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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Veröffentlicht in:	2021 58th ACM/IEEE Design Automation Conference (DAC) S. 367 - 372
Hauptverfasser:	Shrestha, Amar, Fang, Haowen, Rider, Daniel Patrick, Mei, Zaidao, Qiu, Qinru
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 05.12.2021
Schlagworte:	Backpropagation algorithms Bio-Inspired Approaches Biology Hardware Neuromorphic Computing Neuromorphics Nonhomogeneous media Spiking Neural Networks Supervised learning Training
Online-Zugang:	Volltext
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