Numerical study on (ω, Lδ)-Lipschitz shadowing of stochastic differential equations

Qingyi Zhan, Zhifang Zhang and Xiangdong Xie

Applied Mathematics and Computation, 2020, vol. 376, issue C

Abstract: This paper focuses on the feasibility and numerical implementations of (ω, Lδ)-Lipschitz shadowing of a class of stochastic differential equations via numerical analysis. A new notion of random Lipschitz shadowing and exact estimation of shadowing distance of stochastic differential equations are investigated. Moreover, the measurability of the true orbits is also studied. Numerical simulations of chaotic orbits of stochastic Lu¨ system are provided to illustrate the effectiveness of the proposed theorem.

Keywords: Stochastic differential equations; (ω, Lδ)-Lipschitz shadowing; Measurability (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:376:y:2020:i:c:s0096300320300771

DOI: 10.1016/j.amc.2020.125108

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