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
收藏
页码：2374 / 2378
页数：5
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