Global exponential robust stability of delayed neural networks

被引：18

作者：

Li, XL ^{[1
]}

Cao, JD ^{[1
]}

机构：

[1] Southeast Univ, Dept Math, Nanjing 210096, Peoples R China

来源：

INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS | 2004年 / 14卷 / 08期

基金：

中国国家自然科学基金;

关键词：

neural networks; time delays; global exponential robust stability; Lyapunov functional;

D O I：

10.1142/S0218127404011119

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

In this paper, several simple and new conditions are presented to ensure existence, uniqueness and global exponential robust stability of the equilibrium point of neural networks with delays by using contraction mapping principle, homeomorphism property and Lyapunov method. The conditions given in this paper are easy to verify and apply, and the obtained results improve and extend to those in the literature. In addition, two examples are given to show the effectiveness of the proposed results.

引用

页码：2925 / 2931

页数：7

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