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Preservation of quadratic invariants of stochastic differential equations via Runge-Kutta methods

机译:用Runge-Kutta方法保存随机微分方程的二次不变量

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摘要

In this paper, we give conditions for stochastic Runge-Kutta (SRK) methods to preserve quadratic invariants. It is shown that SRK methods preserving quadratic invariants are symplectic. Based on both convergence order conditions and quadratic invariant-preserving conditions, we construct some SRK schemes preserving quadratic invariants with strong and weak convergence order with the help of computer algebra, respectively. Numerical experiments are executed to verify our theoretical analysis and show the superiority of these schemes.
机译:在本文中,我们给出了随机Runge-Kutta(SRK)方法保留二次不变量的条件。结果表明,保留二次不变式的SRK方法是辛的。基于收敛阶条件和二次不变量保持条件,我们分别借助计算机代数构造了一些SRK方案,分别存储了具有强和弱收敛阶的二次不变量。进行了数值实验以验证我们的理论分析并显示出这些方案的优越性。

著录项

  • 来源
    《Applied numerical mathematics 》 |2015年第1期| 38-52| 共15页
  • 作者单位

    State Key Laboratory of Scientific and Engineering Computing, Institute of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, PR China;

    State Key Laboratory of Scientific and Engineering Computing, Institute of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, PR China;

    College of Mathematics, Jilin University, PR China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Stochastic differential equations; Invariant; Runge-Kutta methods; Symplecticity; Strong convergence; Weak convergence;

    机译:随机微分方程不变Runge-Kutta方法;辛;强大的融合;弱收敛;

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