Global exponential stability of cellular neural networks with time-varying discrete and distributed delays

被引：16

作者：

Ma, Keyun ^{[1
]}

Yu, Li ^{[1
]}

Zhang, Wen-an ^{[1
]}

机构：

[1] Zhejiang Univ Technol, Coll Informat Engn, Hangzhou 310032, Zhejiang, Peoples R China

来源：

NEUROCOMPUTING | 2009年 / 72卷 / 10-12期

基金：

国家杰出青年科学基金;

关键词：

Cellular neural networks; Lyapunov-Krasovskii functional; Global exponential stability; Linear matrix inequality (LMI); Delay-dependent criteria; ASYMPTOTIC STABILITY; CRITERION;

D O I：

10.1016/j.neucom.2008.10.001

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper is concerned with the problem of global exponential stability analysis for a class of cellular neural networks with time-varying discrete and distributed delays (DDCNNs). A new delay-dependent sufficient condition is derived for the global exponential stability of the DDCNNs by using the integral inequality method and the newly proposed Lyapunov-Krasovskii functional. The obtained stability condition is less conservative than some of the existing results in the literature. Numerical examples are given to demonstrate the effectiveness and superiority of the proposed results. (C) 2008 Elsevier B.V. All rights reserved.

引用

页码：2705 / 2709

页数：5

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