• DocumentCode
    2709050
  • Title

    Bifurcation analysis of a reconfigurable hybrid spiking neuron and its novel online learning algorithm

  • Author

    Hashimoto, Sho ; Torikai, Hiroyuki

  • Author_Institution
    Grad. Sch. of Eng. Sci., Osaka Univ., Suita, Japan
  • fYear
    2009
  • fDate
    14-19 June 2009
  • Firstpage
    1134
  • Lastpage
    1141
  • Abstract
    A hybrid spiking neuron is a wired system of shift registers and behaves like a neuron model. The neuron exhibits various bifurcation phenomena and response characteristics for a stimulation spike-train input. In this paper we formulate some typical bifurcation mechanisms and clarify these mechanisms by using discrete/continuous hybrid maps. Based on the analysis results, we can clarify mechanisms of various responses of the neuron. In addition, we propose a novel online learning algorithm of the neuron and show that the neuron can reconstruct or approximate response characteristics of another neuron with unknown parameter values.
  • Keywords
    bifurcation; learning (artificial intelligence); neural nets; shift registers; bifurcation analysis; bifurcation mechanisms; continuous hybrid maps; discrete hybrid maps; neuron model; online learning algorithm; reconfigurable hybrid spiking neuron; shift registers; stimulation spike-train input; Algorithm design and analysis; Arithmetic; Bifurcation; Current measurement; Field programmable analog arrays; Field programmable gate arrays; Neural networks; Neurons; Shift registers; Wiring;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2009. IJCNN 2009. International Joint Conference on
  • Conference_Location
    Atlanta, GA
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-3548-7
  • Electronic_ISBN
    1098-7576
  • Type

    conf

  • DOI
    10.1109/IJCNN.2009.5178757
  • Filename
    5178757