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Chin. Phys. B, 2013, Vol. 22(5): 050504    DOI: 10.1088/1674-1056/22/5/050504
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Exponential synchronization of coupled memristive neural networks via pinning control

Wang Guan (王冠), Shen Yi (沈轶), Yin Quan (尹泉)
Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;Key Laboratory of Ministry of Education for Image Processing and Intelligent Control, Wuhan 430074, China
Abstract  This paper is concerned with the exponential synchronization problem of coupled memristive neural networks. In contrast to general neural networks, memristive neural networks exhibit state-dependent switching behaviors due to the physical properties of memristors. Under a mild topology condition, it is proved that a small fraction of controlled subsystems can efficiently synchronize the coupled systems. The pinned subsystems are identified via a search algorithm. Moreover, the information exchange network needs not to be undirected or strongly connected. Finally, two numerical simulations are performed to verify the usefulness and effectiveness of our results.
Keywords:  synchronization      memristor      coupled neural networks      pinning control  
Received:  07 September 2012      Revised:  31 October 2012      Accepted manuscript online: 
PACS:  05.45.Gg (Control of chaos, applications of chaos)  
  05.45.Xt (Synchronization; coupled oscillators)  
Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 61134012 and 11271146).
Corresponding Authors:  Shen Yi     E-mail:  yishen64@163.com

Cite this article: 

Wang Guan (王冠), Shen Yi (沈轶), Yin Quan (尹泉) Exponential synchronization of coupled memristive neural networks via pinning control 2013 Chin. Phys. B 22 050504

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