title: The stability of impulsive stochastic Cohen-Grossberg neural networks with mixed delays and reaction-diffusion terms.
abstract: The global asymptotic stability of impulsive stochastic Cohen-Grossberg neural networks with mixed delays and reaction-diffusion terms is investigated. Under some suitable assumptions and using Lyapunov-Krasovskii functional method, we apply the linear matrix inequality technique to propose some new sufficient conditions for the global asymptotic stability of the addressed model in the stochastic sense. The mixed time delays comprise both the time-varying and continuously distributed delays. The effectiveness of the theoretical result is illustrated by a numerical example.
authors.affiliation: College of Electronic and Information Engineering, Southwest University, Chongqing, 400715 China ; College of Mathematics and Physics, Chongqing University of Science and Technology, Chongqing, 401331 China.
authors.forename: Jie
authors.initials: J
authors.lastname: Tan
authors.affiliation: College of Electronic and Information Engineering, Southwest University, Chongqing, 400715 China.
authors.forename: Chuandong
authors.initials: C
authors.lastname: Li
authors.affiliation: Texas A&M University at Qatar, Doha, Qatar.
authors.forename: Tingwen
authors.initials: T
authors.lastname: Huang
keywords: Global asymptotic stability; Mixed delays; Poincaré inequality; Reaction–diffusion; Stochastic Cohen–Grossberg neural network
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