SPD-CNN: A plain CNN-based model using the symmetric positive definite matrices for cross-subject EEG classification with meta-transfer-learning

The electroencephalography (EEG) signals are easily contaminated by various artifacts and noise, which induces a domain shift in each subject and significant pattern variability among different subjects. Therefore, it hinders the improvement of EEG classification accuracy in the cross-subject learni...

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Detalles Bibliográficos
Autores principales: Chen, Lezhi, Yu, Zhuliang, Yang, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9383414/
https://www.ncbi.nlm.nih.gov/pubmed/35990886
http://dx.doi.org/10.3389/fnbot.2022.958052

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9383414/
https://www.ncbi.nlm.nih.gov/pubmed/35990886
http://dx.doi.org/10.3389/fnbot.2022.958052

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