Existence and globally exponential stability of periodic solution of BAM neural networks with impulses and recent-history distributed delays

被引：25

作者：

Gu, Haibo ^{[1
]}

Jiang, Haijun ^{[1
]}

Teng, Zhidong ^{[1
]}

机构：

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

来源：

NEUROCOMPUTING | 2008年 / 71卷 / 4-6期

基金：

中国国家自然科学基金;

关键词：

neural networks; impulses; periodic solution; globally exponential stability;

D O I：

10.1016/j.neucom.2007.03.007

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, a class of generalized bi-directional associative memory (BAM) neural networks with recent history distributed delays and impulses are considered. By using Lyapunov functional method and fixed point theorem, we derive several sufficient conditions for the existence and globally exponential stability of a unique periodic solution of the networks. The results of this paper ate new and different from previously known results. (c) 2007 Elsevier B.V. All rights reserved.

引用

页码：813 / 822

页数：10

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