随机Ito-Volterra积分方程的数值逼近

Emmanuel Oladayo Oduselu–Hassan, Ignatius N. Njoseh, Jonathan Tsetimi
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引用次数: 0

摘要

随机微分方程(SDE)是一种微分方程,其中一个或多个项及其解是随机过程。许多研究都使用了正交多项式,但大多数研究都集中在确定性系统而不是随机系统上。这就是为什么在本研究中,我们使用显式有限差分格式和Bernstein多项式作为试验函数来研究随机Ito-Volterra积分方程的数值解。采用等距配置法计算中间的未知常数参数,得到所需的近似。将该方法与基于上述方法的块脉冲方法进行了评估和对比,并与文献中其他方法进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Numerical Approximation of the Stochastic Ito-Volterra Integral Equation
A stochastic differential equation (SDE) is a differential equation in which one or more of the terms and the solution are stochastic processes. Numerous studies have employed orthogonal polynomials, however most of them focus on deterministic rather than stochastic systems. This is the reason why in this study, we looked into a numerical solution for the stochastic Ito-Volterra integral equation using the explicit finite difference scheme and Bernstein polynomials as trial functions. The equidistant collocation procedure was used to calculate the unknown constant parameters in between and reach the desired approximation. The method was evaluated and contrasted with the Block Pulse method for approximate answers based on the aforementioned method, which were obtained and compared with others in the literature.
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