Dynamical systems design of silicon neurons using phase reduction method
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- Nakada Kazuki
- Graduate School of Information Sciences, Hiroshima City University
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- Miura Keiji
- Graduate School of Science and Technology, Kwansei Gakuin University
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- Asai Tetsuya
- Graduate School of Information Science and Technology, Hokkaido University
説明
In biologically-inspired, neuromorphic engineering, it is important to design silicon neurons (SiNs) with desirable functions in a systematic way. However, the conventional design methods such as phenomenological design and the conductance-based design relied on the hand-tuned parameters. Thus a more systematic design principle, that considers mathematical structures in the dynamical systems, is needed for efficiency and robustness. In this work, we present the phase response curve (PRC)-based design for SiNs as a dynamical systems design for SiNs to enhance synchronization in an ensemble of SiNs on the basis of the phase reduction theory. By analyzing various circuit models of the previous SiNs, we explore key criteria to realize transitions between two typical PRCs, Type I and Type II. As a case study, we focus on the hybrid type SiNs for tractability and demonstrate how to tune circuit parameters of a resonate-and-fire neuron (RFN) circuit to control the peak location of phase coupling functions resulting from PRCs, which matters for phase locking.
収録刊行物
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- Nonlinear Theory and Its Applications, IEICE
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Nonlinear Theory and Its Applications, IEICE 7 (2), 95-109, 2016
一般社団法人 電子情報通信学会
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詳細情報 詳細情報について
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- CRID
- 1390001205344364288
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- NII論文ID
- 130005142595
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- ISSN
- 21854106
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- Crossref
- CiNii Articles
- KAKEN
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- 抄録ライセンスフラグ
- 使用不可
