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.
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页数：23
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