Sparse measures with swarm-based pliable hidden Markov model and deep learning for EEG classification

In comparison to other biomedical signals, electroencephalography (EEG) signals are quite complex in nature, so it requires a versatile model for feature extraction and classification. The structural information that prevails in the originally featured matrix is usually lost when dealing with standa...

Descripción completa

Detalles Bibliográficos
Autores principales: Prabhakar, Sunil Kumar, Ju, Young-Gi, Rajaguru, Harikumar, Won, Dong-Ok
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/PMC9709410/
https://www.ncbi.nlm.nih.gov/pubmed/36465961
http://dx.doi.org/10.3389/fncom.2022.1016516

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9709410/
https://www.ncbi.nlm.nih.gov/pubmed/36465961
http://dx.doi.org/10.3389/fncom.2022.1016516

Ejemplares similares