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International Symposium on Neural Networks

ISNN 2015: Advances in Neural Networks – ISNN 2015 pp 192–201Cite as

Global Exponential Anti-synchronization of Coupled Memristive Chaotic Neural Networks with Time-Varying Delays

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9377))

Abstract

This paper investigates the problem of global exponential anti-synchronization of a class of memristive chaotic neural networks with time-varying delays. First, a memrsitive neural network is modeled. Then, considering the state-dependent properties of the memristor, a new fuzzy model employing parallel distributed compensation (PDC) provides a new way to analyze the complicated memristive neural networks with only two subsystems. And the controller is dependent on the output of the system in the case of packed circuits. An illustrative example is also presented to show the effectiveness of the results.

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Author information

Authors and Affiliations

  1. Shannon Lab, Huawei Technologies Co., Ltd., Beijing, China

    Zheng Yan, Shuzhan Bi & Xijun Xue

Authors
  1. Zheng Yan
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  2. Shuzhan Bi
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  3. Xijun Xue
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Corresponding author

Correspondence to Zheng Yan .

Editor information

Editors and Affiliations

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

    Xiaolin Hu

  2. Fuzhou University, Fuzhou, China

    Yousheng Xia

  3. School of Information Science and Technology, Sun Yat-sen University, Guangzhou, China

    Yunong Zhang

  4. Chinese Academy of Sciences, Institute of Automation, Beijing, China

    Dongbin Zhao

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© 2015 Springer International Publishing Switzerland

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Yan, Z., Bi, S., Xue, X. (2015). Global Exponential Anti-synchronization of Coupled Memristive Chaotic Neural Networks with Time-Varying Delays. In: Hu, X., Xia, Y., Zhang, Y., Zhao, D. (eds) Advances in Neural Networks – ISNN 2015. ISNN 2015. Lecture Notes in Computer Science(), vol 9377. Springer, Cham. https://doi.org/10.1007/978-3-319-25393-0_22

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  • DOI: https://doi.org/10.1007/978-3-319-25393-0_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25392-3

  • Online ISBN: 978-3-319-25393-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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