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arXiv 1703.09565math.NAcs.NA
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截断欧拉-马尔可夫方法用于随机微分延迟方程

The Truncated Euler-Maruyama Method for Stochastic Differential Delay Equations

Shanghai Normal University(上海师范大学);University of Strathclyde(思克莱德大学)

Qian Guo, Xuerong Mao, Rongxian Yue

AI总结:

本文基于截断欧拉-马尔可夫方法研究在广义Khasminskii型条件下随机微分延迟方程数值解的强收敛性问题。

摘要:

Mao [15]讨论了在广义Khasminskii型条件下随机微分延迟方程(SDDEs)的数值解,并证明了欧拉-马尔可夫(EM)数值解以概率收敛于真实解。然而,目前尚无在该广义条件下SDDEs数值解的强收敛性(即L^p意义下)的结果。本文将使用Mao [16]开发的截断EM方法,研究在广义Khasminskii型条件下SDDEs数值解的强收敛性。

英文摘要:

The numerical solutions of stochastic differential delay equations (SDDEs) under the generalized Khasminskii-type condition were discussed by Mao [15], and the theory there showed that the Euler-Maruyama (EM) numerical solutions converge to the true solutions in probability. However, there is so far no result on the strong convergence (namely in L^p) of the numerical solutions for the SDDEs under this generalized condition. In this paper, we will use the truncated EM method developed by Mao [16] to study the strong convergence of the numerical solutions for the SDDEs under the generalized Khasminskii-type condition.

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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