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IMPLICIT STOCHASTIC RUNGE-KUTTA METHODS FOR STOCHASTIC DIFFERENTIAL EQUATIONS

机译:随机微分方程的隐式随机Runge-Kutta方法

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摘要

In this paper we construct implicit stochastic Runge-Kutta (SRK) methods for solving stochastic differential equations of Stratonovich type. Instead of using the increment of a Wiener process, modified random variables are used. We give convergence conditions of the SRK methods with these modified random variables. In particular, the truncated random variable is used. We present a two-stage stiffly accurate diagonal implicit SRK (SADISRK2) method with strong order 1.0 which has better numerical behaviour than extant methods. We also construct a five-stage diagonal implicit SRK method and a six-stage stiffly accurate diagonal implicit SRK method with strong order 1.5. The mean-square and asymptotic stability properties of the trapezoidal method and the SADISRK2 method are analysed and compared with an explicit method and a semi-implicit method. Numerical results are reported for confirming convergence properties and for comparing the numerical behaviour of these methods.
机译:在本文中,我们构造了隐式随机Runge-Kutta(SRK)方法来求解Stratonovich类型的随机微分方程。代替使用维纳过程的增量,使用修改后的随机变量。通过这些修改后的随机变量,我们给出了SRK方法的收敛条件。特别地,使用了截断的随机变量。我们提出了一种具有强阶数1.0的两阶段刚性精确对角隐式SRK(SADISRK2)方法,该方法具有比现有方法更好的数值性能。我们还构造了一个五阶对角隐式SRK方法和一个六阶刚性阶为1.5的刚性精确对角隐式SRK方法。分析了梯形方法和SADISRK2方法的均方和渐近稳定性,并将其与显式方法和半隐式方法进行了比较。报告了数值结果,以确认收敛性并比较这些方法的数值行为。

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