Parameter Estimation in Hodgkin-Huxley Model with Adaptive Method
Neuron models are highly nonlinear and involve many electrophysiological variables and parameters, only some of the variables are easily measured experimentally, while other parameters are difficult to experimentally determine. However, successful estimation of the unknown parameters often cannot be guaranteed. In this paper, we proposed a model reference adaptive method to estimate different parameters of a neuron model (the H-H model as an example) simultaneously. Simulation result of two parameters is accurate as the values we set in the HH model. However, overshoot occurs when we estimate three parameters with different orders of magnitude. By adjusting the coefficients to control the learning rates of different parameters, a good simulation result has been acquired efficiently. This method can also be applied to estimate parameters in other nonlinear systems.
H-H model parameter estimation model reference adaptive metod overshoot solution
Jianbing Sun Bin Deng Xile Wei Chenhui Jia Jiang Wang Jia Zhao
School of Electrical Engineering and Automation Tianjin University Tianjin, China
国际会议
上海
英文
1865-1869
2011-10-15（万方平台首次上网日期，不代表论文的发表时间）