• DocumentCode
    504481
  • Title

    Adaptive input estimation of a Hodgkin-Huxley neuron

  • Author

    Ito, Ryuta ; Totoki, Yusuke ; Suemitsu, Haruo ; Matsuo, Takami

  • Author_Institution
    Dept. of Archit. & Mechatron., Oita Univ., Oita, Japan
  • fYear
    2009
  • fDate
    18-21 Aug. 2009
  • Firstpage
    5230
  • Lastpage
    5235
  • Abstract
    In this paper, we propose an adaptive observer based on the HH model equations without any linearization method. The nonlinear adaptive observer based on the HH dynamic structure is proposed to estimate the internal states and the input current of a HH neuron. The input current is estimated as a slow-varying parameter using the adaptive parameter update law with a signum function. The MATLAB simulations demonstrate the estimation performance of the proposed adaptive observers.
  • Keywords
    adaptive control; neurocontrollers; nonlinear control systems; observers; HH model equation; Hodgkin-Huxley neuron; MATLAB simulation; adaptive input estimation; nonlinear adaptive observer; signum function; slow-varying parameter; Biological system modeling; Computational modeling; Electric variables measurement; Equations; Frequency synchronization; Mathematical model; Neurons; Observers; Parameter estimation; State estimation; Bursting; Lyapunov exponent; adaptive observer; spiking; synchronization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    ICCAS-SICE, 2009
  • Conference_Location
    Fukuoka
  • Print_ISBN
    978-4-907764-34-0
  • Electronic_ISBN
    978-4-907764-33-3
  • Type

    conf

  • Filename
    5333414