Abstract and Applied Analysis
Volume 2009 (2009), Article ID 957475, 15 pages
doi:10.1155/2009/957475
Research Article

Existence and Exponential Stability of Periodic Solution for a Class of Generalized Neural Networks with Arbitrary Delays

Yimin Zhang,1 Yongkun Li,2 and Kuohui Ye2

1Department of Mathematics, Zhaotong Teacher's College, Zhaotong, Yunnan 657000, China
2Department of Mathematics, Yunnan University, Kunming, Yunnan 650091, China

Received 4 August 2009; Accepted 1 December 2009

Academic Editor: Jean Mawhin

Copyright © 2009 Yimin Zhang 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 the continuation theorem of coincidence degree and M-matrix theory, we obtain some sufficient conditions for the existence and exponential stability of periodic solutions for a class of generalized neural networks with arbitrary delays, which are milder and less restrictive than those of previous known criteria. Moreover our results generalize and improve many existing ones.