• DocumentCode
    3231144
  • Title

    Synthesis of frequency generator via spiking neurons network: A genetic algorithm approach

  • Author

    Soares, Gabriela E. ; Borges, Henrique E. ; Gomes, Rogério M. ; Oliveira, Geraldo M C

  • Author_Institution
    Intell. Syst. Lab., Fed. Centre of Technol. Educ. of Minas Gerais, Belo Horizonte, Brazil
  • fYear
    2010
  • fDate
    23-26 Sept. 2010
  • Firstpage
    1613
  • Lastpage
    1620
  • Abstract
    Inspired by the Theory of Neuronal Group Selection (TNGS), we have carried out synthesis of frequency generator via spiking neurons network through genetic algorithm. The TNGS sets that a neuronal group is the most basic unit in the cortical area and are generated by synapses of localized neural cells in the cortical area of the brain firing and oscillating in synchrony at a predefined frequency. Each one of these clusters (Neuronal Groups) is a set of localized, tightly coupled neurons developed in the embryo. According to this proposal, this paper describes a method of tuning the parameters of the Izhikevich spiking neuron model. Computational experiments consisting of a network with all neurons of the same type and a network with different neurons were conducted. A genetic algorithm was used to tune the parameters in these two different cases. The results were compared in order to find the best way to create a frequency generator of spiking neurons network.
  • Keywords
    genetic algorithms; neural nets; tuning; Izhikevich spiking neuron model; brain cortical area; frequency generator synthesis; genetic algorithm; localized neural cell synapse; neuronal group selection theory; parameter tuning; spiking neuron network; tightly coupled neurons; Embryo; Neurons; genetic algorithm; neural networks; neuronal groups; spiking neuron;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4244-6437-1
  • Type

    conf

  • DOI
    10.1109/BICTA.2010.5645261
  • Filename
    5645261