• DocumentCode
    2004604
  • Title

    Silicon neuron design based on phase reduction analysis

  • Author

    Nakada, Kaoru ; Miura, Kiyotaka ; Asai, Tetsuya

  • Author_Institution
    Adv. Electron. Res. Div., Kyushu Univ., Fukuoka, Japan
  • fYear
    2012
  • fDate
    20-24 Nov. 2012
  • Firstpage
    1059
  • Lastpage
    1062
  • 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.
  • Keywords
    learning (artificial intelligence); neural chips; synchronisation; Izhikevich type silicon neuron; PRC-based design; RFN circuit; conductance-based design; dynamical system design approach; ensemble synchronization; generalization; phase reduction analysis; phase response curve; phase response property; phenomenological design; resonate-and-fire neuron circuit; silicon neuron design;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Soft Computing and Intelligent Systems (SCIS) and 13th International Symposium on Advanced Intelligent Systems (ISIS), 2012 Joint 6th International Conference on
  • Conference_Location
    Kobe
  • Print_ISBN
    978-1-4673-2742-8
  • Type

    conf

  • DOI
    10.1109/SCIS-ISIS.2012.6505177
  • Filename
    6505177