Journal of Inequalities and Applications
Volume 2010 (2010), Article ID 132790, 19 pages
doi:10.1155/2010/132790
Research Article

Existence and Stability of Antiperiodic Solution for a Class of Generalized Neural Networks with Impulses and Arbitrary Delays on Time Scales

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

Received 14 June 2010; Accepted 16 August 2010

Academic Editor: Kok Lay Teo

Copyright © 2010 Yongkun Li et al. 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

By using coincidence degree theory and Lyapunov functions, we study the existence and global exponential stability of antiperiodic solutions for a class of generalized neural networks with impulses and arbitrary delays on time scales. Some completely new sufficient conditions are established. Finally, an example is given to illustrate our results. These results are of great significance in designs and applications of globally stable anti-periodic Cohen-Grossberg neural networks with delays and impulses.