New LMI conditions for delay-dependent asymptotic stability of delayed Hopfield neural networks

被引：50

作者：

Lou, Xuyang ^{[1
]}

Cui, Baotong ^{[1
]}

机构：

[1] So Yangtze Univ, Res Ctr Control Sci & Engn, Wuxi 214122, Jiangsu, Peoples R China

来源：

NEUROCOMPUTING | 2006年 / 69卷 / 16-18期

基金：

中国国家自然科学基金;

关键词：

asymptotic stability; Hopfield neural networks; delay-dependent; Lyapunov functional; linear matrix inequality;

D O I：

10.1016/j.neucom.2006.02.019

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, new delay-dependent asymptotic stability conditions for delayed Hopfield neural networks are given in terms of a linear matrix inequality, which are less conservative than existing ones in the literature. The conditions guarantee the existence of a unique equilibrium point and its global asymptotic stability of a given delayed Hopfield neural network. (c) 2006 Elsevier B.V. All rights reserved.

引用

页码：2374 / 2378

页数：5

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