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Advances in Mathematical Physics
Volume 2013 (2013), Article ID 732406, 6 pages
http://dx.doi.org/10.1155/2013/732406
Research Article

LMI-Based Stability Criteria for Discrete-Time Neural Networks with Multiple Delays

Hui Xu1,2 and Ranchao Wu1

1School of Mathematics, Anhui University, Hefei 230039, China
2Department of Public Teaching, Anhui Business Vocational College, Hefei 230041, China

Received 17 March 2013; Accepted 26 May 2013

Academic Editor: Wen Xiu Ma

Copyright © 2013 Hui Xu and Ranchao Wu. 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

Discrete neural models are of great importance in numerical simulations and practical implementations. In the current paper, a discrete model of continuous-time neural networks with variable and distributed delays is investigated. By Lyapunov stability theory and techniques such as linear matrix inequalities, sufficient conditions guaranteeing the existence and global exponential stability of the unique equilibrium point are obtained. Introduction of LMIs enables one to take into consideration the sign of connection weights. To show the effectiveness of the method, an illustrative example, along with numerical simulation, is presented.