Global exponential stability and periodic solutions of delayed cellular neural networks

被引：64

作者：

Cao, JD ^{[1
]}

机构：

[1] Yunnan Univ, Adult Educ Coll, Kunming 650091, Peoples R China

来源：

JOURNAL OF COMPUTER AND SYSTEM SCIENCES | 2000年 / 60卷 / 01期

关键词：

cellular neural networks; Lyapunov functional; global exponential stability; periodic solution;

D O I：

10.1006/jcss.1999.1658

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, the problems of global exponential stability and periodic solutions for a class of delayed cellular neural networks are analyzed via the method of constructing suitable Lyapunov functionals. Some simple sufficient conditions are given for global exponential stability and the existence of periodic solutions. These conditions can be used to design globally stable networks, and they are easy to check and apply in practice. 2000 Academic Press.

引用

页码：38 / 46

页数：9

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