TY - GEN
T1 - Interchangeable Hebbian and Anti-Hebbian STDP Applied to Supervised Learning in Spiking Neural Network
AU - Chang, Che Chia
AU - Chen, Pin Chun
AU - Hudec, Boris
AU - Liu, Po-Tsun
AU - Hou, Tuo-Hung
PY - 2019/1/16
Y1 - 2019/1/16
N2 - This work provides a complete framework, including device, architecture, and algorithm, for implementing bio-inspired supervised spiking neural networks (SNNs) on hardware. An analog synapse with atypical dual bipolar resistive-switching (D-BRS) modes demonstrates interchangeable Hebbian spiking-timing-dependent plasticity (STDP) and anti-Hebbian STDP, and it is capable of implementing supervised ReSuMe SNNs in crossbar arrays. By using an 'exchange' update scheme, accurate supervised learning (∼96% for MNIST) is achieved in a compact network.
AB - This work provides a complete framework, including device, architecture, and algorithm, for implementing bio-inspired supervised spiking neural networks (SNNs) on hardware. An analog synapse with atypical dual bipolar resistive-switching (D-BRS) modes demonstrates interchangeable Hebbian spiking-timing-dependent plasticity (STDP) and anti-Hebbian STDP, and it is capable of implementing supervised ReSuMe SNNs in crossbar arrays. By using an 'exchange' update scheme, accurate supervised learning (∼96% for MNIST) is achieved in a compact network.
UR - http://www.scopus.com/inward/record.url?scp=85061785057&partnerID=8YFLogxK
U2 - 10.1109/IEDM.2018.8614648
DO - 10.1109/IEDM.2018.8614648
M3 - Conference contribution
AN - SCOPUS:85061785057
T3 - Technical Digest - International Electron Devices Meeting, IEDM
SP - 15.5.1-15.5.4
BT - 2018 IEEE International Electron Devices Meeting, IEDM 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 64th Annual IEEE International Electron Devices Meeting, IEDM 2018
Y2 - 1 December 2018 through 5 December 2018
ER -