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Abstract and Applied Analysis
Volume 2013, Article ID 728606, 16 pages
Research Article

Synchronization of Switched Complex Bipartite Neural Networks with Infinite Distributed Delays and Derivative Coupling

1Department of Mathematics and Physics, Jiangsu University of Science and Technology, Zhenjiang 212003, China
2Department of Mathematics, Southeast University, Nanjing 210096, China
3Department of Mathematics, King Abdulaziz University, Jeddah 21589, Saudi Arabia
4Department of Mathematics, Jiangsu University, Zhenjiang 212003, China
5Faculty of Economics and Management, Nanjing University of Aeronautics & Astronautics, Nanjing 212096, China

Received 7 March 2013; Accepted 8 April 2013

Academic Editor: Hongli Dong

Copyright © 2013 Qiuxiang Bian 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.


A new model of switched complex bipartite neural network (SCBNN) with infinite distributed delays and derivative coupling is established. Using linear matrix inequality (LMI) approach, some synchronization criteria are proposed to ensure the synchronization between two SCBNNs by constructing effective controllers. Some numerical simulations are provided to illustrate the effectiveness of the theoretical results obtained in this paper.