Silicon neuron design based on phase reduction analysis

Kazuki Nakada, Keiji Miura, Tetsuya Asai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper, we propose a dynamical system design approach for silicon neurons (SiNs) based on the phase reduction theory. The design approaches for SiNs can be classified as three: the phenomenological design, the conductance-based design, and the dynamical systems design. As a part of the third approach, we propose the phase response curve (PRC)-based design for SiNs to enhance synchronization in an ensembles of SiNs. We consider the key criteria to optimize SiN design in terms of phase response properties by analyzing various circuit models of previous SiNs. Furthermore, as a case study, we demonstrate how to tune circuit parameters to obtain a desirable PRC of a resonate-and-fire neuron (RFN) circuit. Finally, we discuss the possibility of extending our approach to design a class of the generalized integrate-and-fire neuron (GIFN) circuits including the Izhikevich type SiNs.

Original languageEnglish
Title of host publication6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012
Pages1059-1062
Number of pages4
DOIs
Publication statusPublished - 2012 Dec 1
Event2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012 - Kobe, Japan
Duration: 2012 Nov 202012 Nov 24

Publication series

Name6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012

Other

Other2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012
Country/TerritoryJapan
CityKobe
Period12/11/2012/11/24

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

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