Novel delay-dependent global asymptotic stability condition of Hopfield neural networks with delays

被引：3

作者：

Yang, Degang ^{[1
,2
]}

Hu, Chunyan ^{[1
]}

机构：

[1] Chongqing Normal Univ, Dept Math & Comp Sci, Chongqing 400047, Peoples R China

[2] Chongqing Univ, Dept Comp Sci & Engn, Chongqing 400044, Peoples R China

来源：

COMPUTERS & MATHEMATICS WITH APPLICATIONS | 2009年 / 57卷 / 11-12期

基金：

中国国家自然科学基金;

关键词：

Global asymptotic stability; Hopfield neural networks; Linear matrix inequality; Lyapunov functional method; ROBUST STABILITY; SYSTEMS;

D O I：

10.1016/j.camwa.2008.10.047

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, the global asymptotic stability of Hopfield neural networks with delays is investigated. Distinct differences from other analytical approaches lie in transforming to an equivalent system by using a parameterized transformation which allows free variables in an operator. A novel, less conservative and restrictive criterion than those established in the earlier references is given in terms of several matrix inequalities by utilizing the Lyapunov theory and matrix inequality framework. The results are related to the size of delays. Numerical examples are given to show the effectiveness of our proposed method. (c) 2009 Elsevier Ltd. All rights reserved.

引用

页码：1978 / 1984

页数：7

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