Abstract In this paper, a synchronization scheme for a class of chaotic neural networks with time-varying delays is presented. This class of chaotic neural networks covers several well-known neural networks, such as Hopfield neural networks, cellular neural networks, and bidirectional associative memory networks. The obtained criteria are expressed in terms of linear matrix inequalities, thus they can be efficiently verified. A comparison between our results and the previous results shows that our results are less restrictive.
Received: 07 March 2006
Revised: 04 November 2006
Accepted manuscript online:
Fund: Project supported by the
National Natural Science Foundation of China (Grant No
60674026), the Science Foundation of Southern Yangtze
University, China.
Cite this article:
Wu Wei(吴炜) and Cui Bao-Tong (崔宝同) Linear matrix inequality approach to exponential synchronization of a class of chaotic neural networks with time-varying delays 2007 Chinese Physics 16 1889
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