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
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;
Conference_Titel :
ICCAS-SICE, 2009
Conference_Location :
Fukuoka
Print_ISBN :
978-4-907764-34-0
Electronic_ISBN :
978-4-907764-33-3