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Mathematical Problems in Engineering
Volume 2014 (2014), Article ID 934592, 10 pages
http://dx.doi.org/10.1155/2014/934592
Research Article

Global Exponential Stability for DCNNs with Impulses on Time Scales

Department of Mathematics, Yunnan University, Kunming, Yunnan 650091, China

Received 25 September 2013; Accepted 17 December 2013; Published 2 January 2014

Academic Editor: Lu Zhen

Copyright © 2014 Yongkun Li and Yuanhong Zhi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A class of delayed cellular neural networks (DCNNs) with impulses on time scales is considered. By using the topological degree theory, and the time scale calculus theory some sufficient conditions are derived to ensure the existence, uniqueness, and global exponential stability of equilibria for this class of neural networks. Finally, a numerical example illustrates the feasibility of our results and also shows that the continuous-time neural network and the discrete-time analogue have the same dynamical behaviors. The results of this paper are completely new and complementary to the previously known results.