• DocumentCode
    2308605
  • Title

    Simple noise reduction in the adaptive synchronization of coupled neurons by Robust Fixed Point Transformation

  • Author

    Várkonyi, Teréz A. ; Tar, József K. ; Bitó, János F. ; Rudas, Imre J.

  • Author_Institution
    John von Neumann Fac. of Inf., Obuda Univ., Budapest, Hungary
  • fYear
    2011
  • fDate
    23-25 June 2011
  • Firstpage
    297
  • Lastpage
    302
  • Abstract
    To avoid the general mathematical difficulties of the application of Lyapunov´s “direct” method in adaptive control in the present paper an alternative approach, the use of “Robust Fixed Point Transformation (RFPT)” is applied for the adaptive synchronization of two coupled, asymmetric, chaotically behaving, approximately known Fitz - Hugh - Nagumo (FHN) neurons. Since the RFPT scheme is based on the use of the “Expected - Realized Response Scheme” the noise in the observed quantities may influence the efficiency of the controller. For this purpose the use of a very simple, easily realizable technique is proposed that applies polynomial filtering coefficients in the time domain. Its efficiency is investigated and substantiated via extended simulation investigations.
  • Keywords
    adaptive control; chaos; filtering theory; neurocontrollers; nonlinear control systems; synchronisation; Fitz-Hugh-Nagumo neuron; adaptive controller; chaotic motion; expected-realized response scheme; neuron adaptive synchronization; noise reduction; polynomial filtering coefficient; robust fixed point transformation; Adaptation models; Adaptive systems; Chaos; Neurons; Noise; PD control; Synchronization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Engineering Systems (INES), 2011 15th IEEE International Conference on
  • Conference_Location
    Poprad
  • Print_ISBN
    978-1-4244-8954-1
  • Type

    conf

  • DOI
    10.1109/INES.2011.5954762
  • Filename
    5954762