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Mean-Square Stability of Split-Step Theta Milstein Methods for Stochastic Differential Equations

机译:随机微分方程的分步Theta Milstein方法的均方稳定性

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摘要

The fundamental analysis of numerical methods for stochastic differential equations (SDEs) has been improved by constructing new split-step numerical methods. In this paper, we are interested in studying the mean-square (MS) stability of the new general drifting split-step theta Milstein (DSS theta M) methods for SDEs. First, we consider scalar linear SDEs. The stability function of the DSS theta M methods is investigated. Furthermore, the stability regions of the DSS theta M methods are compared with those of test equation, and it is proved that the methods with theta >= 3/2 are stochastically A-stable. Second, the nonlinear stability of DSS theta M methods is studied. Under a coupled condition on the drifting and diffusion coefficients, it is proved that the methods with theta > 1/2 can preserve the MS stability of the SDEs with no restriction on the step-size. Finally, numerical examples are given to examine the accuracy of the proposed methods under the stability conditions in approximation of SDEs.
机译:通过构建新的分步数值方法,改进了随机微分方程(SDE)数值方法的基础分析。在本文中,我们有兴趣研究SDE的新通用漂移分步theta Milstein(DSS theta M)新方法的均方(MS)稳定性。首先,我们考虑标量线性SDE。研究了DSS theta M方法的稳定性函数。此外,将DSS theta M方法的稳定性区域与测试方程的稳定性区域进行了比较,并证明了theta> = 3/2的方法是随机A稳定的。其次,研究了DSS theta M方法的非线性稳定性。在漂移和扩散系数耦合的条件下,证明了theta> 1/2的方法可以保留SDE的MS稳定性,而对步长没有限制。最后,通过数值例子验证了所提方法在稳定条件下近似SDE的准确性。

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  • 来源
    《Mathematical Problems in Engineering》 |2018年第1期|1682513.1-1682513.13|共13页
  • 作者单位

    Harbin Inst Technol Dept Math Harbin 150001 Heilongjiang Peoples R China|Menoufia Univ Fac Sci Dept Math Menoufia 32511 Egypt;

    Harbin Inst Technol Dept Math Harbin 150001 Heilongjiang Peoples R China;

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