Basis Selection for Increased Interclass Separability of EEG Signals
Résumé
We present an adaptive feature selection method for the classification of EEG signals. The algorithm determines the most discriminative channels and regions of the time-frequency plane. Promising results are obtained when classifying signals associated with real and imaginary hand motion of a healthy subject.
Origine | Fichiers produits par l'(les) auteur(s) |
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