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Suppression of overlearning in independent component analysis used for removal of muscular artifacts from electroencephalographic records
This paper addresses the overlearning problem in the independent component analysis (ICA) used for the removal of muscular artifacts from electroencephalographic (EEG) records. We note that for short EEG records with high number of channels the ICA fails to separate artifact-free EEG and muscular ar...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6091961/ https://www.ncbi.nlm.nih.gov/pubmed/30106969 http://dx.doi.org/10.1371/journal.pone.0201900 |