Optimal index and averaging principle for Itô–Doob stochastic fractional differential equations

IF 0.8 4区数学 Q3 STATISTICS & PROBABILITY

Stochastics and Dynamics Pub Date : 2022-02-25 DOI:10.1142/s0219493722500186

Wenya Wang, Zhongkai Guo

引用次数: 5

Abstract

In this paper, a class of Itô–Doob stochastic fractional differential equations (Itô–Doob SFDEs) models are discussed. Using the time scale transformation method, we consider the averaging principle of the transformed equations and establish the relevant results. At the same time, we find that the optimal index for the original Itô–Doob SFDEs can be determined, the selection of such index is similar to the classical stochastic differential equations model.

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It–Doob随机分数微分方程的最优指标及其平均原理

本文讨论了一类It–Doob随机分数阶微分方程（It–Doob-SFDEs）模型。利用时标变换方法，我们考虑了变换方程的平均原理，并建立了相应的结果。同时，我们发现可以确定原始It–Doob SFDE的最优指标，该指标的选择与经典随机微分方程模型相似。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Stochastics and Dynamics 数学-统计学与概率论

CiteScore

1.70

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： This interdisciplinary journal is devoted to publishing high quality papers in modeling, analyzing, quantifying and predicting stochastic phenomena in science and engineering from a dynamical system''s point of view. Papers can be about theory, experiments, algorithms, numerical simulation and applications. Papers studying the dynamics of stochastic phenomena by means of random or stochastic ordinary, partial or functional differential equations or random mappings are particularly welcome, and so are studies of stochasticity in deterministic systems.