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 计算数学 2019, Vol. 41 Issue (1): 12-36    DOI:
 论文 最新目录 | 下期目录 | 过刊浏览 | 高级检索 Previous Articles  |  Next Articles STRONG CONVERGENCE OF THE IMPROVED SPLIT-STEP ONE-LEG θ METHODS FOR STOCHASTIC DIFFERENTIAL EQUATIONS
Zhang Wei, Wang Wenqiang
Hunan Key Laboratory for Computation and Simulation in Science and Engineering, Xiangtan University, Xiangtan 411105, China
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Abstract： In this paper a class of methods, called improved split-step one-leg theta methods(ISSOLTM), are introduced and are shown to be convergent for SDEs with one-sided Lipschitz continuous drift coefficient if the method parameter satisfies 1/2 ≤ θ ≤ 1. At the same time, we improve the strong order from one half to one on the basis of the existing literature. For 0 ≤ θ ≤ 1/2, under the additional linear growth condition for the drift coefficient, the methods are also strongly convergent with the the order 1. Finally, the obtained results are supported by numerical experiments.

 引用本文: . 随机微分方程改进的分裂步单支θ方法的强收敛性[J]. 计算数学, 2019, 41(1): 12-36. . STRONG CONVERGENCE OF THE IMPROVED SPLIT-STEP ONE-LEG θ METHODS FOR STOCHASTIC DIFFERENTIAL EQUATIONS[J]. Mathematica Numerica Sinica, 2019, 41(1): 12-36.

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