XOR learning by spiking neural network with infrared communications

Abstract

A Spiking Neural Network (SNN), which expresses information by spike trains, has an ability to process information with low energy like a human brain. Hardware implementation of a SNN is an important research problem. If the neurons are linked by wireless communications, SNNs can obtain the spatial degree of freedom, which may extend application area dramatically. Additionally, such SNNs can process information with low energy, owing to wireless communication by the spike trains. Therefore, it is regarded as low power-consumption wireless sensor networks (WSNs) with adding the functions of SNN neurons to wireless sensor nodes. This “Wireless Neural Sensor Networks” can distribute information processing like a brain on the WSN nodes. This paper presents a SNN with infrared(IR) communications as the first step of the above concept. Neurons are implemented by field programmable gate array, which are linked by IR communications. The implemented SNN succeeded in acquiring the XOR function through reinforcement learning.