Multi-layer perceptron with pulse glial chain having oscillatory excitation threshold

A brain has neuron and glial cells. In the brain, these cells correlate each other and make a higher brain function. In this study, we propose a Multi-Layer Perceptron (MLP) with pulse glial chain having oscillatory excitation threshold. We connect artificial glia units with the neurons in a hidden-layer. When the connecting neuron output is larger than an excitation threshold of the connected glia, the glia excites and generates the pulse. This pulse transmits to the neighboring glias and the connecting neuron. The pulse increases a threshold of the connecting neuron, thus the glia gives energy for solving tasks. In this model, the excitation threshold is oscillating within a defined value. Even if the connecting neuron output does not change, the pulse generation occurs by the oscillation of the excitation threshold. The oscillation of the excitation threshold gives more energy to the network and improves a learning performance of the MLP. By computer simulation, we confirm that the oscillation of the excitation threshold improves a learning performance.