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International Symposium on Neural Networks

ISNN 2011: Advances in Neural Networks – ISNN 2011 pp 213–221Cite as

Synchronization of Nonidentical Chaotic Neural Networks with Time-Varying Delays

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6675))

Abstract

In this paper, the problem on synchronization of two nonidentical chaotic neural networks with time-varying delays is investigated. By constructing a proper sliding surface, and employing a combination of the free-weighting matrix method, inequality technique and Lyapunov theory, a sliding mode controller is designed to achieve the asymptotical synchronization of two nonidentical chaotic neural networks with time-varying delays. The provided condition is expressed in terms of linear matrix inequalities (LMIs), and is dependent on the time delay. A simulation example is given to show the effectiveness.

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Author information

Authors and Affiliations

  1. Department of Mathematics, Chongqing Jiaotong University, Chongqing, 400074, China

    Qiankun Song

Authors
  1. Qiankun Song
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Editor information

Editors and Affiliations

  1. Institute of Automation, Key Laboratory of Complex Systems and Intelligence Science, Chinese Academy of Sciences, 100190, Beijing, China

    Derong Liu

  2. College of Information Science and Engineering, Shenyang, Northeastern University, 110004, Liaoing, China

    Huaguang Zhang

  3. Department of Electrical and Computer Engineering, University of Cyprus, 75 Kallipoleos Avenue, 1678, Nicosia, Cyprus

    Marios Polycarpou

  4. Dipartimento di Elettronica, Politecnico di Milano, Piazza L. da Vinci 32, 20133, Milano, Italy

    Cesare Alippi

  5. Deptartment of Electrical, Computer and Biomedical Engineering, University of Rhode Island, RI 02881, Kingston, USA

    Haibo He

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© 2011 Springer-Verlag Berlin Heidelberg

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Song, Q. (2011). Synchronization of Nonidentical Chaotic Neural Networks with Time-Varying Delays. In: Liu, D., Zhang, H., Polycarpou, M., Alippi, C., He, H. (eds) Advances in Neural Networks – ISNN 2011. ISNN 2011. Lecture Notes in Computer Science, vol 6675. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21105-8_26

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  • DOI: https://doi.org/10.1007/978-3-642-21105-8_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21104-1

  • Online ISBN: 978-3-642-21105-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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