Open AccessStability Analysis for Impulsive Stochastic Reaction-Diffusion Differential System and Its Application to Neural Networks
Author(s) -
Yanke Du,
Yanlu Li,
Rui Xu
Publication year - 2013
Publication title -
journal of applied mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.307
H-Index - 43
eISSN - 1687-0042
pISSN - 1110-757X
DOI - 10.1155/2013/785141
Subject(s) - reaction–diffusion system , artificial neural network , stability (learning theory) , exponential stability , stochastic differential equation , diffusion , computer science , mathematics , differential equation , exponential function , mathematical analysis , physics , artificial intelligence , thermodynamics , machine learning , nonlinear system , quantum mechanics
This paper is concerned with the stability of impulsive stochastic reaction-diffusion differential systems with mixed time delays. First, an equivalent relation between the solution of a stochastic reaction-diffusion differential system with time delays and impulsive effects and that of corresponding system without impulses is established. Then, some stability criteria for the stochastic reaction-diffusion differential system with time delays and impulsive effects are derived. Finally, the stability criteria are applied to impulsive stochastic reaction-diffusion Cohen-Grossberg neural networks with mixed time delays, and sufficient conditions are obtained for the exponential p-stability of the zero solution to the neural networks. An example is given to illustrate the effectiveness of our theoretical results. The systems we studied in this paper are more general, and some existing results are improved and extended
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