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Stability Analysis of Periodic Orbits in Digital Spiking Neurons

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Neural Information Processing (ICONIP 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9948))

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Abstract

This paper considers stability of various periodic spike-trains from digital spiking neuron constructed by two coupled shift registers. The dynamics is integrated into a digital spike map defined on a set of points. In order to analyze the stability, we introduce two simple feature quantities that characterize plentifulness and superstability of the periodic spike-trains. Using the feature quantities, stability of typical examples is investigated.

T. Saito—This work is supported in part by JSPS KAKENHI\(\#\)15K00350.

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Authors and Affiliations

  1. Hosei University, Koganei, Tokyo, 184-8584, Japan

    Tomoki Hamaguchi, Kei Yamaoka & Toshimichi Saito

Authors
  1. Tomoki Hamaguchi
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  2. Kei Yamaoka
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  3. Toshimichi Saito
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Corresponding author

Correspondence to Toshimichi Saito .

Editor information

Editors and Affiliations

  1. The University of Tokyo, Tokyo, Japan

    Akira Hirose

  2. Kobe University, Kobe, Japan

    Seiichi Ozawa

  3. Okinawa Institute of Science and Technology Graduate University, Onna, Japan

    Kenji Doya

  4. Nara Institute of Science and Technology, Ikoma, Japan

    Kazushi Ikeda

  5. Kyungpook National University, Daegu, Korea (Republic of)

    Minho Lee

  6. Chinese Academy of Sciences, Beijing, China

    Derong Liu

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Hamaguchi, T., Yamaoka, K., Saito, T. (2016). Stability Analysis of Periodic Orbits in Digital Spiking Neurons. In: Hirose, A., Ozawa, S., Doya, K., Ikeda, K., Lee, M., Liu, D. (eds) Neural Information Processing. ICONIP 2016. Lecture Notes in Computer Science(), vol 9948. Springer, Cham. https://doi.org/10.1007/978-3-319-46672-9_38

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  • DOI: https://doi.org/10.1007/978-3-319-46672-9_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46671-2

  • Online ISBN: 978-3-319-46672-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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