基于多项式条件的随机泛函微分方程的近似泰勒方法

Pub Date : 2021-11-01 DOI:10.2478/auom-2021-0037
D. Djordjević, M. Milosevic
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引用次数: 0

摘要

摘要本文研究了一类随机泛函微分方程的解析近似方法,这类方程的系数既不满足Lipschitz条件,也不满足线性增长条件,但满足多项式条件。同时,从观测类中得到的方程具有具有有限矩的唯一解。在时间间隔的分区上定义近似方程,其漂移系数和扩散系数是初始方程系数的泰勒近似。由于初始方程的系数是泛函的,所以泰勒近似需要fr导数。本文的主要结果是初值方程的精确解的近似解序列的Lp和几乎肯定收敛性。给出了一个例子,说明了理论结果,并证明了近似解的存在性、唯一性和矩有界性。
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An approximate Taylor method for Stochastic Functional Differential Equations via polynomial condition
Abstract The subject of this paper is an analytic approximate method for a class of stochastic functional differential equations with coefficients that do not necessarily satisfy the Lipschitz condition nor linear growth condition but they satisfy some polynomial conditions. Also, equations from the observed class have unique solutions with bounded moments. Approximate equations are defined on partitions of the time interval and their drift and diffusion coefficients are Taylor approximations of the coefficients of the initial equation. Taylor approximations require Fréchet derivatives since the coefficients of the initial equation are functionals. The main results of this paper are the Lp and almost sure convergence of the sequence of the approximate solutions to the exact solution of the initial equation. An example that illustrates the theoretical results and contains the proof of the existence, uniqueness and moment boundedness of the approximate solution is displayed.
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