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

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Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence (ICIC 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5227))

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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.

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Author information

Authors and Affiliations

  1. College of Automation, Guangdong Polytechnic Normal University, Guangzhou, P.R. China, 510635

    Zhongsheng Wang & Nin Yan

  2. College of Information Science and Engineering, Ocean University of China, Qingdao, China, 266071

    Yanjun Liang

Authors
  1. Zhongsheng Wang
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  2. Yanjun Liang
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  3. Nin Yan
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Editor information

De-Shuang Huang Donald C. Wunsch II Daniel S. Levine Kang-Hyun Jo

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© 2008 Springer-Verlag Berlin Heidelberg

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Wang, Z., Liang, Y., Yan, N. (2008). Synchronization and Parameter Identification for a Class of Chaotic Neural Networks with Time-Varying Delays Via Adaptive Control. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2008. Lecture Notes in Computer Science(), vol 5227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85984-0_15

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  • DOI: https://doi.org/10.1007/978-3-540-85984-0_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85983-3

  • Online ISBN: 978-3-540-85984-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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