GLOBAL EXPONENTIAL STABILITY AND EXISTENCE OF ANTI-PERIODIC SOLUTIONS TO IMPULSIVE COHEN-GROSSBERG NEURAL NETWORKS ON TIME SCALES

被引：0

作者：

Li, Yongkun ^{[1
]}

Zhang, Tianwei ^{[1
]}

机构：

[1] Yunnan Univ, Dept Math, Kunming 650091, Yunnan, Peoples R China

来源：

TOPOLOGICAL METHODS IN NONLINEAR ANALYSIS | 2015年 / 45卷 / 02期

关键词：

Anti-periodic solution; Cohen-Grossberg neural networks; impulse; time scale; PERIODIC-SOLUTIONS; PARABOLIC EQUATIONS; DISTRIBUTED DELAYS; VARYING DELAYS; INTERPOLATION; SYSTEMS;

D O I：

暂无

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

By using the method of coincidence degree theory and Lyapunov functions, some new criteria are established for the existence and global exponential stability of anti-periodic solutions to impulsive Cohen-Grossberg neural networks on time scales. Our results are new even if the time scale T = R or Z. Finally, an example is given to illustrate our results.

引用

页码：363 / 384

页数：22

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