Periodic solutions and exponential stability in delayed cellular neural networks

被引：100

作者：

Cao, JD ^{[1
]}

机构：

[1] Yunnan Univ, Adult Educ Coll, Kunming 650091, Peoples R China

来源：

PHYSICAL REVIEW E | 1999年 / 60卷 / 03期

关键词：

D O I：

10.1103/PhysRevE.60.3244

中图分类号：

O35 [流体力学]; O53 [等离子体物理学];

学科分类号：

070204 ; 080103 ; 080704 ;

摘要：

Some simple sufficient conditions are given ensuring global exponential stability and the existence of periodic solutions of delayed cellular neural networks (DCNNs) by constructing suitable Lyapunov functionals and some analysis techniques. These conditions are easy to check in terms of system parameters and have important leading significance in the design and applications of globally stable DCNNs and periodic oscillatory DCNNs. In addition, two examples are given to illustrate the theory. [S1063-651X(99)05909-7].

引用

页码：3244 / 3248

页数：5

共 15 条

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