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Abstract and Applied Analysis
Volume 2014, Article ID 938612, 9 pages
Research Article

Finite-Time Synchronizing Control for Chaotic Neural Networks

National Engineering Research Center of Advanced Rolling, University of Science and Technology Beijing, Beijing 100083, China

Received 11 April 2014; Revised 4 June 2014; Accepted 4 June 2014; Published 17 June 2014

Academic Editor: Hongli Dong

Copyright © 2014 Chao Zhang 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.


This paper addresses the finite-time synchronizing problem for a class of chaotic neural networks. In a real communication network, parameters of the master system may be time-varying and the system may be perturbed by external disturbances. A simple high-gain observer is designed to track all the nonlinearities, unknown system functions, and disturbances. Then, a dynamic active compensatory controller is proposed and by using the singular perturbation theory, the control method can guarantee the finite-time stability of the error system between the master system and the slave system. Finally, two illustrative examples are provided to show the effectiveness and applicability of the proposed scheme.