Stabilization effect of diffusion in delayed neural networks systems with Dirichlet boundary conditions

被引：6

作者：

Chen, Zhang ^{[1
]}

Zhao, Donghua ^{[2
]}

机构：

[1] Shandong Univ, Sch Math, Jinan 250100, Peoples R China

[2] Fudan Univ, Sch Math Sci, Minist Educ, Key Lab Math Nonlinear Sci, Shanghai 200433, Peoples R China

来源：

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2011年 / 348卷 / 10期

基金：

中国国家自然科学基金;

关键词：

TIME-VARYING DELAYS; GLOBAL EXPONENTIAL STABILITY; ASYMPTOTIC STABILITY; DYNAMIC-ANALYSIS; MU-STABILITY; TERMS;

D O I：

10.1016/j.jfranklin.2011.09.011

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, reaction-diffusion neural networks with unbounded time-varying delays and Dirichlet boundary conditions is studied. A new concept of global mu-stability in the sense of L(2) norm is introduced, and sufficient conditions are given to guarantee global mu-stability of the equilibrium point. The results obtained not only improve those in the earlier findings, but also show diffusion terms contribute to stabilization of neural networks systems. (C) 2011 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

引用

页码：2884 / 2897

页数：14

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