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

机译:半线性随机时滞微分方程指数Euler方法的收敛性和稳定性

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摘要

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 ½ 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.
机译:本文的主要目的是研究半线性随机延迟微分方程(SLSDDEs)的指数Euler方法的均方值的强收敛性和指数稳定性。证明了指数Euler逼近解收敛于SLSDDEs具有强½阶的解析解。一方面,Lyapunov函数给出了SLSDDEs的经典稳定性定理。但是,在本文中,我们通过使用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,对于任何步长,已知对SLSDDE的隐式Euler方案在均方上是指数稳定的。但是,在本文中,我们提出了一种显式方法,以证明对数标准的性质证明了针对SLSDDE的指数Euler方法对于任何步长都具有相同的稳定性。

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