@inproceedings{1c4a518d75a94153b4b3393b8c73357f,
title = "SR-WTA: Skyrmion racing winner-takes-all module for spiking neural computing",
abstract = "Spiking neural network (SNN) has emerged as one of the popular architectures in complex pattern recognition and classification tasks. However, hardware implementation of such algorithms using conventional CMOS based neuron consume resources and power that are orders of magnitude higher than that in human brain. This can be attributed to the mismatch of the computational architecture between biological brain and the current Boolean logic computing platform. Magnetic skyrmions have been intensively studied as a prospective information carrier in neuromorphic computing hardware design. In this work, a compact time-domain skyrmion-racing winner-takes-all (SR-WTA) leaky-integrate-fire (LIF) spiking neuron network is presented for the first time. The skyrmion motion dynamics in the LIF neuron and the behaviors of the neuron network was investigated comprehensively. Both SPICE and micromagnetic simulations are performed to evaluate the functionality and performance of the proposed SR-WTA based SNN.",
keywords = "Bio-inspired, LIF neuron, SR-WTA, Skyrmion, Spiking Neural Network",
author = "Biao Pan and Kang Wang and Xing Chen and Jinyu Bai and Jianlei Yang and Youguang Zhang and Weisheng Zhao",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE; 2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 ; Conference date: 26-05-2019 Through 29-05-2019",
year = "2019",
doi = "10.1109/ISCAS.2019.8702783",
language = "英语",
series = "Proceedings - IEEE International Symposium on Circuits and Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 - Proceedings",
address = "美国",
}