In-Hardware Learning of Multilayer Spiking Neural Networks on a Neuromorphic Processor

Although widely used in machine learning, backpropagation cannot directly be applied to SNN training and is not feasible on a neuromorphic processor that emulates biological neuron and synapses. This work presents a spike-based backpropagation algorithm with biological plausible local update rules a...

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Bibliographic Details

Published in:	2021 58th ACM/IEEE Design Automation Conference (DAC) pp. 367 - 372
Main Authors:	Shrestha, Amar, Fang, Haowen, Rider, Daniel Patrick, Mei, Zaidao, Qiu, Qinru
Format:	Conference Proceeding
Language:	English
Published:	IEEE 05.12.2021
Subjects:	Backpropagation algorithms Bio-Inspired Approaches Biology Hardware Neuromorphic Computing Neuromorphics Nonhomogeneous media Spiking Neural Networks Supervised learning Training
Online Access:	Get full text
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