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Abstract and Applied Analysis
Volume 2013 (2013), Article ID 814692, 14 pages
http://dx.doi.org/10.1155/2013/814692
Research Article

Robust Synchronization Criterion for Coupled Stochastic Discrete-Time Neural Networks with Interval Time-Varying Delays, Leakage Delay, and Parameter Uncertainties

1School of Electrical Engineering, Chungbuk National University, 52 Naesudong-ro, Heungdeok-gu, Cheongju 361-763, Republic of Korea
2Department of Electrical Engineering, Yeungnam University, 214-1 Dae-Dong, Gyeongsan 712-749, Republic of Korea
3School of Electronic Engineering, Daegu University, Gyeongsan 712-714, Republic of Korea
4Department of Biomedical Engineering, School of Medicine, Chungbuk National University, 52 Naesudong-ro, Heungdeok-gu, Cheongju 361-763, Republic of Korea

Received 6 September 2012; Accepted 10 December 2012

Academic Editor: José J. Oliveira

Copyright © 2013 M. J. Park 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

The purpose of this paper is to investigate a delay-dependent robust synchronization analysis for coupled stochastic discrete-time neural networks with interval time-varying delays in networks coupling, a time delay in leakage term, and parameter uncertainties. Based on the Lyapunov method, a new delay-dependent criterion for the synchronization of the networks is derived in terms of linear matrix inequalities (LMIs) by constructing a suitable Lyapunov-Krasovskii’s functional and utilizing Finsler’s lemma without free-weighting matrices. Two numerical examples are given to illustrate the effectiveness of the proposed methods.