Global stability of cellular neural networks with constant and variable delays

被引：70
|
作者：
Li, XM
Huang, LH [1 ]
Zhu, HY
机构：
[1] Hunan Univ, Coll Math & Econometr, Changsha 410082, Hunan, Peoples R China
[2] Nanhua Univ, Dept Math, Hengyang 421001, Hunan, Peoples R China
来源：
NONLINEAR ANALYSIS-THEORY METHODS & APPLICATIONS | 2003年 / 53卷 / 3-4期
关键词：
DCNNs; global asymptotic stability; global exponential stability; variable delay;
D O I：
10.1016/S0362-546X(02)00176-1
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
This paper gives new conditions ensuring global asymptotic stability and global exponential stability for cellular neural networks with constant delay and variable delay, respectively. These conditions are derived by using the essence of piecewise linearity of the output function of cellular neural networks and by constructing Lyapunov functions and fanctionals. Furthermore, these conditions are significantly weaker than those given in existing literature. (C) 2003 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码：319 / 333
页数：15
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