Existence and global convergence of periodic solution of delayed neural networks

被引：7

作者：

Yuan, Zhaohui ^{[1
]}

Yuan, Lifen ^{[2
]}

机构：

[1] Hunan Univ, Coll Math & Econometr, Changsha 410082, Hunan, Peoples R China

[2] Hunan Normal Univ, Coll Informat Sci, Changsha 410081, Hunan, Peoples R China

来源：

MATHEMATICAL AND COMPUTER MODELLING | 2008年 / 48卷 / 1-2期

基金：

中国国家自然科学基金;

关键词：

convergence; periodic solution; exponential stability; neural networks; delay;

D O I：

10.1016/j.mcm.2007.08.010

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This paper is concerned with the existence and global convergence of a periodic solution of delayed neural networks. Employing Schauder fixed point theorem, we obtain some novel sufficient conditions ensuring the existence as well as the global convergence of the periodic solution. Our results are new and improve some previously known results since these results are based on integral average values of the coefficients. The theoretical analysis is verified by numerical simulations. (C) 2007 Elsevier Ltd. All rights reserved.

引用

页码：101 / 113

页数：13

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