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High-order split-step theta methods for non-autonomous stochastic differential equations with non-globally Lipschitz continuous coefficients

机译:具有非全局Lipschitz连续系数的非自治随机微分方程的高阶分裂步长theta方法

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摘要

In this paper, we first propose the so-called improved split-step theta methods for non-autonomous stochastic differential equations driven by non-commutative noise. Then, we prove that the improved split-step theta method is convergent with strong order of one for stochastic differential equations with the drift coefficient satisfying a superlinearly growing condition and a one-sided Lipschitz continuous condition. Finally, the obtained results are verified by numerical experiments. Copyright (C) 2016 John Wiley & Sons, Ltd.
机译:在本文中,我们首先针对非交换噪声驱动的非自治随机微分方程提出了所谓的改进的分步θ方法。然后,证明了改进的分步θ法对于一类随机微分方程具有强超一阶收敛性,其漂移系数满足超线性增长条件和单边Lipschitz连续条件。最后,通过数值实验验证了所得结果。版权所有(C)2016 John Wiley&Sons,Ltd.

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