Table of Contents
ISRN Discrete Mathematics
Volume 2012 (2012), Article ID 831715, 10 pages
http://dx.doi.org/10.5402/2012/831715
Research Article

Global Exponential Stability of Discrete-Time Multidirectional Associative Memory Neural Network with Variable Delays

College of Science, Hunan Agricultural University, Hunan, Changsha 410128, China

Received 3 July 2012; Accepted 20 September 2012

Academic Editors: C.-K. Lin and W. F. Smyth

Copyright © 2012 Min Wang 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

A discrete-time multidirectional associative memory neural networks model with varying time delays is formulated by employing the semidiscretization method. A sufficient condition for the existence of an equilibrium point is given. By calculating difference and using inequality technique, a sufficient condition for the global exponential stability of the equilibrium point is obtained. The results are helpful to design global exponentially stable multidirectional associative memory neural networks. An example is given to illustrate the effectiveness of the results.