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Weakly corrected numerical solutions to stochastically driven nonlinear dynamical systems

机译:随机驱动非线性动力学系统的弱校正数值解

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摘要

A method to weakly correct the solutions of stochastically driven nonlinear dynamical systems, herein numerically approximated through the Eule-Maruyama (EM) time-marching map, is proposed. An essential feature of the method is a change of measures that aims at rendering the EM-approximated solution measurable with respect to the filtration generated by an appropriately defined error process. Using Ito's formula and adopting a Monte Carlo (MC) setup, it is shown that the correction term may be additively applied to the realizations of the numerically integrated trajectories. Numerical evidence, presently gathered via applications of the proposed method to a few nonlinear mechanical oscillators and a semi-discrete form of a 1-D Burger's equation, lends credence to the remarkably improved numerical accuracy of the corrected solutions even with relatively large time step sizes.
机译:提出了一种弱校正随机驱动非线性动力学系统解的方法,在此方法是通过Eule-Maruyama(EM)时间行进图进行数值逼近的。该方法的一个基本特征是改变了测量方法,旨在使EM近似溶液相对于由适当定义的误差过程产生的过滤可测量。使用伊藤公式,并采用蒙特卡洛(MC)设置,表明可以将校正项加到数值积分轨迹的实现中。目前,通过将所提出的方法应用到一些非线性机械振荡器和一维汉堡模型的半离散形式而获得的数值证据,即使在相对较大的时间步长的情况下,也可以证明校正后的解决方案的数值精度得到了显着提高。 。

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