随机延迟积分微分方程的分步后向欧拉法的弱收敛性

IF 5.4 3区 材料科学 Q2 CHEMISTRY, PHYSICAL
Yan Li, Qiuhong Xu, Wanrong Cao
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引用次数: 0

摘要

在本文中,我们的主要目的是讨论分步后向欧拉(SSBE)方法的弱收敛性,该方法在用于求解一类以全局 Lipschitz 系数为特征的随机延迟积分微分方程(SDIDE)时,以其卓越的稳定性而闻名。由于缺乏 Kolmogorov 方程,传统的弱收敛分析技术无法直接应用于 SDIDE。为了弥补这一缺陷,我们采用修正方程来建立用于求解原始 SDIDE 的 SSBE 方法与应用于修正方程的 Euler-Maruyama 方法之间的等价性。通过证明 SDIDEs 解与修正方程之间的一阶强收敛性,我们建立了用于 SDIDEs 的 SSBE 方法的一阶弱收敛性。最后,我们通过数值模拟来验证我们的理论发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Weak convergence of the split-step backward Euler method for stochastic delay integro-differential equations

In this paper, our primary objective is to discuss the weak convergence of the split-step backward Euler (SSBE) method, renowned for its exceptional stability when used to solve a class of stochastic delay integro-differential equations (SDIDEs) characterized by global Lipschitz coefficients. Traditional weak convergence analysis techniques are not directly applicable to SDIDEs due to the absence of a Kolmogorov equation. To bridge this gap, we employ modified equations to establish an equivalence between the SSBE method used for solving the original SDIDEs and the Euler–Maruyama method applied to modified equations. By demonstrating first-order strong convergence between the solutions of SDIDEs and the modified equations, we establish the first-order weak convergence of the SSBE method for SDIDEs. Finally, we present numerical simulations to validate our theoretical findings.

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来源期刊
ACS Applied Energy Materials
ACS Applied Energy Materials Materials Science-Materials Chemistry
CiteScore
10.30
自引率
6.20%
发文量
1368
期刊介绍: ACS Applied Energy Materials is an interdisciplinary journal publishing original research covering all aspects of materials, engineering, chemistry, physics and biology relevant to energy conversion and storage. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important energy applications.
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