Global exponential periodicity and stability of cellular neural networks with variable and distributed delays

被引：28

作者：

Zhou, Liqun ^{[1
]}

Hu, Guangda ^{[2
]}

机构：

[1] Tianjin Normal Univ, Sci Math Coll, Tianjin 300387, Peoples R China

[2] Univ Sci & Technol Beijing, Dept Automat, Beijing 100083, Peoples R China

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2008年 / 195卷 / 02期

关键词：

cellular neural networks; variable delays; distributed delay; global exponential periodicity; global exponential stability;

D O I：

10.1016/j.amc.2007.04.114

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, global exponential periodicity and stability are investigated for cellular neural networks with variable and distributed delays. Without assuming the differentiability, boundedness and monotonicity of the activation functions, some new sufficient conditions are derived for checking global exponential periodicity, existence and uniqueness of periodic solution for this system based on Laypunov functional, Halanay inequality and mathematical induction. The criteria given are easily verifiable. Some examples are given to illustrate the correctness of our results. (c) 2007 Elsevier Inc. All rights reserved.

引用

页码：402 / 411

页数：10

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