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Robust Multistability and Multiperiodicity of Neural Networks with Time Delays

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Advances in Neural Networks – ISNN 2015 (ISNN 2015)

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

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Abstract

In this paper, we are concerned with the robust multistability and multiperiodicity of delayed neural networks. A set of sufficient conditions ensuring the coexistence of 2n periodic solutions and their local stability are presented. And the attraction basin of each periodic solution can be enlarged by rigorous analysis.

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Authors and Affiliations

  1. School of Mathematics, Shanghai University of Finance and Economics, Shanghai, P.R. China

    Lili Wang

Authors
  1. Lili Wang
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Correspondence to Lili Wang .

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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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Wang, L. (2015). Robust Multistability and Multiperiodicity of Neural Networks with Time 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_17

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  • DOI: https://doi.org/10.1007/978-3-319-25393-0_17

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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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