Stockwell transform and semi-supervised feature selection from deep features for classification of BCI signals

Over the past few years, the processing of motor imagery (MI) electroencephalography (EEG) signals has been attracted for developing brain-computer interface (BCI) applications, since feature extraction and classification of these signals are extremely difficult due to the inherent complexity and te...

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Detalles Bibliográficos
Autores principales: Salimpour, Sahar, Kalbkhani, Hashem, Seyyedi, Saeed, Solouk, Vahid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9273790/
https://www.ncbi.nlm.nih.gov/pubmed/35817814
http://dx.doi.org/10.1038/s41598-022-15813-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9273790/
https://www.ncbi.nlm.nih.gov/pubmed/35817814
http://dx.doi.org/10.1038/s41598-022-15813-3

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