Implementation of Delay-Enabled Axons for Lightweight Neural Networks with Improving Accuracy in Edge Computing

In this work, we constructed a novel axon with adjustable delay characteristics, which accurately emulates the delay property of biological axons. Based on this axon, we built a Liquid State Machine (LSM) network, which achieved a 5% increase in accuracy while reducing the number of parameters by a factor of 31.