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arXiv 1302.0440math.PR
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双倒向随机微分方程的Euler时间离散及其在半线性随机微分方程中的应用

Euler time discretization of Backward Doubly SDEs and Application to Semilinear SPDEs

Achref Bachouch, Mohamed Anis Ben Lasmar, Anis Matoussi, Mohamed Mnif

摘要:

研究了一类半线性随机偏微分方程(简称SPDE)的数值概率解法。数值格式是基于解解耦的正倒向双随机微分方程系统的离散时间近似。在参数的标准假设下,证明了数值格式的收敛性和收敛速率。证明是基于向后方程的路径正则性结果的推广。

英文摘要:

This paper investigates a numerical probabilistic method for the solution of some semilinear stochastic partial differential equations (SPDEs in short). The numerical scheme is based on discrete time approximation for solutions of systems of decoupled forward-backward doubly stochastic differential equations. Under standard assumptions on the parameters, the convergence and the rate of convergence of the numerical scheme is proven. The proof is based on a generalization of the result on the path regularity of the backward equation.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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