期刊
NONLINEAR ANALYSIS-REAL WORLD APPLICATIONS
卷 12, 期 6, 页码 3014-3027出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.nonrwa.2011.05.002
关键词
Cellular neural networks; Anti-periodic solution; Exponential stability; Delay; Impulsive effects
资金
- National Natural Science Foundation of China [11072059]
- Natural Science Foundation of Jiangsu Province of China [BK2009271]
In this paper, we discuss anti-periodic solution for delayed cellular neural networks with impulsive effects. By means of contraction mapping principle and Krasnoselski's fixed point theorem, we obtain the existence of anti-periodic solution for neural networks. By establishing a new impulsive differential inequality, using Lyapunov functions and inequality techniques, some new results for exponential stability of anti-periodic solution are obtained. Meanwhile, an example and numerical simulations are given to show that impulses may change the exponentially stable behavior of anti-periodic solution. (C) 2011 Elsevier Ltd. All rights reserved.
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