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Convergence and stability of the compensated split-step theta method for stochastic differential equations with piecewise continuous arguments driven by Poisson random measure

机译:随机微分方程补偿分离步骤θThe方法的收敛性和稳定性,泊松随机测量驱动的分段连续参数

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This paper deals with the numerical solutions of stochastic differential equations with piecewise continuous arguments (SDEPCAs) driven by Poisson random measure in which the coefficients are highly nonlinear. It is shown that the compensated split-step theta (CSST) method with theta is an element of[0, 1] is strongly convergent in pth(p = 2) moment under some polynomially Lipschitz continuous conditions. It is also obtained that the convergence order is close to 1/p. In terms of the stability, it is proved that the CSST method with theta is an element of[1/2, 1] reproduces the exponential mean square stability of the underlying system under the monotone condition and some restrictions on the step-size. Without any restriction on the step-size, there exists theta* is an element of(1/2, 1] such that the CSST method with theta is an element of(theta*, 1] is exponentially stable in mean square. Moreover, if the drift and jump coefficients satisfy the linear growth condition, the CSST method with theta is an element of[0, 1/2] also preserves the exponential mean square stability. Some numerical simulations are presented to verify the conclusions. (C) 2018 Elsevier B.V. All rights reserved.
机译:本文涉及随着泊松随机测量驱动的分段连续参数(SDEPCAS)的随机微分方程的数值解,其中系数是高度非线性的。结果表明,具有θ的补偿分裂步骤Theta(CSST)方法是[0,1]的元素在一些多项式Lipschitz连续条件下的PTH(P> = 2)时刻强烈收敛。还可以获得收敛顺序接近1 / p。就稳定性而言,证明了具有Theta的CST方法是[1/2,1]的元素再现单调条件下底层系统的指数均方稳定性以及对阶梯大小的一些限制。没有对阶梯大小的任何限制,存在θ*是(1/2,1]的元素,使得具有θ的CST方法是(Theta *,1]的元素在均值方面是指数稳定的。此外,如果漂移和跳跃系数满足线性生长条件,则具有θ的CSST方法是[0,1/2]的元素,还保留指数均方稳定性。提出了一些数值模拟以验证结论。(c)2018 ElseVier BV版权所有。

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