@article{article_265327, title={Observer Design for the Hodgkin-Huxley Neuronal Model}, journal={International Journal of Applied Mathematics Electronics and Computers}, pages={66–71}, year={2016}, DOI={10.18100/ijamec.265327}, url={https://izlik.org/JA44EY27YF}, author={Cetin, Meric and Beyhan, Selami}, keywords={Nonlinear observer,state estimation,Hodgkin-Huxley neuronal model,discretization based gradient observer,sliding-mode observer,extended Kalman filter}, abstract={<span lang="en-us" style="font-size:12pt;font-family:’Times New Roman’, serif;" xml:lang="en-us">Hodgkin-Huxley (HH) neuronal model has been widely accepted neuronal
model in neuroscience. The variation of the ionic currents in neuron cell
causes the variations in the membrane potential. The level of membrane
potential indicates the activation and inactivation dynamics. In this paper, in
order to observe the unmeasurable states and parameters of HH neuron
accurately, Runge-Kutta discretization based nonlinear observer is designed. In
numerical simulations, the membrane potential is measured and the ionic
currents are estimated. The numerical results provide accurate estimation
results that can be used both in monitoring and control of neuron dynamics. </span>}, number={Special Issue-1}