CAJ | 학술논문

提出并分析了求解刚性It(o)随机微分方程的分步向后Milstein方法, 基于分离技巧构造了DSSBM和MSSBM两种数值方法, 并证明了这两种方法都是一阶强收敛的. 通过讨论方法的数值稳定性和计算精度, 表明了所给方法在解决刚性随机系统时的优越性.
제출병분석료구해강성It(o)수궤미분방정적분보향후Milstein방법, 기우분리기교구조료DSSBM화MSSBM량충수치방법, 병증명료저량충방법도시일계강수렴적. 통과토론방법적수치은정성화계산정도, 표명료소급방법재해결강성수궤계통시적우월성.
The authors presented and analyzed split-step backward Milstein methods for solving ltd stochastic differential equations (SDEs). Two methods, a DSSBM method and an MSSBM method, were constructed based on the splitting technique. We proved that these methods are of strong order 1. The stability properties and numerical results show the effectiveness of these methods in the pathwise approximation of stiff SDEs.