Transferred Subspace Learning Based on Non-negative Matrix Factorization for EEG Signal Classification

Transferred Subspace Learning Based on Non-negative Matrix Factorization for EEG Signal Classification

EEG signal classification has been a research hotspot recently. The combination of EEG signal classification with machine learning technology is very popular. Traditional machine leaning methods for EEG signal classification assume that the EEG signals are drawn from the same distribution. However,...

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Bibliographic Details
Main Authors: Aimei Dong, Zhigang Li, Qiuyu Zheng
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-03-01
Series:Frontiers in Neuroscience
Subjects:
non-negative factorization
transfer learning
shared hidden subspace
EEG signal
classification
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2021.647393/full

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https://www.frontiersin.org/articles/10.3389/fnins.2021.647393/full

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