Linear matrix inequality approach to exponential synchronization of a class of chaotic neural  networks with time-varying delays

doi:10.1088/1009-1963/16/7/014

中国物理B ›› 2007, Vol. 16 ›› Issue (7): 1889-1896.doi: 10.1088/1009-1963/16/7/014

Linear matrix inequality approach to exponential synchronization of a class of chaotic neural networks with time-varying delays

吴炜, 崔宝同

Control Science and Engineering Research Center, Southern Yangtze University, Wuxi 214122, China

收稿日期:2006-03-07 修回日期:2006-11-04 出版日期:2007-07-04 发布日期:2007-07-04
基金资助:
Project supported by the National Natural Science Foundation of China (Grant No 60674026), the Science Foundation of Southern Yangtze University, China.

Linear matrix inequality approach to exponential synchronization of a class of chaotic neural networks with time-varying delays

Wu Wei(吴炜) and Cui Bao-Tong (崔宝同)^†

Control Science and Engineering Research Center, Southern Yangtze University, Wuxi 214122, China

Received:2006-03-07 Revised:2006-11-04 Online:2007-07-04 Published:2007-07-04
Supported by:
Project supported by the National Natural Science Foundation of China (Grant No 60674026), the Science Foundation of Southern Yangtze University, China.

摘要/Abstract

摘要： 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.

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.

Key words: chaotic neural networks, exponential synchronization, linear matrix inequalities

中图分类号: (Neural networks, fuzzy logic, artificial intelligence)

07.05.Mh

05.45.-a (Nonlinear dynamics and chaos)

吴炜, 崔宝同. Linear matrix inequality approach to exponential synchronization of a class of chaotic neural networks with time-varying delays[J]. 中国物理B, 2007, 16(7): 1889-1896.

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[J]. Chinese Physics, 2007, 16(7): 1889-1896.

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Linear matrix inequality approach to exponential synchronization of a class of chaotic neural networks with time-varying delays

Linear matrix inequality approach to exponential synchronization of a class of chaotic neural networks with time-varying delays

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