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• W2611660429 abstract "Independent Component Analysis (ICA) is often used in EEG signal processing but only when the matrix of channels is big enough. If the matrix is small, the artifacts usually cannot be extracted as single components and the decision which components should be removed from the components’ set is impeded. Therefore, in our opinion, in order to apply ICA successfully for a low-dimensional EEG, the strategy for dealing with the components’ set should be reversed." @default.
• W2611660429 created "2017-05-12" @default.
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• W2611660429 creator A5062839503 @default.
• W2611660429 date "2017-05-07" @default.
• W2611660429 modified "2023-09-27" @default.
• W2611660429 title "EEG Classification for MI-BCI with Independent Component Analysis" @default.
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• W2611660429 doi "https://doi.org/10.1007/978-3-319-59162-9_41" @default.
• W2611660429 hasPublicationYear "2017" @default.
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