An averaging principle for neutral stochastic functional differential equations driven by Poisson random measure

Wei Mao; Xuerong Mao

doi:10.1186/s13662-016-0802-x

An averaging principle for neutral stochastic functional differential equations driven by Poisson random measure

Wei Mao, Xuerong Mao

Mathematics And Statistics

Research output: Contribution to journal › Article

3 Citations (Scopus)

29 Downloads (Pure)

Abstract

In this paper, we study the averaging principle for neutral stochastic functional differential equations (SFDEs) with Poisson random measure. By stochastic inequality, Burkholder-Davis-Gundy’s inequality and Kunita’s inequality, we prove that the solution of the averaged neutral SFDEs with Poisson random measure converges to that of the standard one in (Formula presented.) sense and also in probability. Some illustrative examples are presented to demonstrate this theory.

Original language	English
Article number	77
Number of pages	18
Journal	Advances in Difference Equations
Volume	2016
Issue number	1
DOIs	https://doi.org/10.1186/s13662-016-0802-x
Publication status	Published - 15 Mar 2016

Keywords

averaging principle
convergence in probability
L convergence
neutral SFDEs
Poisson random measure

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10.1186/s13662-016-0802-x

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Mao, W., & Mao, X. (2016). An averaging principle for neutral stochastic functional differential equations driven by Poisson random measure. Advances in Difference Equations, 2016(1), [77]. https://doi.org/10.1186/s13662-016-0802-x

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