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.
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页码：1 / 7
页数：7
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