An Image Recognizing method Based on Precise Moment of Spikes

Abstract

Inspired by neural computing science, Spiking Neural Networks(SNNs), as the third generation of Artificial Neural Networks(ANNs), with its high biological interpretability, powerful time-space information processing ability and diverse spike coding method, has shown a great potential in pattern recognition, object detecting and data predicting. It has received extensive attention in the field of brain-inspired computing and machine learning. Utilizing spike trains as communication signals within the network is one of the advantages of spiking neural networks, which is the main way of information transmission between neurons in the brain. How to encode input information into spike signals for transmission in the network determines the working efficiency. In this paper, a spiking neural network based on the spike firing rate and temporal coding is proposed in the training and testing process respectively, and applied to the recognition of MNIST handwritten digital dataset, with an accuracy of 78.74%.