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In this paper we consider the two-dimensional stochastic Gross-Pitaevskii equation, which is a model to describe Bose-Einstein condensation at positive temperature. The equation is a complex Ginzburg-Landau equation with a harmonic…

Probability · Mathematics 2021-01-29 Anne de Bouard , Arnaud Debussche , Reika Fukuizumi

In this paper, we consider the strong convergence of the time-space fractional diffusion equation driven by fractional Gaussion noise with Hurst index $H\in(\frac{1}{2},1)$. A sharp regularity estimate of the mild solution and the numerical…

Numerical Analysis · Mathematics 2021-01-07 Daxin Nie , Weihua Deng

Additive or multiplicative stationary noise recently became an important issue in applied fields such as microscopy or satellite imaging. Relatively few works address the design of dedicated denoising methods compared to the usual white…

Computer Vision and Pattern Recognition · Computer Science 2013-07-18 Jérôme Fehrenbach , Pierre Weiss

In this paper we introduce and study a new feature-preserving nonlinear anisotropic diffusion for denoising signals. The proposed partial differential equation is based on a novel diffusivity coefficient that uses a nonlocal automatically…

Analysis of PDEs · Mathematics 2019-07-23 Giacomo Aletti , Monica Moroni , Giovanni Naldi

We study the two-dimensional wave equation with cubic nonlinearity posed on $\mathbb R^2$, with space-time white noise forcing. After a suitable renormalisation of the nonlinearity, we prove global well-posedness for this equation for…

Analysis of PDEs · Mathematics 2021-09-07 Leonardo Tolomeo

Geographical and Temporal Weighted Regression (GTWR) model is an important local technique for exploring spatial heterogeneity in data relationships, as well as temporal dependence due to its high fitting capacity when it comes to real…

Methodology · Statistics 2023-09-21 Héctor Araya , Lisandro Fermín , Silfrido Gómez , Tania Roa , Soledad Torres

Fractional Gaussian noise models the time series with long-range dependence; when the Hurst index $H>1/2$, it has positive correlation reflecting a persistent autocorrelation structure. This paper studies the numerical method for solving…

Numerical Analysis · Mathematics 2020-07-29 Daxin Nie , Jing Sun , Weihua Deng

We present and study an explicit exponential integrator for parabolic SPDEs in any dimension driven by a Gaussian noise which is white in time and with spatial correlation given by a Riesz kernel. Under assumptions on the coefficients of…

Numerical Analysis · Mathematics 2026-02-20 Charles-Edouard Bréhier , David Cohen , Lluís Quer-Sardanyons , Johan Ulander

This paper studies the linear stochastic partial differential equation of fractional orders both in time and space variables $\left(\partial^\beta + \frac{\nu}{2} (-\Delta)^{\alpha/2} \right) u(t,x)= \lambda u(t,x) \dot{W}(t,x)$, where…

Probability · Mathematics 2016-02-19 Le Chen , Guannan Hu , Yaozhong Hu , Jingyu Huang

In this article, we introduce a L\'evy analogue of the spatially homogeneous Gaussian noise of Dalang (1999), and we construct a stochastic integral with respect to this noise. The spatial covariance of the noise is given by a tempered…

Probability · Mathematics 2013-08-01 Raluca Balan

In this paper we establish the optimal regularity estimates for the Cauchy problem of stochastic kinetic equations with random coefficients in anisotropic Besov spaces. As applications, we study the nonlinear filtering problem for a…

Probability · Mathematics 2021-03-04 Xiaolong Zhang , Xicheng Zhang

We study the convective wave equation in two space dimension driven by spatially homogeneous Gaussian noise. The existence of the real-valued solution is proved by providing a necessary and sufficient condition of Gaussian noise source. Our…

Probability · Mathematics 2014-12-09 Sang-Hyeon Park , Imbo Sim

We propose localized spectral estimators for the quadratic covariation and the spot covolatility of diffusion processes which are observed discretely with additive observation noise. The eligibility of this approach to lead to an…

Statistics Theory · Mathematics 2015-03-19 Markus Bibinger , Markus Reiß

In this article, we consider the stochastic wave and heat equations driven by a Gaussian noise which is spatially homogeneous and behaves in time like a fractional Brownian motion with Hurst index $H>1/2$. The solutions of these equations…

Probability · Mathematics 2016-03-31 Raluca M. Balan , Daniel Conus

In this article, we consider the stochastic wave and heat equations on $\mathbb{R}$ with non-vanishing initial conditions, driven by a Gaussian noise which is white in time and behaves in space like a fractional Brownian motion of index…

Probability · Mathematics 2014-07-16 Raluca Balan , Maria Jolis , Lluis Quer-Sardanyons

In this paper, we consider nonlinear diffusion processes driven by space-time white noises, which have an interpretation in terms of partial differential equations. For a specific choice of coefficients, they correspond to the Landau…

Probability · Mathematics 2007-05-23 Joaquin Fontbona , Helene Guerin , Sylvie Meleard

We study the effect of Gaussian perturbations on a class of model hyperbolic partial differential equations with double symplectic characteristics in low spatial dimensions, extending some recent work in [5]. The coefficients of our partial…

Probability · Mathematics 2024-09-04 Enrico Bernardi , Leonardo Marconi

In this article, we study a $d$-dimensional stochastic quadratic nonlinear Schr\"{o}dinger equation (SNLS), driven by a fractional derivative (of order $-\alpha<0$) of a space-time white noise: $$\left\{ \begin{array}{l}i\partial_t u-\Delta…

Analysis of PDEs · Mathematics 2022-04-07 Nicolas Schaeffer

We consider the problem of estimating unknown parameters in stochastic differential equations driven by colored noise, which we model as a sequence of Gaussian stationary processes with decreasing correlation time. We aim to infer…

Numerical Analysis · Mathematics 2024-12-30 Grigorios A. Pavliotis , Sebastian Reich , Andrea Zanoni

Gaussian random fields with Mat\'ern covariance functions are popular models in spatial statistics and machine learning. In this work, we develop a spatio-temporal extension of the Gaussian Mat\'ern fields formulated as solutions to a…

Methodology · Statistics 2023-04-06 Finn Lindgren , Haakon Bakka , David Bolin , Elias Krainski , Håvard Rue