Adaptive deep feature representation learning for cross-subject EEG decoding

Adaptive deep feature representation learning for cross-subject EEG decoding

Abstract Background: The collection of substantial amounts of electroencephalogram (EEG) data is typically time-consuming and labor-intensive, which adversely impacts the development of decoding models with strong generalizability, particularly when the available data is limited. Utilizing sufficien...

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Bibliographic Details
Main Authors: Shuang Liang, Linzhe Li, Wei Zu, Wei Feng, Wenlong Hang
Format: Article
Language:English
Published: BMC 2024-12-01
Series:BMC Bioinformatics
Subjects:
Electroencephalogram
Domain adaptation
Discriminative feature learning
Entropy minimization
Motor imagery
Online Access:https://doi.org/10.1186/s12859-024-06024-w
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https://doi.org/10.1186/s12859-024-06024-w

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