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Circuitry Analog and Synchronization of Hyperchaotic Neuron Model

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Advances in Neural Networks - ISNN 2008 (ISNN 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5264))

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Abstract

Recently, a general model of nonlinear systems with distributed delays is studied and a four-dimensional continuous autonomous chaotic neuron model is found and analyzed. In this paper, circuitry analog of the chaotic neuron model is introduced. Adaptive chaos synchronization scheme is presented and analyzed. A series of computer simulations demonstrated the effectiveness of the proposed synchronization schemes.

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References

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Author information

Authors and Affiliations

  1. School of Electronics & Information Engineering, Southwest University, 400715, Chongqing, P.R. China

    Shukai Duan & Lidan Wang

  2. College of Automation, Chongqing University, 400044, Chongqing, P.R. China

    Shukai Duan

Authors
  1. Shukai Duan
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  2. Lidan Wang
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Tsinghu University, 100084, Beijing, China

    Fuchun Sun

  2. Institute TAMS (Technical Aspects of Multimodal Systems), department of Informatics, University of Hamburg, Vogt-Koelln-Straße 30, 22527, Hamburg, Germany

    Jianwei Zhang

  3. Intel China Research Center, 8/F, Peking University, Department of Machine Intelligence, 100871, Beijing, China

    Ying Tan

  4. Department of Mathematics, Southeast University, 210096, Nanjing, China

    Jinde Cao

  5. Departamento de Control Automático, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, 07360, México D.F., México

    Wen Yu

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© 2008 Springer-Verlag Berlin Heidelberg

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Duan, S., Wang, L. (2008). Circuitry Analog and Synchronization of Hyperchaotic Neuron Model. In: Sun, F., Zhang, J., Tan, Y., Cao, J., Yu, W. (eds) Advances in Neural Networks - ISNN 2008. ISNN 2008. Lecture Notes in Computer Science, vol 5264. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87734-9_66

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  • DOI: https://doi.org/10.1007/978-3-540-87734-9_66

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87733-2

  • Online ISBN: 978-3-540-87734-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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