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半线性随机延迟微分方程指数欧拉方法的收敛性与稳定性

Convergence and stability of the exponential Euler method for semi-linear stochastic delay differential equations.

作者信息

Zhang Ling

机构信息

Mathematical Department of Teacher Education Institute, DaQing Normal University, DaQing, 163712 P.R. China.

出版信息

J Inequal Appl. 2017;2017(1):249. doi: 10.1186/s13660-017-1518-5. Epub 2017 Oct 6.

Abstract

The main purpose of this paper is to investigate the strong convergence and exponential stability in mean square of the exponential Euler method to semi-linear stochastic delay differential equations (SLSDDEs). It is proved that the exponential Euler approximation solution converges to the analytic solution with the strong order [Formula: see text] to SLSDDEs. On the one hand, the classical stability theorem to SLSDDEs is given by the Lyapunov functions. However, in this paper we study the exponential stability in mean square of the exact solution to SLSDDEs by using the definition of logarithmic norm. On the other hand, the implicit Euler scheme to SLSDDEs is known to be exponentially stable in mean square for any step size. However, in this article we propose an explicit method to show that the exponential Euler method to SLSDDEs is proved to share the same stability for any step size by the property of logarithmic norm.

摘要

本文的主要目的是研究指数Euler方法对半线性随机延迟微分方程(SLSDDEs)的强收敛性和均方指数稳定性。证明了指数Euler逼近解以强阶[公式:见原文]收敛到SLSDDEs的解析解。一方面,利用Lyapunov函数给出了SLSDDEs的经典稳定性定理。然而,在本文中,我们通过对数范数的定义研究了SLSDDEs精确解的均方指数稳定性。另一方面,已知SLSDDEs的隐式Euler格式对于任何步长在均方意义下是指数稳定的。然而,在本文中,我们提出了一种显式方法,通过对数范数的性质证明了SLSDDEs的指数Euler方法对于任何步长都具有相同的稳定性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e600/5630662/044ad5495f41/13660_2017_1518_Fig1_HTML.jpg

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