A novel neural network inspired from Neuroendocrine-Immune System

Abstract

Inspired by the modulation mechanism of Neuroendocrine-Immune System (NEIs), this paper presents a novel structure of artificial neural network named NEI-NN as well as its evolutionary method. The NEI-NN includes two parts, i.e. positive sub-network (PSN) and negative sub-network (NSN). The increased and decreased secretion functions of hormone are designed as the neuron functions of PSN and NSN, respectively. In order to make the novel neural network learn quickly, we redesign the novel neuron, which is different from those of conventional neural networks. Besides the normal input signals, two control signals are also considered in the proposed solution. One control signal is the enable/disable signal, and the other one is the slope control signal. The former can modify the structure of NEI-NN, and the later can regulate the evolutionary speed of NEI-NN. The NEI-NN can obtain the optimized network structure during the evolutionary process of weights. We chooses a second order with delay model to examine the performance of novel neural network. The experiment results show that the optimized structure and learning speed of NEI-NN are better than the conventional neural network.