Existence and global exponential stability of anti-periodic solutions for shunting inhibitory cellular neural networks with impulses and continuously distributed delays

被引：0

作者：

Xu, Changjin ^{[1
]}

Zhang, Qiming ^{[2
]}

Liao, Maoxin ^{[3
]}

机构：

[1] Guizhou Key Laboratory of Economics System Simulation, Guizhou University of Finance and Economics, Guiyang, China

[2] College of Science, Hunan University of Technology, Zhuzhou, China

[3] School of Mathematics and Physics, University of South China, Hengyang, China

来源：

Journal of Computational and Theoretical Nanoscience | 2015年 / 12卷 / 10期

关键词：

Asymptotic stability - Cellular neural networks - Fixed point arithmetic;

D O I：

10.1166/jctn.2015.4305

中图分类号：

学科分类号：

摘要：

This paper is concerned with the existence and exponential stability of anti-periodic solutions of shunting inhibitory cellular neural networks with impulses and continuously distributed delays. Applying Krasnoselski's fixed point theorem, inequality techniques and Lyapunov method, sufficient conditions which ensure the existence and exponential stability of anti-periodic solutions of shunting inhibitory neural networks are presented. An example with its numerical simulations is given to illustrate our main results. Our results are new and supplement some previously known ones. Copyright © 2015 American Scientific Publishers.

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页码：3927 / 3935

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