Feature Selection for Motor Imagery EEG Classification Based on Firefly Algorithm and Learning Automata

Motor Imagery (MI) electroencephalography (EEG) is widely studied for its non-invasiveness, easy availability, portability, and high temporal resolution. As for MI EEG signal processing, the high dimensions of features represent a research challenge. It is necessary to eliminate redundant features,...

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Detalles Bibliográficos
Autores principales: Liu, Aiming, Chen, Kun, Liu, Quan, Ai, Qingsong, Xie, Yi, Chen, Anqi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5713053/
https://www.ncbi.nlm.nih.gov/pubmed/29117100
http://dx.doi.org/10.3390/s17112576

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5713053/
https://www.ncbi.nlm.nih.gov/pubmed/29117100
http://dx.doi.org/10.3390/s17112576

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