Bi-Smoothed Functional Independent Component Analysis for EEG Artifact Removal

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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Bibliographic Details
Main Authors: Marc Vidal, Mattia Rosso, Ana M. Aguilera 
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Mathematics
Subjects:
functional data
functional kurtosis
penalized splines
smoothed principal components
auditory–motor coupling task
EEG
Online Access:https://www.mdpi.com/2227-7390/9/11/1243

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https://www.mdpi.com/2227-7390/9/11/1243

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