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求解随机微分方程的两种方法的稳定性分析 被引量:4

Stability Analysis of Two Kinds of Methods for Solving Stochastic Differential Equations
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摘要 给出了两种数值求解随机微分方程的半隐式方法:M ilste in法和无导数法,两种方法均是一阶强收敛的,具有较高的精度.分析了方法的均方和渐近稳定性,给出了稳定性条件并绘出了方法的稳定域,得到了一般意义下的重要结果. The Milstein and derlvative-free methods are provided for solving stochastic differential equations in this thesis, both of them are strong convergent with order one. In investigating their mean-square and asymptotical stability properties, we obtained the corresponding conditions for stability and ploted the stability regions.
作者 朱霞 阮立志
出处 《中南民族大学学报(自然科学版)》 CAS 2006年第2期98-100,共3页 Journal of South-Central University for Nationalities:Natural Science Edition
基金 国家自然科学基金资助项目(10431060) 中南民族大学自然科学基金资助项目(YZY05008)
关键词 随机微分方程 均方稳定性 渐近稳定性 半隐Milstein法 半隐无导数法 stochastic differential equations mean-square stability asymptotical stability semi-implicit Milstein methods semi-lmplicit derivative-free methods
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参考文献3

  • 1朱霞,李建国,李宏智,姜珊珊.随机微分方程Milstein方法的稳定性[J].华中科技大学学报(自然科学版),2003,31(3):111-113. 被引量:12
  • 2Saito Y,Mitsui T.Stability analysis of numerical schemes for stochastic differential equations[J].SIAM J Numer Anal,1996,33(6):2 254-2 267.
  • 3Higham D J.Mean-square and asymptotic stability of the stochastic theta method[J].SIAM J Numer Anal,2000,38(3):753-769.

二级参考文献5

  • 1Saito Y, Mitsui T. Stability analysis of numerical schemes for stochastic differential equations. SIAM. J.Numer. Anal., 1996, 33(6): 2 254~2267
  • 2Burrage P M. Runge-kutta methods for stochastic differential equations: [Ph. D Thesis]. Department of Mathematics, the University of Queensland, Australia,1998.
  • 3Kleoden P E, Platen E, Schurz H. Numerical solution of stochastic differential equations. Berlin: Spring Verlag, 1992.
  • 4Desmond J. Higham. Mean-square and asymptotic stability of the stochastic theta method. SIAM. J. Numer.Anal., 2000, 38(3): 753~769
  • 5Rumelin W. Numerical treatment of stochastic differential equations. SIAM. J. Numer. Anal., 1982,19(3): 604~613

共引文献11

同被引文献29

  • 1朱霞,李建国,李宏智,姜珊珊.随机微分方程Milstein方法的稳定性[J].华中科技大学学报(自然科学版),2003,31(3):111-113. 被引量:12
  • 2朱霞.求解随机微分方程的欧拉法的收敛性[J].华中科技大学学报(自然科学版),2003,31(3):114-116. 被引量:17
  • 3郭小林.随机微分方程欧拉格式算法分析[J].大学数学,2006,22(3):94-99. 被引量:4
  • 4曹婉容.线性随机延迟微分方程半隐式Euler方法的局部收敛性证明[J].黑龙江大学自然科学学报,2007,24(1):97-99. 被引量:3
  • 5Tian T H,Burrage K.Two-stage stochastic Runge-Kutta methods for stochastic differential equations[J].BIT,2002,42:625-643.
  • 6Burrage K,Burrage P M.High strong order explicit Runge-Kutta methods for stochastic ordinary differential equations[J].Appl Numer Math,1996,22:81-101.
  • 7Burrage K,Burrage P M.Order conditions of stochastic Runge-Kutta methods by B-series[J].SIAM J Numer Anal,2000,38:1626-1646.
  • 8Saito Y,Mitsui T.T-stability of numerical scheme for stochastic differential equations[J].World Sci Ser Appl Anal,1993,2:333-344.
  • 9Marion G,Mao Xuerong,Renshaw E.Convergence of the Euler scheme for a class of stochastic differential equations[J].International Mathematical Journal,2001,1(1):9-22.
  • 10Liu Mingzhu,Cao Wanrong,Fan Zhencheng.Convergence and stability of the semi-implicit Euler method for a linear stochastic differential delay equation[J].J Comp Appl Math,2004,170:255-268.

引证文献4

二级引证文献15

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