Implementation of Spiking Neural Network with Wireless Communications
Ryuya Hiraoka, Kazuki Matsumoto, Kien Nguyen, Hiroyuki Torikai, Hiroo Sekiya
26th International COnference on Neuron Information Processing of the Asia-Pacific Neural Network Society (ICONIP2019), pp.619-626, Dec. 2019. [pdf document]

<Abstract>

This paper proposes and implements the Spiking Neural Network (SNN) with radio-frequency wireless communications. The implemented network could obtain the XOR function through reinforcement learning. By applying the wireless communication for Internet of Things to the SNN, the SNN works with sufficient communication distance and low power consumptions for not only the line of sight environment but also the non -line of sight one. Additionally, it is unnecessary to consider communication directivity and obstacles for constructing the networks. The experimental results showed the extensibility and the scalability of the implemented system in this paper.

 

Copyright (C) 2001- S-Lab., Dept. of Information and Image Sciences, Faculty of Engineering, Chiba Univ. All Rights Reserved.