...
首页> 外文期刊>Applied mathematics and computation >Strong convergence of the stopped Euler–Maruyama method for nonlinear stochastic differential equations
【24h】

Strong convergence of the stopped Euler–Maruyama method for nonlinear stochastic differential equations

机译:非线性随机微分方程停止Euler-Maruyama方法的强收敛性

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

In this paper, numerical methods for the nonlinear stochastic differential equations (SDEs) with non-global Lipschitz drift coefficient are discussed. The existing known results have only so far shown that the classical (explicit) Euler–Maruyama (EM) approximate solutions converge to the true solution in probability [22,23]. More recently, the authors in [16] proved that the classical EM method will diverge in L~2 sense for the underlying SDEs in this paper (and those SDEs with superlinearly growing coefficients). These strongly indicate that the classical EM method is not good enough for the highly nonlinear SDEs. However, in this paper, we introduce a modified EM method using stopping time and show successfully that the discrete version of the modified EM approximate solution converges to the true solution in the strong sense (namely in L~2) with a order arbitrarily close to a half.
机译:本文讨论了具有非全局Lipschitz漂移系数的非线性随机微分方程(SDE)的数值方法。到目前为止,现有的已知结果仅表明经典(显式)的欧拉–丸山(EM)近似解在概率上收敛于真实解[22,23]。最近,[16]中的作者证明了经典的EM方法将在本文的底层SDE(以及那些具有超线性增长系数的SDE)的L〜2意义上发散。这些有力地表明,对于高度非线性的SDE,传统的EM方法还不够好。然而,在本文中,我们介绍了一种使用停止时间的改进的EM方法,并成功地表明,该改进的EM近似解的离散版本在强意义上(即L〜2)收敛到真实解,其阶次任意接近一半。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号