PERIODIC SOLUTIONS OF HIGH-ORDER COHEN-GROSSBERG NEURAL NETWORKS WITH TIME-VARYING DELAYS

被引：0

作者：

Liu, Qiming ^{[1
]}

机构：

[1] Shijiazhuang Mech Engn Coll, Inst Appl Math, Shijiazhuang 050003, Hebei, Peoples R China

来源：

ADVANCES IN DIFFERENTIAL EQUATIONS AND CONTROL PROCESSES | 2010年 / 6卷 / 01期

关键词：

Cohen-Grossberg neural networks; periodic solution; delay; global stability;

D O I：

暂无

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

A class of high-order Cohen-Grossberg neural networks with time-varying delays is investigated in this paper. Sufficient conditions to guarantee the uniqueness and global exponential stability of periodic solutions of such networks are established by using suitable Lyapunov functional and the properties of M-matrix. The results in this paper improve the earlier publications.

引用

页码：1 / 14

页数：14

共 19 条

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