Estimating model parameters and input current of Hodgkin-Huxley model using Kalman filter

Abstract

Hodgkin-Huxley model used for nervous models is known as a multi-variable strong non-linear model. We considered Hodgkin Huxley model as a stochastic process to estimate the state variables and the model parameters from the observed data with the noise. We discretized the model using the local linearization method and applied Kalman filter to this model. Then the trend input current and the model parameters could be estimated simultaneously utilizing the maximum likelihood method.