Cargando…
Hybrid Genetic Algorithm for Clustering IC Topographies of EEGs
Clustering of independent component (IC) topographies of Electroencephalograms (EEG) is an effective way to find brain-generated IC processes associated with a population of interest, particularly for those cases where event-related potential features are not available. This paper proposes a novel a...
Autores principales: | Munilla, Jorge, Al-Safi, Haedar E. S., Ortiz, Andrés, Luque, Juan L. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10164025/ https://www.ncbi.nlm.nih.gov/pubmed/36881274 http://dx.doi.org/10.1007/s10548-023-00947-y |
Ejemplares similares
-
Patient privacy in smart cities by blockchain technology and feature selection with Harris Hawks Optimization (HHO) algorithm and machine learning
por: Al-Safi, Haedar, et al.
Publicado: (2022) -
An Approach for Cardiac Coronary Detection of Heart Signal Based on Harris Hawks Optimization and Multichannel Deep Convolutional Learning
por: Alsafi, Haedar, et al.
Publicado: (2022) -
Development of grouped icEEG for the study of cognitive processing
por: Kadipasaoglu, Cihan M., et al.
Publicado: (2015) -
The ICLabel dataset of electroencephalographic (EEG) independent component (IC) features
por: Pion-Tonachini, Luca, et al.
Publicado: (2019) -
Dysconnection Topography in Schizophrenia Revealed with State-Space Analysis of EEG
por: Jalili, Mahdi, et al.
Publicado: (2007)