An Intelligent EEG Classification Methodology Based on Sparse Representation Enhanced Deep Learning Networks

The classification of electroencephalogram (EEG) signals is of significant importance in brain–computer interface (BCI) systems. Aiming to achieve intelligent classification of EEG types with high accuracy, a classification methodology using sparse representation (SR) and fast compression residual c...

Descripción completa

Detalles Bibliográficos
Autores principales: Huang, Jing-Shan, Li, Yang, Chen, Bin-Qiang, Lin, Chuang, Yao, Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7596898/
https://www.ncbi.nlm.nih.gov/pubmed/33177970
http://dx.doi.org/10.3389/fnins.2020.00808

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7596898/
https://www.ncbi.nlm.nih.gov/pubmed/33177970
http://dx.doi.org/10.3389/fnins.2020.00808

Ejemplares similares