TY - JOUR
T1 - Magnetic skyrmion-based artificial neuron device
AU - Li, Sai
AU - Kang, Wang
AU - Huang, Yangqi
AU - Zhang, Xichao
AU - Zhou, Yan
AU - Zhao, Weisheng
N1 - Publisher Copyright:
© 2017 IOP Publishing Ltd.
PY - 2017/7/14
Y1 - 2017/7/14
N2 - Neuromorphic computing, inspired by the biological nervous system, has attracted considerable attention. Intensive research has been conducted in this field for developing artificial synapses and neurons, attempting to mimic the behaviors of biological synapses and neurons, which are two basic elements of a human brain. Recently, magnetic skyrmions have been investigated as promising candidates in neuromorphic computing design owing to their topologically protected particle-like behaviors, nanoscale size and low driving current density. In one of our previous studies, a skyrmion-based artificial synapse was proposed, with which both short-term plasticity and long-term potentiation functions have been demonstrated. In this work, we further report on a skyrmion-based artificial neuron by exploiting the tunable current-driven skyrmion motion dynamics, mimicking the leaky-integrate-fire function of a biological neuron. With a simple single-device implementation, this proposed artificial neuron may enable us to build a dense and energy-efficient spiking neuromorphic computing system.
AB - Neuromorphic computing, inspired by the biological nervous system, has attracted considerable attention. Intensive research has been conducted in this field for developing artificial synapses and neurons, attempting to mimic the behaviors of biological synapses and neurons, which are two basic elements of a human brain. Recently, magnetic skyrmions have been investigated as promising candidates in neuromorphic computing design owing to their topologically protected particle-like behaviors, nanoscale size and low driving current density. In one of our previous studies, a skyrmion-based artificial synapse was proposed, with which both short-term plasticity and long-term potentiation functions have been demonstrated. In this work, we further report on a skyrmion-based artificial neuron by exploiting the tunable current-driven skyrmion motion dynamics, mimicking the leaky-integrate-fire function of a biological neuron. With a simple single-device implementation, this proposed artificial neuron may enable us to build a dense and energy-efficient spiking neuromorphic computing system.
KW - artificial neuron
KW - leaky-integrate-fire
KW - magnetic skyrmion
KW - neuromorphic computing
UR - https://www.scopus.com/pages/publications/85025441948
U2 - 10.1088/1361-6528/aa7af5
DO - 10.1088/1361-6528/aa7af5
M3 - 文章
C2 - 28639562
AN - SCOPUS:85025441948
SN - 0957-4484
VL - 28
JO - Nanotechnology
JF - Nanotechnology
IS - 31
M1 - 31LT01
ER -