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Bi-Smoothed Functional Independent Component Analysis for EEG Artifact Removal

Motivated by mapping adverse artifactual events caused by body movements in electroencephalographic (EEG) signals, we present a functional independent component analysis based on the spectral decomposition of the kurtosis operator of a smoothed principal component expansion. A discrete roughness pen...

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Principais autores: Marc Vidal, Mattia Rosso, Ana M. Aguilera 
פורמט: Artigo
שפה:Inglês
יצא לאור: MDPI AG 2021-05-01
סדרה:Mathematics
נושאים:
functional data
functional kurtosis
penalized splines
smoothed principal components
auditory–motor coupling task
EEG
גישה מקוונת:https://www.mdpi.com/2227-7390/9/11/1243
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