Global exponential stability and existence of periodic solutions for delayed reaction-diffusion BAM neural networks with Dirichlet boundary conditions

被引：6

作者：

Zhang, Weiyuan ^{[1
]}

Li, Junmin ^{[2
]}

Chen, Minglai ^{[2
]}

机构：

[1] Xianyang Normal Univ, Inst Math & Appl Math, Xianyang 712000, Peoples R China

[2] Xidian Univ, Sch Sci, Xian 710071, Shaanxi, Peoples R China

来源：

BOUNDARY VALUE PROBLEMS | 2013年

基金：

中国国家自然科学基金;

关键词：

neural networks; reaction-diffusion; mixed time delays; global exponential stability; Poincare mapping; Lyapunov functional; TIME-VARYING DELAYS; DISTRIBUTED DELAYS; ASYMPTOTIC STABILITY; OSCILLATORY SOLUTION; TERMS; CRITERION;

D O I：

10.1186/1687-2770-2013-105

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, both global exponential stability and periodic solutions are investigated for a class of delayed reaction-diffusion BAM neural networks with Dirichlet boundary conditions. By employing suitable Lyapunov functionals, sufficient conditions of the global exponential stability and the existence of periodic solutions are established for reaction-diffusion BAM neural networks with mixed time delays and Dirichlet boundary conditions. The derived criteria extend and improve previous results in the literature. A numerical example is given to show the effectiveness of the obtained results.

引用

页数：23

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