A new recursive least squares-based learning algorithm for spiking neurons

Spiking neural networks (SNNs) are regarded as effective models for processing spatio-temporal information. However, their inherent complexity of temporal coding makes it an arduous task to put forward an effective supervised learning algorithm, which still puzzles researchers in this area. In this...

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Bibliographic Details

Published in:	Neural networks Vol. 138; pp. 110 - 125
Main Authors:	Zhang, Yun, Qu, Hong, Luo, Xiaoling, Chen, Yi, Wang, Yuchen, Zhang, Malu, Li, Zefang
Format:	Journal Article
Language:	English
Published:	United States Elsevier Ltd 01.06.2021
Subjects:	Recursive least squares Spiking neural networks Spiking neurons Supervised learning Spiking neurons Supervised learning Recursive least squares Spiking neural networks
ISSN:	0893-6080, 1879-2782, 1879-2782
Online Access:	Get full text
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