Exponential stability of periodic solution to Cohen-Grossberg-type BAM networks with time-varying delays

被引：45

作者：

Xiang, Hongjun ^{[1
,2
]}

Cao, Jinde ^{[1
]}

机构：

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

[2] Xiangnan Univ, Dept Math, Chenzhou 423000, Peoples R China

来源：

NEUROCOMPUTING | 2009年 / 72卷 / 7-9期

基金：

美国国家科学基金会; 中国国家自然科学基金;

关键词：

Cohen-Grossberg-type; BAM neural networks; Periodic solution; Invariant set; Exponential stability; Storage patterns; Memory patterns; BIDIRECTIONAL ASSOCIATIVE MEMORY; GLOBAL ASYMPTOTIC STABILITY; NEURAL-NETWORKS; INDEPENDENT STABILITY; QUALITATIVE-ANALYSIS; ROBUST STABILITY; EXISTENCE;

D O I：

10.1016/j.neucom.2008.07.006

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Periodic solutions can represent various Storage patterns or memory patterns in some applications. In this paper, the existence and global exponential stability of periodic solution are discussed for the Cohen-Grossberg-type bidirectional associative memory (BAM) neural networks with time-varying delays. By applying the analysis method and inequality technique, some novel sufficient conditions are obtained to ensure the existence, uniqueness, global attractivity and exponential stability of the periodic solution to the considered system. Moreover, two examples are also given to demonstrate the feasibility of the obtained results. (C) 2008 Elsevier B.V. All rights reserved.

引用

页码：1702 / 1711

页数：10

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