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
Link To Document