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Related papers: On Time Uniform Wong-Zakai Approximation Theorems

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We study a family of numerical schemes applied to a class of multiscale systems of stochastic differential equations. When the time scale separation parameter vanishes, a well-known homogenization or Wong--Zakai diffusion approximation…

Numerical Analysis · Mathematics 2022-08-02 Charles-Edouard Bréhier

We consider a class of stochastic differential equations driven by a one dimensional Brownian motion and we investigate the rate of convergence for Wong-Zakai-type approximated solutions. We first consider the Stratonovich case, obtained…

Probability · Mathematics 2018-06-06 Bilel Kacem Ben Ammou , Alberto Lanconelli

Diffusion approximation provides weak approximation for stochastic gradient descent algorithms in a finite time horizon. In this paper, we introduce new tools motivated by the backward error analysis of numerical stochastic differential…

Machine Learning · Computer Science 2019-09-05 Yuanyuan Feng , Tingran Gao , Lei Li , Jian-Guo Liu , Yulong Lu

The strong convergence of Wong-Zakai approximations of the solution to the reflecting stochastic differential equations was studied in [2]. We continue the study and prove the strong convergence under weaker assumptions on the domain.

Probability · Mathematics 2014-07-28 Shigeki Aida

Consider an It\^{o} process $X$ satisfying the stochastic differential equation $dX=a(X)\,dt+b(X)\,dW$ where $a,b$ are smooth and $W$ is a multidimensional Brownian motion. Suppose that $W_n$ has smooth sample paths and that $W_n$ converges…

Dynamical Systems · Mathematics 2016-02-10 David Kelly , Ian Melbourne

We examine a Wong-Zakai type approximation of a family of stochastic differential equations driven by a general cadlag semimartingale. For such an approximation, compared with the pointwise convergence result by Kurtz, Pardoux and Protter…

Probability · Mathematics 2019-02-19 Xianming Liu , Guangyue Han

We investigate the stochastic modified equation which plays an important role in the stochastic backward error analysis for explaining the mathematical mechanism of a numerical method. The contribution of this paper is threefold. First, we…

Numerical Analysis · Mathematics 2019-07-08 Chuchu Chen , Jialin Hong , Chuying Huang

The aim of this paper is to obtain convergence in mean in the uniform topology of piecewise linear approximations of Stochastic Differential Equations (SDEs) with $C^1$ drift and $C^2$ diffusion coefficients with uniformly bounded…

Probability · Mathematics 2025-03-13 Sahani Pathiraja

We investigate the regularity of the law of Wong-Zakai-type approximations for It\^o stochastic differential equations. These approximations solve random differential equations where the diffusion coefficient is Wick-multiplied by the…

Probability · Mathematics 2019-01-10 Alberto Lanconelli

In this paper we prove a general approximation result for reflected stochastic differential equations in bounded domains satisfying conditions reorganized by Ren and Wu. Then we show that it includes Wong-Zakai approximation, mollifier…

Probability · Mathematics 2019-09-11 Sheng Wang

In this paper we show that the rate of convergence of Wong-Zakai approximations for stochastic partial differential equations driven by Wiener processes is essentially the same as the rate of convergence of the driving processes W_n…

Probability · Mathematics 2012-09-14 I. Gyöngy , P. R. Stinga

We introduce a novel approach to numerical approximation of nonlinear Schr\"odinger equation with white noise dispersion in the regime of low-regularity solutions. Approximating such solutions in the stochastic setting is particularly…

Numerical Analysis · Mathematics 2025-05-14 Jianbo Cui , Georg Maierhofer

The aim of this note is to propose a novel numerical scheme for drift-less one dimensional stochastic differential equations of It\^o's type driven by standard Brownian motion. Our approximation method is equivalent to the well known…

Probability · Mathematics 2024-07-24 Alberto Lanconelli , Berk Tan Perçin

In this paper we prove the Wong-Zakai approximation of probability density functions of solutions at a fixed time of rough differential equations driven by fractional Brownian rough path with Hurst parameter $H$ $(1/4 <H \leq 1/2)$. Besides…

Probability · Mathematics 2025-07-28 Yuzuru Inahama

In this paper we prove an approximate continuity result for stochastic differential equations with normal reflections in domains satisfying Saisho's conditions, which together with the Wong-Zakai approximation result completes the support…

Probability · Mathematics 2016-06-07 Jiagang Ren , Jing Wu

This paper is devoted to the smooth and stationary Wong-Zakai approximations for a class of rough differential equations driven by a geometric fractional Brownian rough path $\boldsymbol{\omega}$ with Hurst index…

Probability · Mathematics 2023-03-09 Qiyong Cao , Hongjun Gao , Bjorn Schmalfuss

We consider sequences of additive functionals of difference approximations for uniformly non-degenerate multidimensional diffusions. The conditions are given, sufficient for such a sequence to converge weakly to a W-functional of the…

Probability · Mathematics 2007-05-23 Alexey M. Kulik

In this paper we consider the following stochastic partial differential equation (SPDE) in the whole space: $du (t, x) = [a^{i j} (t, x) D_{i j} u(t, x) + f(u, t, x)]\, dt + \sum_{k = 1}^m g^k (u(t, x)) dw^k (t).$ We prove the convergence…

Probability · Mathematics 2018-11-15 Timur Yastrzhembskiy

We establish general conditions under which there exists uniform in time convergence between a stochastic process and its approximated system. These standardised conditions consist of a local in time estimate between the original and the…

Probability · Mathematics 2024-12-09 Katharina Schuh , Iain Souttar

The time-space fractional cable equation arises from extending the generalized fractional Ohm's law to model anomalous diffusion processes. In this paper, we develop and analyze a numerical approximation for stochastic nonlinear time-space…

Numerical Analysis · Mathematics 2026-01-06 Jiawei He , Jianhua Huang , Fang Su
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