Multiclass EEG signal classification utilizing Rényi min-entropy-based feature selection from wavelet packet transformation

This paper proposes a novel feature selection method utilizing Rényi min-entropy-based algorithm for achieving a highly efficient brain–computer interface (BCI). Usually, wavelet packet transformation (WPT) is extensively used for feature extraction from electro-encephalogram (EEG) signals. For the...

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Detalles Bibliográficos
Autores principales: Rahman, Md. Asadur, Khanam, Farzana, Ahmad, Mohiuddin, Uddin, Mohammad Shorif
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7297893/
https://www.ncbi.nlm.nih.gov/pubmed/32548772
http://dx.doi.org/10.1186/s40708-020-00108-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7297893/
https://www.ncbi.nlm.nih.gov/pubmed/32548772
http://dx.doi.org/10.1186/s40708-020-00108-y

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