Table of Contents
Advances in Artificial Neural Systems
Volume 2013, Article ID 908602, 5 pages
Research Article

Globally Exponential Stability of Impulsive Neural Networks with Given Convergence Rate

Department of Mathematics, Shandong Normal University, Ji'nan 250014, China

Received 29 November 2012; Accepted 12 April 2013

Academic Editor: Manwai Mak

Copyright © 2013 Chengyan Liu 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.


This paper deals with the stability problem for a class of impulsive neural networks. Some sufficient conditions which can guarantee the globally exponential stability of the addressed models with given convergence rate are derived by using Lyapunov function and impulsive analysis techniques. Finally, an example is given to show the effectiveness of the obtained results.