Gradient method of learning for stochastic kinetic model of neuron

Abstract

In this paper we are focusing on the kinetic extension [4] of classic model of Hodgkin and Huxley [2]. We are showing the descent gradient method used in the learning process of neuron, which is described with stochastic kinetic model. In comparison with [1] we use only 3 weights instead of 9: gNa; gK and gL: We show that this model behaves equally accurate as the model of Hodgkin and Huxley with slighter system description.

Description

Subject(s)

stochastický kinetický model neuronu, gradientní metoda učení, Hodgin-Huxleyho model

Citation

ISTET 2013: International Symposiumon Theoretical Electrical Engineering: 24th – 26th June 2013, Pilsen, Czech Republic, p. III-17-III-18.
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