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General Modified Split-Step Balanced Methods for Stiff Stochastic Differential Equations

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【作者】 殷政伟甘四清李荣德

【Author】 YIN Zheng-wei;GAN Si-qing;LI Rong-de;School of Mathematics and Statistics,Henan University of Science and Technology;State Key Laboratory of High Performance Complex Manufacturing,School of Mathematics and Statistics,Central South University;CITIC Heavy Industries Co.,LTD.;

【机构】 School of Mathematics and Statistics,Henan University of Science and TechnologyState Key Laboratory of High Performance Complex Manufacturing,School of Mathematics and Statistics,Central South UniversityCITIC Heavy Industries Co.,LTD.

【摘要】 A class of general modified split-step balanced methods proposed in the paper can be applied to solve stiff stochastic differential systems with m-dimensional multiplicative noise.Compared to some other already reported split-step balanced methods,the drift increment function of the methods can be taken from any chosen one-step ordinary differential equations(ODEs)solver.The schemes is proved to be strong convergent with order one.For the mean-square stability analysis,the investigation is confined to two cases.Some numerical experiments are reported to testify the performance and the effectiveness of the methods.

【Abstract】 A class of general modified split-step balanced methods proposed in the paper can be applied to solve stiff stochastic differential systems with m-dimensional multiplicative noise.Compared to some other already reported split-step balanced methods,the drift increment function of the methods can be taken from any chosen one-step ordinary differential equations(ODEs)solver.The schemes is proved to be strong convergent with order one.For the mean-square stability analysis,the investigation is confined to two cases.Some numerical experiments are reported to testify the performance and the effectiveness of the methods.

【基金】 National Natural Science Foundation of China(No.11171352)
  • 【文献出处】 Journal of Donghua University(English Edition) ,东华大学学报(英文版) , 编辑部邮箱 ,2013年03期
  • 【分类号】O211.63
  • 【被引频次】1
  • 【下载频次】68
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