Global exponential synchronization of delayed BAM neural networks with reaction-diffusion terms and the Neumann boundary conditions

Boundary value problems

WeiYuan Zhang²  JunMin Li³ 

[1] Institute of Maths and Applied Mathematics, Xianyang Normal University, Xianyang, ShaanXi, China;School of Science, Xidian University, Shaan Xi Xi'an, China

关键词: neural networks;    reaction-diffusion;    delays;    global exponential synchronization;    Lyapunov functional;   

DOI  :  10.1186/1687-2770-2012-2

学科分类：数学（综合）

来源: SpringerOpen

【 摘 要 】

In this article, a delay-differential equation modeling a bidirectional associative memory (BAM) neural networks (NNs) with reaction-diffusion terms is investigated. A feedback control law is derived to achieve the state global exponential synchronization of two identical BAM NNs with reaction-diffusion terms by constructing a suitable Lyapunov functional, using the drive-response approach and some inequality technique. A novel global exponential synchronization criterion is given in terms of inequalities, which can be checked easily. A numerical example is provided to demonstrate the effectiveness of the proposed results.

【 授权许可】

CC BY