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Convergence of the Euler Method of Stochastic Differential Equations with Piecewise Continuous Arguments

机译:分段连续变量随机微分方程Euler方法的收敛性。

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The main purpose of this paper is to investigate the strong convergence of the Euler method to stochastic differential equations with piecewise continuous arguments (SEPCAs). Firstly, it is proved that the Euler approximation solution converges to the analytic solution under local Lipschitz condition and the boundedpth moment condition. Secondly, the Euler approximation solution converge to the analytic solution is given under local Lipschitz condition and the linear growth condition. Then an example is provided to show which is satisfied with the monotone condition without the linear growth condition. Finally, the convergence of numerical solutions to SEPCAs under local Lipschitz condition and the monotone condition is established.
机译:本文的主要目的是研究具有分段连续参数(SEPCA)的随机微分方程的Euler方法的强收敛性。首先证明了在局部Lipschitz条件和有界矩条件下,欧拉逼近解收敛于解析解。其次,在局部Lipschitz条件和线性增长条件下给出了Euler逼近解收敛于解析解。然后提供一个示例,以显示单调条件而不满足线性增长条件的情况。最后,建立了局部Lipschitz条件和单调条件下SEPCA数值解的收敛性。

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