Seto

We study analytically and numerically the problem of a nonlinear mechanical oscillator with additive noise in the absence of damping. We show that the amplitude, the velocity and the energy of the oscillator grow algebraically with time.…

Statistical Mechanics · Physics 2009-11-07 K. Mallick , P. Marcq

The multivariate linear regression model with shuffled data and additive Gaussian noise arises in various correspondence estimation and matching problems. Focusing on the denoising aspect of this problem, we provide a characterization the…

Machine Learning · Statistics 2017-04-26 Ashwin Pananjady , Martin J. Wainwright , Thomas A. Courtade

Asymptotic energy-distortion performance of zero-delay communication scenarios under additive white Gaussian noise is investigated. Using high-resolution analysis for quantizer design, the higher-order term in the logarithm of the…

Information Theory · Computer Science 2018-01-01 Ceren Sevinç , Ertem Tuncel

We study the singular stochastic wave equation on $\mathbb T^2$, with a cubic nonlinearity and Gaussian rough Mat\'ern forcing (a Fourier multiplier of order $\alpha>0$ applied to space-time white noise) and establish local well-posedness…

Probability · Mathematics 2025-10-15 Xue-Mei Li , Xianfeng Ren

Residual variance and the signal-to-noise ratio are important quantities in many statistical models and model fitting procedures. They play an important role in regression diagnostics, in determining the performance limits in estimation and…

Methodology · Statistics 2012-09-04 Lee H. Dicker

We report the experimental verification of noise-enhanced logic behaviour in an electronic analog of a synthetic genetic network, composed of two repressors and two constitutive promoters. We observe good agreement between circuit…

Biological Physics · Physics 2014-02-19 Edward H. Hellen , Syamal K. Dana , Jurgen Kurths , Elizabeth Kehler , Sudeshna Sinha

In this paper we analyze, for a model of linear regression with gaussian covariates, the performance of a Bayesian estimator given by the mean of a log-concave posterior distribution with gaussian prior, in the high-dimensional limit where…

Probability · Mathematics 2021-11-12 Jean Barbier , Wei-Kuo Chen , Dmitry Panchenko , Manuel Sáenz

We use white Gaussian noise as a test signal for single-mode and multimode transmission links and estimate the link capacity based on a calculation of mutual information. We also extract the complex amplitude channel estimations and…

This paper considers a noisy data structure recovery problem. The goal is to investigate the following question: Given a noisy observation of a permuted data set, according to which permutation was the original data sorted? The focus is on…

Information Theory · Computer Science 2020-11-24 Minoh Jeong , Alex Dytso , Martina Cardone , H. Vincent Poor

Some intriging connections between the properties of nonlinear noise driven systems and the nonlinear dynamics of a particular set of Hamilton's equation are discussed. A large class of Fokker-Planck Equations, like the Schr\"odinger…

chao-dyn · Physics 2009-10-22 Mark M. Millonas

In the problem of learning mixtures of linear regressions, the goal is to learn a collection of signal vectors from a sequence of (possibly noisy) linear measurements, where each measurement is evaluated on an unknown signal drawn uniformly…

Machine Learning · Computer Science 2019-11-01 Akshay Krishnamurthy , Arya Mazumdar , Andrew McGregor , Soumyabrata Pal