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Despite the broad application of the analytic wavelet transform (AWT), a systematic statistical characterization of its magnitude and phase as inhomogeneous random fields on the time-frequency domain when the input is a random process…

Statistics Theory · Mathematics 2025-12-23 Gi-Ren Liu , Yuan-Chung Sheu , Hau-Tieng Wu

The infinitesimal generator (fractional Laplacian) of a process obtained by subordinating a killed Brownian motion catches the power-law attenuation of wave propagation. This paper studies the numerical schemes for the stochastic wave…

Numerical Analysis · Mathematics 2021-02-23 Xing Liu , Weihua Deng

We consider the problem of fitting a parametric model to time-series data that are afflicted by correlated noise. The noise is represented by a sum of two stationary Gaussian processes: one that is uncorrelated in time, and another that has…

Earth and Planetary Astrophysics · Physics 2014-11-20 Joshua A. Carter , Joshua N. Winn

An averaging method is applied to derive effective approximation to the following singularly perturbed nonlinear stochastic damped wave equation \nu u_{tt}+u_t=\D u+f(u)+\nu^\alpha\dot{W} on an open bounded domain $D\subset\R^n$\,, $1\leq…

Analysis of PDEs · Mathematics 2015-05-28 Yan Lv , A. J. Roberts

This work introduces a wavelet neural network to learn a filter-bank specialized to fit non-stationary signals and improve interpretability and performance for digital signal processing. The network uses a wavelet transform as the first…

Machine Learning · Computer Science 2022-05-09 Jason Stock , Chuck Anderson

This paper provides central limit theorems for the wavelet packet decomposition of stationary band-limited random processes. The asymptotic analysis is performed for the sequences of the wavelet packet coefficients returned at the nodes of…

Information Theory · Computer Science 2009-10-26 Abdourrahmane Atto , Dominique Pastor

This work deals with exact solutions to the wave equations. We start by introducing the Non-Diffracting Waves (NDW), and by a definition of NDWs. Afterwards we recall -besides ordinary waves (gaussian beams, gaussian pulses)- the simplest…

The standard approaches to neural network implementation yield powerful function approximation capabilities but are limited in their abilities to learn meta representations and reason probabilistic uncertainties in their predictions.…

Machine Learning · Computer Science 2023-10-05 Saurav Jha , Dong Gong , Xuesong Wang , Richard E. Turner , Lina Yao

We study well-posedness of sweeping processes with stochastic perturbations generated by a fractional Brownian motion and convergence of associated numerical schemes. To this end, we first prove new existence, uniqueness and approximation…

Classical Analysis and ODEs · Mathematics 2015-05-07 Adrian Falkowski , Leszek Slominski

To overcome topological constraints and improve the expressiveness of normalizing flow architectures, Wu, K\"ohler and No\'e introduced stochastic normalizing flows which combine deterministic, learnable flow transformations with stochastic…

Machine Learning · Computer Science 2022-12-02 Paul Hagemann , Johannes Hertrich , Gabriele Steidl

This article is devoted to study stochastic lattice dynamical systems driven by a fractional Brownian motion with Hurst parameter $H\in(1/2,1)$. First of all, we investigate the existence and uniqueness of pathwise mild solutions to such…

Analysis of PDEs · Mathematics 2016-09-09 Hakima Bessaih , María J. Garrido-Atienza , Xiaoying Han , Björn Schmalfuß

We investigate thermodynamics of general nonequilibrium processes stopped at stochastic times. We propose a systematic strategy for constructing fluctuation-theorem-like martingales for each thermodynamic functional, yielding a family of…

Statistical Mechanics · Physics 2023-06-02 Haoran Yang , Hao Ge

Our simple but useful technique is using an integration by parts to split the stochastic convolution into two terms. We develop five applications for this technique. The first one is getting a uniform estimate of stochastic convolution of…

Probability · Mathematics 2012-01-24 Lihu Xu

A 2D Stochastic incompressible non-Newtonian fluids driven by fractional Bronwnian motion with Hurst parameter $H \in (1/2,1)$ is studied. The Wiener-type stochastic integrals are introduced for infinite-dimensional fractional Brownian…

Mathematical Physics · Physics 2011-07-15 Jin Li , Jianhua Huang

In this article, we consider the problem of estimating fractional processes based on noisy high-frequency data. Generalizing the idea of pre-averaging to a fractional setting, we exhibit a sequence of consistent estimators for the unknown…

Statistics Theory · Mathematics 2026-01-14 David Chen , Yu Cheng , Carsten Chong , Pierre Gentine , Wangdong Jia , Bryce Monier , Shiyang Shen

In a previous paper, we studied the ergodic properties of an Euler scheme of a stochastic differential equation with a Gaussian additive noise in order to approximate the stationary regime of such equation. We now consider the case of…

Probability · Mathematics 2013-11-20 Serge Cohen , Fabien Panloup , Samy Tindel

This study derived the vertical distribution of streamwise velocity in wide open channels by maximizing Tsallis entropy, in accordance with the maximum entropy principle, subject to the total probability rule and the conservation of mass,…

Computational Physics · Physics 2024-03-04 Manotosh Kumbhakar , Rajendra K. Ray , Suvra Kanti Chakraborty , Koeli Ghoshal , Vijay P. Singh

We analyze the stochastic thermodynamics of systems with continuous space of states. The evolution equation, the rate of entropy production, and other results are obtained by a continuous time limit of a discrete time formulation. We point…

Statistical Mechanics · Physics 2020-08-27 Mário J. de Oliveira

Let $a$ be a finite signed measure on $[-r, 0]$ with $r \in (0, \infty)$. Consider a stochastic process $(X^{(\vartheta)}(t))_{t\in[-r,\infty)}$ given by a linear stochastic delay differential equation \[ \mathrm{d} X^{(\vartheta)}(t) =…

Statistics Theory · Mathematics 2025-01-28 János Marcell Benke , Gyula Pap

For signals belonging to balls in smoothness classes and noise with enough moments, the asymptotic behavior of the minimax quadratic risk among soft-threshold estimates is investigated. In turn, these results, combined with a median…

Statistics Theory · Mathematics 2016-08-16 R. Averkamp , C. Houdré