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International Symposium on Neural Networks

ISNN 2014: Advances in Neural Networks – ISNN 2014 pp 27–34Cite as

Anti-Synchronization Control for Memristor-Based Recurrent Neural Networks

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8866))

Abstract

In this paper, we consider the simplified memristor-based neural networks with time-varying delay, under the framework of Filippov’s solution and differential inclusion theory, by structuring novel Lyapunov functional and employing feedback control technique, adopting feedback controller, anti-synchronization criteria for memristor-based neural networks with time-varying delay are derived, which depend on the jumps parameter \(T_i\), hence the proposed criteria are more general than existing reference. Finally, an example is provided to show the effectiveness of theoretical result.

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Author information

Authors and Affiliations

  1. Department of Mathematics, Research Center for Complex Systems and Network Sciences, Southeast University, Nanjing, 210096, China

    Ning Li, Jinde Cao & Mengzhe Zhou

  2. Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah, 21589, Saudi Arabia

    Jinde Cao

Authors
  1. Ning Li
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  2. Jinde Cao
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  3. Mengzhe Zhou
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Corresponding author

Correspondence to Ning Li .

Editor information

Editors and Affiliations

  1. Wuhan, China

    Zhigang Zeng

  2. University of Macau, Macau, Macao

    Yangmin Li

  3. The Chinese University of Hong Kong, Hong Kong, Hong Kong, Hong Kong SAR

    Irwin King

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© 2014 Springer International Publishing Switzerland

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Cite this paper

Li, N., Cao, J., Zhou, M. (2014). Anti-Synchronization Control for Memristor-Based Recurrent Neural Networks. In: Zeng, Z., Li, Y., King, I. (eds) Advances in Neural Networks – ISNN 2014. ISNN 2014. Lecture Notes in Computer Science(), vol 8866. Springer, Cham. https://doi.org/10.1007/978-3-319-12436-0_4

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  • DOI: https://doi.org/10.1007/978-3-319-12436-0_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12435-3

  • Online ISBN: 978-3-319-12436-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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