Global exponential stability of periodic neural networks with time-varying delays

被引：39

作者：

Jiang, Haijun ^{[1
]}

Cao, Jinde

机构：

[1] Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830046, Peoples R China

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

来源：

NEUROCOMPUTING | 2006年 / 70卷 / 1-3期

基金：

中国国家自然科学基金;

关键词：

neural networks; variable coefficients; time-varying delays; global exponential stability; periodic solution;

D O I：

10.1016/j.neucom.2006.01.021

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we consider the periodic neural networks with variable coefficients and time-varying delays, and investigate the existence of periodic solution and its global exponential stability. Various sufficient conditions ensuring the existence of periodic and its global exponential stability are given. The results obtained in this paper extend and generalize those given in previous literature. (c) 2006 Elsevier B.V. All rights reserved.

引用

页码：343 / 350

页数：8

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