Robust adaptive synchronization of chaotic neural networks by slide technique
Lou Xu-Yang(楼旭阳)a)b)† and Cui Bao-Tong(崔宝同)a)‡
a College of Communication and Control Engineering, Jiangnan University, Wuxi 214122, China; b CSIRO Division of Mathematical and Information Sciences, University of Adelaide, Urrbrae 5064, Australia
Abstract In this paper, we focus on the robust adaptive synchronization between two coupled chaotic neural networks with all the parameters unknown and time-varying delay. In order to increase the robustness of the two coupled neural networks, the key idea is that a sliding-mode-type controller is employed. Moreover, without the estimate values of the network unknown parameters taken as an updating object, a new updating object is introduced in the constructing of controller. Using the proposed controller, without any requirements for the boundedness, monotonicity and differentiability of activation functions, and symmetry of connections, the two coupled chaotic neural networks can achieve global robust synchronization no matter what their initial states are. Finally, the numerical simulation validates the effectiveness and feasibility of the proposed technique.
Received: 01 May 2007
Revised: 03 September 2007
Accepted manuscript online:
Fund: Project supported by the National
Natural Science Foundation of China (Grant No 60674026), the Key
Project of Chinese Ministry of Education (Grant No 107058), the
Jiangsu Provincial Natural Science Foundation of China (Grant No
BK2007016) and the Jiangsu Provincial Program for Postgraduate Scientific
Innovative Research of Jiangnan University (Grant No CX07B$_-$116z).
Cite this article:
Lou Xu-Yang(楼旭阳) and Cui Bao-Tong(崔宝同) Robust adaptive synchronization of chaotic neural networks by slide technique 2008 Chin. Phys. B 17 520
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