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The Convergence and MS Stability of Exponential Euler Method for Semilinear Stochastic Differential Equations

机译:半线性随机微分方程指数Euler方法的收敛性和MS稳定性

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The numerical approximation of exponential Euler method is constructed for semilinear stochastic differential equations (SDEs). The convergence and mean-square(MS) stability of exponential Euler method are investigated. It is proved that the exponential Euler method is convergent with the strong order1/2for semilinear SDEs. A mean-square linear stability analysis shows that the stability region of exponential Euler method contains that of EM method and stochastic Theta method(0≤θ<1)and also contains that of the scale linear SDE, that is, exponential Euler method is analogue mean-squareA-stable. Then the exponential stability of the exponential Euler method for scalar semi-linear SDEs is considered. Under the conditions that guarantee the analytic solution is exponentially stable in mean-square sense, the exponential Euler method can reproduce the mean-square exponential stability for any nonzero stepsize. Numerical experiments are given to verify the conclusions.
机译:针对半线性随机微分方程(SDE),构造了指数Euler方法的数值逼近。研究了指数欧拉方法的收敛性和均方(MS)稳定性。证明了半线性SDE的指数欧拉方法与强阶1/2收敛。均方线性稳定性分析表明,指数Euler方法的稳定性区域包含EM方法和随机Theta方法(0≤θ<1)的稳定性区域,还包含比例线性SDE的稳定性区域,即指数Euler方法是类似的均方根稳定。然后考虑了标量半线性SDEs的指数欧拉方法的指数稳定性。在保证解析解在均方意义上是指数稳定的条件下,指数欧拉方法可以重现任何非零步长的均方指数稳定性。通过数值实验验证了结论。

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