Global stability in Lagrange sense for BAM-type Cohen-Grossberg neural networks with time-varying delays

被引：21

作者：

Jian, Jigui ^{[1
]}

Zhao, Zhihua ^{[1
]}

机构：

[1] China Three Gorges Univ, Coll Sci, Yichang 443002, Hubei, Peoples R China

来源：

SYSTEMS SCIENCE & CONTROL ENGINEERING | 2015年 / 3卷 / 01期

基金：

中国国家自然科学基金;

关键词：

BAM-type Cohen-Grossberg neural networks; Lagrange stability; globally attractive set; inequality;

D O I：

10.1080/21642583.2014.881729

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we investigate the positive invariant sets and global exponential attractive sets for a class of bidirectional associative memory (BAM)-type Cohen-Grossberg neural networks with multiple time-varying delays. By applying inequality techniques, some easily verifiable delay-independent criteria for the ultimate boundedness and global exponential attractive sets of BAM-type Cohen-Grossberg neural networks are obtained by constructing appropriate Lyapunov functions. Finally, one example with numerical simulations is given to illustrate the results obtained in this paper.

引用

页码：1 / 7

页数：7

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