Abstract and Applied Analysis
Volume 2011 (2011), Article ID 297147, 17 pages
http://dx.doi.org/10.1155/2011/297147
Research Article

Stochastic Dynamics of Nonautonomous Cohen-Grossberg Neural Networks

Chuangxia Huang1 and Jinde Cao2

1College of Mathematics and Computing Science, Changsha University of Science and Technology, Changsha 410114, China
2Department of Mathematics, Southeast University, Nanjing 210096, China

Received 15 February 2011; Accepted 21 March 2011

Academic Editor: Yong Zhou

Copyright © 2011 Chuangxia Huang and Jinde Cao. 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

This paper is devoted to the study of the stochastic stability of a class of Cohen-Grossberg neural networks, in which the interconnections and delays are time-varying. With the help of Lyapunov function, Burkholder-Davids-Gundy inequality, and Borel-Cantell's theory, a set of novel sufficient conditions on pth moment exponential stability and almost sure exponential stability for the trivial solution of the system is derived. Compared with the previous published results, our method does not resort to the Razumikhin-type theorem and the semimartingale convergence theorem. Results of the development as presented in this paper are more general than those reported in some previously published papers. An illustrative example is also given to show the effectiveness of the obtained results.