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Applying dimension reduction to EEG data by Principal Component Analysis reduces the quality of its subsequent Independent Component decomposition

Independent Component Analysis (ICA) has proven to be an effective data driven method for analyzing EEG data, separating signals from temporally and functionally independent brain and non-brain source processes and thereby increasing their definition. Dimension reduction by Principal Component Analy...

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Detalhes bibliográficos
Publicado no:Neuroimage
Main Authors: Artoni, Fiorenzo, Delorme, Arnaud, Makeig, Scott
Formato: Artigo
Idioma:Inglês
Publicado em: 2018
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC6650744/
https://ncbi.nlm.nih.gov/pubmed/29526744
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neuroimage.2018.03.016
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