Potential Application of Neuron with Multi Dendrites in Medicines

Abstract

A neural networks based on neurons with multi dendrites employing activation function with variable structure is introduced. No prior work, however, has discovered the impact of dendrites position on heavies’ information to propagate. Given the frequent observations of correlations in the dendrites structure, and the importance of the spike propagation and burst problems, this is a significant gap in our knowledge. To fill that gap, we consider a model neuron with multi dendrites. In this paper, we discover that Hopfield’s type of neural network can generate multi dynamic behaviors. Our contribution in this paper is to modify Hopfield’s neural network in paper [5] by changing position sign of differential system equation in line two and we add a parameter of P, which has an interesting effect on the output response, we obtain four-differential system equation, which means obtaining four models of neurons. Maybe, the results reached in this work shed some light on Henry Poincare’s conjuncture. Each neuron has its dynamic behavior which has never been reported before; one of them has a great similarity with real biological neuron signal. Then we notice that the dynamic behavioral response contains impact of neuron such as, signals of neurons with different directions, bounded regions with different segments and separation regions. Finally, the numerical examples will illustrate the effectiveness of this work.