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

Boundary value problems

Weiyuan Zhang¹  Junmin Li²  Minglai Chen³ 

[1] Institute of Mathematics and Applied Mathematics, Xianyang Normal University, Xianyang, China;School of Science, Xidian University, Xi’an, China

关键词: neural networks;    reaction-diffusion;    mixed time delays;    global exponential stability;    Poincaré mapping;    Lyapunov functional;   

DOI  :  10.1186/1687-2770-2013-105

学科分类：数学（综合）

来源: SpringerOpen

【 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.

【 授权许可】

CC BY