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PWC-ICA: A Method for Stationary Ordered Blind Source Separation with Application to EEG

Independent component analysis (ICA) is a class of algorithms widely applied to separate sources in EEG data. Most ICA approaches use optimization criteria derived from temporal statistical independence and are invariant with respect to the actual ordering of individual observations. We propose a me...

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Библиографические подробности
Опубликовано в: :Comput Intell Neurosci
Главные авторы: Ball, Kenneth, Bigdely-Shamlo, Nima, Mullen, Tim, Robbins, Kay
Формат: Artigo
Язык:Inglês
Опубликовано: Hindawi Publishing Corporation 2016
Предметы:
Online-ссылка:https://ncbi.nlm.nih.gov/pmc/articles/PMC4909972/
https://ncbi.nlm.nih.gov/pubmed/27340397
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2016/9754813
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