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Chin. Phys. B, 2013, Vol. 22(11): 110504    DOI: 10.1088/1674-1056/22/11/110504
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H synchronization of chaotic neural networks with time-varying delays

O. M. Kwona, M. J. Parka, Ju H. Parkb, S. M. Leec, E. J. Chad
a School of Electrical Engineering, Chungbuk National University, 52 Naesudong-ro, Heungdeok-gu, Cheongju 361-763, Republic of Korea;
b Department of Electrical Engineering, Yeungnam University, 214-1 Dae-Dong, Kyongsan 712-749, Republic of Korea;
c School of Electronic Engineering, Daegu University, Gyungsan 712-714, Republic of Korea;
d Department of Biomedical Engineering, School of Medicine, Chungbuk National University, 52 Naesudong-ro, Heungdeok-gu, Cheongju 361-763, Republic of Korea
Abstract  In this paper, we investigate the problem of H synchronization for chaotic neural networks with time-varying delays. A new model of the networks with disturbances in both master and slave systems is presented. By constructing a suitable Lyapunov–Krasovskii functional and using a reciprocally convex approach, a novel H synchronization criterion for the networks concerned is established in terms of linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. Two numerical examples are given to illustrate the effectiveness of the proposed method.
Keywords:  chaotic neural networks      time-varying delays      H synchronization      Lyapunov method  
Received:  01 March 2013      Revised:  06 May 2013      Accepted manuscript online: 
PACS:  05.65.+b (Self-organized systems)  
  02.01.Yn  
Fund: Project supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (Grant No. 2012-0000479) and the Korea Healthcare Technology R&D Project, Ministry of Health and Welfare, Republic of Korea (Grant No. A100054).
Corresponding Authors:  Ju H. Park     E-mail:  jessie@ynu.ac.kr

Cite this article: 

O. M. Kwon, M. J. Park, Ju H. Park, S. M. Lee, E. J. Cha H synchronization of chaotic neural networks with time-varying delays 2013 Chin. Phys. B 22 110504

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