Journal
MATHEMATICAL AND COMPUTER MODELLING
Volume 55, Issue 3-4, Pages 837-843Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.mcm.2011.09.009
Keywords
Global exponential stability; Time-varying delays; Impulsive cellular neural networks; Lyapunov function; Razumikhin technique
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Funding
- National Natural Science Foundations of China (NSFC) [11026182, 61175119, 61074011]
- Program for New Century Excellent Talents in University [NCET-10-0329]
- Alexander von Humboldt Foundation of Germany
- Natural Science Foundation of Jiangsu Province of China [BK2010408]
- Zhejiang Innovation Project [T200905]
- Natural Science Foundation of Zhejiang Province of China [Y6100007]
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In this paper, the issue of global exponential stability for impulsive cellular neural networks (CNN) with time-varying delays is investigated. Based on Lyapunov functions and the Razumikhin technique, some new stability criteria with an exponential convergence rate are derived. Our results show that impulses play an important role in making cellular neural networks globally exponentially stable even if it may be unstable without impulses. Furthermore, the impulsive moments are independent on the upper bound of the delay function used in our results. Hence, compared with the method of Lyapunov functionals as in many previous studies, our results are less conservative and more effective for stability analysis. (C) 2011 Elsevier Ltd. All rights reserved.
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