Trained stochastic model of biological neural network used in image processing task

In this paper we are presenting some new approaches to the biological model of neural network, which is strictly based on Hodgkin-Huxley types of models. The first aspect was to introduce stochasticity into a model of dendritic structure of neuron already proposed in Hodgkin and Huxley (1952) by using Markov kinetic schemes (Destexhe et al., 1994). Second thing was to bring into this model a training algorithm which is based on the descent gradient method. Subsequently the trained neural network is supposed to solve a problem of noise removal from a given image.This study is supposed to underline potential of biologically realistic models of neural network, which - with a bit of invention - can be used like conventional artificial neural networks.