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

Wei Mao, Xuerong Mao

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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 languageEnglish
Article number77
Number of pages18
JournalAdvances in Difference Equations
Volume2016
Issue number1
DOIs
Publication statusPublished - 15 Mar 2016

Keywords

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

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