Synchronization and Parameter Identification for a Class of Chaotic Neural Networks with Time-Varying Delays Via Adaptive Control

Authors:
Zhongsheng Wang;Yanjun Liang;Nin Yan
Affiliations:
College of Automation, Guangdong Polytechnic Normal University, Guangzhou, P.R. China 510635;College of Information Science and Engineering, Ocean University of China, Qingdao, China 266071;College of Automation, Guangdong Polytechnic Normal University, Guangzhou, P.R. China 510635
Venue:
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Year:
2008

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Abstract

The paper aims to present a new synchronization and parameter identification scheme for a class of time-varying neural networks. By combining the adaptive control method and the Razumikhin-type Theorem, a novel delay-independent and decentralized linear-feedback control with appropriate updated law is designed to achieve the synchronization and parameter identification. The updating law of parameters can be directly constructed. Hopfield neural networks with time-varying delays are given to show the effectiveness of the presented synchronization scheme.