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首页> 外文期刊>International journal of computer mathematics >Strong convergence of the truncated Euler-Maruyama method for stochastic functional differential equations
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Strong convergence of the truncated Euler-Maruyama method for stochastic functional differential equations

机译:随机泛函微分方程的截断Euler-Maruyama方法的强收敛性。

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摘要

In this paper, we establish the truncated Euler-Maruyama (EM) method for stochastic functional differential equation (SFDE) dy(t) = f(y(t)) dt + g(y(t)) dB(t) and consider the strong convergence theory for the numerical solutions of SFDEs under the local Lipschitz condition plus Khasminskii-type condition instead of the linear growth condition. The type of convergence specifically addressed in this paper is strong-L-q convergence for 2 = q p, and p is a parameter in Khasminskii-type condition. We also discussed the rates of L-q-convergence for the truncated EM method.
机译:在本文中,我们为随机泛函微分方程(SFDE)dy(t)= f(y(t))dt + g(y(t))dB(t)建立了截断的Euler-Maruyama(EM)方法局部Lipschitz条件加Khasminskii型条件代替线性增长条件的SFDE数值解的强收敛理论。本文具体解决的收敛类型是2 <= q 的强L-q收敛,并且p是Khasminskii型条件下的参数。我们还讨论了截断EM方法的L-q收敛速率。

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