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We study quasilinear parabolic stochastic partial differential equations with general multiplicative noise on a bounded domain in $\mathbb{R}^{d}$, with homogeneous Dirichlet boundary condition. We establish the existence and uniqueness of…

Probability · Mathematics 2023-10-26 Mengzi Xie

This paper investigates a damped stochastic wave equation driven by a non-Gaussian Levy noise. The weak solution is proved to exist and be unique. Moreover we show the existence of a unique invariant measure associated with the transition…

Probability · Mathematics 2009-05-08 Lijun Bo , Kehua Shi , Yongjin Wang

We first state a special type of It\^o formula involving stochastic integrals of both standard and fractional Brownian motions. Then we use Doss-Sussman transformation to establish the link between backward doubly stochastic differential…

Probability · Mathematics 2011-03-18 Shuai Jing

We examine the existence and uniqueness of invariant measures of a class of stochastic partial differential equations with Gaussian and Poissonian noise and its exponential convergence. This class especially includes a case of stochastic…

Probability · Mathematics 2024-08-23 Peter Kuchling , Barbara Rüdiger , Baris Ugurcan

This article deals with the approximation of a stochastic partial differential equation (SPDE) via amplitude equations. We consider an SPDE with a cubic nonlinearity perturbed by a general multiplicative noise that preserves the constant…

Dynamical Systems · Mathematics 2019-10-08 Hongbo Fu , Dirk Blömker

In this paper, we study the contractivity of nonlinear stochastic differential equations (SDEs) driven by deterministic inputs and Brownian motions. Given a weighted $\ell_2$-norm for the state space, we show that an SDE is incrementally…

Systems and Control · Electrical Eng. & Systems 2026-02-23 Yu Kawano , Simone Betteti , Alexander Davydov , Francesco Bullo

This paper investigates the well-posedness and small-noise asymptotics of a class of stochastic partial differential equations defined on a bounded domain of $\mathbb{R}^d$, where the diffusion coefficient depends nonlinearly and…

Probability · Mathematics 2025-06-23 Sandra Cerrai , Giuseppina Guatteri , Gianmario Tessitore

In order to bring contraction analysis into the very fruitful and topical fields of stochastic and Bayesian systems, we extend here the theory describes in \cite{Lohmiller98} to random differential equations. We propose new definitions of…

Optimization and Control · Mathematics 2013-09-27 Nicolas Tabareau , Jean-Jacques Slotine

This paper continues the study of [11, 13] for stationary solutions of stochastic linear retarded functional differential equations with the emphasis on delays which appear in those terms including spatial partial derivatives. As a…

Probability · Mathematics 2014-02-11 Kai Liu

Our investigation is specially motivated by the stochastic version of a common model of potential spread in a dendritic tree. We do not assume the noise in the junction points to be Markovian. In fact, we allow for long-range dependence in…

Probability · Mathematics 2018-12-21 Stefano Bonaccorsi , Delio Mugnolo

We consider a reaction-diffusion equation of the type \[ \partial_t\psi = \partial^2_x\psi + V(\psi) + \lambda\sigma(\psi)\dot{W} \qquad\text{on $(0\,,\infty)\times\mathbb{T}$}, \] subject to a "nice" initial value and periodic boundary,…

Probability · Mathematics 2020-12-24 Davar Khoshnevisan , Kunwoo Kim , Carl Mueller , Shang-Yuan Shiu

Stochastic contraction analysis is a recently developed tool for studying the global stability properties of nonlinear stochastic systems, based on a differential analysis of convergence in an appropriate metric. To date, stochastic…

Optimization and Control · Mathematics 2013-04-02 Quang-Cuong Pham , Jean-Jacques Slotine

Semilinear stochastic evolution equations with multiplicative Poisson noise and monotone nonlinear drift are considered. We do not impose coercivity conditions on coefficients. A novel method of proof for establishing existence and…

Probability · Mathematics 2014-06-17 Erfan Salavati , Bijan Z. Zangeneh

In this article, we study the stochastic wave equation on the entire space $\mathbb{R}^d$, driven by a space-time L\'evy white noise with possibly infinite variance (such as the $\alpha$-stable L\'evy noise). In this equation, the noise is…

Probability · Mathematics 2023-03-23 Raluca M. Balan

We investigate the pathwise well-posedness of stochastic evolution equations perturbed by multiplicative Neumann boundary noise, such as fractional Brownian motion for $H\in(1/3,1/2]$. Combining the controlled rough path approach with the…

Probability · Mathematics 2023-10-17 Alexandra Neamtu , Tim Seitz

We study a stochastic Schr{\"o}dinger equation with a quadratic nonlinearity and a space-time fractional perturbation, in space dimension less than 3. When the Hurst index is large enough, we prove local well-posedness of the problem using…

Analysis of PDEs · Mathematics 2020-05-05 Aurélien Deya , Nicolas Schaeffer , Laurent Thomann

We consider a 2D stochastic modified Swift-Hohenberg equations with multiplicative noise and periodic boundary. First, we establish the existence of local and global martingale and pathwise solutions in the regular Sobolev space $H^{2m}$…

Dynamical Systems · Mathematics 2024-04-24 Jintao Wang , Xiaoqian Zhang , Chunqiu Li

We extend Walsh's theory of martingale measures in order to deal with hyperbolic stochastic partial differential equations that are second order in time, such as the wave equation and the beam equation, and driven by spatially homogeneous…

Probability · Mathematics 2011-02-18 Robert C. Dalang , Carl Mueller

In this work we investigate the long-time behavior, that is the existence and characterization of invariant measures as well as convergence of transition probabilities, for Markov processes obtained as the unique mild solution to stochastic…

Probability · Mathematics 2022-03-17 Balint Fárkas , Martin Friesen , Barbara Rüdiger , Dennis Schroers

Statistical inference for a linear stochastic hyperbolic equation with two unknown parameters is studied. Based on observation of coordinates of the solution or their linear combination, minimum contrast estimators are introduced. Strong…

Probability · Mathematics 2018-06-21 Josef Janák
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