LMI-based criteria for global robust stability of bidirectional associative memory networks with time delay

被引：118

作者：

Cao, Jinde ^{[1
]}

Ho, Daniel W. C.

Huang, Xia

机构：

[1] SE Univ, Dept Math, Nanjing 210096, Peoples R China

[2] City Univ Hong Kong, Dept Math, Hong Kong, Hong Kong, Peoples R China

来源：

NONLINEAR ANALYSIS-THEORY METHODS & APPLICATIONS | 2007年 / 66卷 / 07期

基金：

中国国家自然科学基金;

关键词：

global robust stability; BAM neural networks; Linear Matrix Inequality (LMI); Lyapunov function;

D O I：

10.1016/j.na.2006.02.009

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, several new sufficient conditions are given to ensure existence, uniqueness and globally exponential robust stability of the equilibrium point for bidirectional associative memory (BAM) networks with delays. This novel approach, based on the Linear Matrix Inequality (LMI) technique, removes some existing restrictions on the system's parameters, and the derived conditions are easy to verify via the LMI toolbox. In addition, two examples are given to show the effectiveness and the advantage of the proposed results. (c) 2006 Elsevier Ltd. All rights reserved.

引用

页码：1558 / 1572

页数：15

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