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The Scientific World Journal
Volume 2014 (2014), Article ID 840185, 10 pages
http://dx.doi.org/10.1155/2014/840185
Research Article

Synchronization Control for Stochastic Neural Networks with Mixed Time-Varying Delays

1School of Instrument Science, Southeast University, Nanjing 210096, China
2College of Information Engineering, Yangzhou University, Yangzhou 225009, China
3School of Automation, Southeast University, Nanjing 210096, China
4Institute of Automation, Chinese Academy of Science, Beijing 100190, China

Received 18 May 2014; Accepted 7 June 2014; Published 2 July 2014

Academic Editor: Guanghui Wen

Copyright © 2014 Qing Zhu 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

Synchronization control of stochastic neural networks with time-varying discrete and continuous delays has been investigated. A novel control scheme is proposed using the Lyapunov functional method and linear matrix inequality (LMI) approach. Sufficient conditions have been derived to ensure the global asymptotical mean-square stability for the error system, and thus the drive system synchronizes with the response system. Also, the control gain matrix can be obtained. With these effective methods, synchronization can be achieved. Simulation results are presented to show the effectiveness of the theoretical results.