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International Conference on Neural Information Processing

ICONIP 2018: Neural Information Processing pp 616–624Cite as

Proposal of Carrier-Wave Reservoir Computing

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11301))

Abstract

Reservoir computing is highly compatible with physical waves such as optical wave and spin wave. In such wave-realized reservoir computing, signals are not limited to the raw signals, or baseband signals, but also expressed as frequency-shifted signals having a carrier. This paper proposes such a reservoir computing architecture, namely, carrier-wave reservoir computing. We present its construction and suitable learning dynamics with which we deal with the phase information explicitly. The merits of the proposed carrier-wave reservoir computing are its frequency-dependent processing functions, frequency-domain multiplexing ability and explicit phase-information utilization. It is also useful for material evaluation from the viewpoint of computational ability in the reservoir computing.

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Author information

Authors and Affiliations

  1. The University of Tokyo, Tokyo, Japan

    Akira Hirose, Gouhei Tanaka & Ryosho Nakane

  2. IBM Research - Tokyo, Kawasaki, Japan

    Seiji Takeda, Toshiyuki Yamane, Hidetoshi Numata, Naoki Kanazawa, Jean Benoit Heroux & Daiju Nakano

Authors
  1. Akira Hirose
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  2. Gouhei Tanaka
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  3. Seiji Takeda
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  4. Toshiyuki Yamane
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  5. Hidetoshi Numata
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  6. Naoki Kanazawa
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  7. Jean Benoit Heroux
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  8. Daiju Nakano
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  9. Ryosho Nakane
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Corresponding author

Correspondence to Akira Hirose .

Editor information

Editors and Affiliations

  1. The Chinese Academy of Sciences, Beijing, China

    Long Cheng

  2. City University of Hong Kong, Kowloon, Hong Kong

    Andrew Chi Sing Leung

  3. Kobe University, Kobe, Japan

    Seiichi Ozawa

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Hirose, A. et al. (2018). Proposal of Carrier-Wave Reservoir Computing. In: Cheng, L., Leung, A., Ozawa, S. (eds) Neural Information Processing. ICONIP 2018. Lecture Notes in Computer Science(), vol 11301. Springer, Cham. https://doi.org/10.1007/978-3-030-04167-0_56

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  • DOI: https://doi.org/10.1007/978-3-030-04167-0_56

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04166-3

  • Online ISBN: 978-3-030-04167-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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