A novel criterion of wavelet packet best basis selection for signal classification with application to brain-computer interfaces.

Abstract

This study proposes a method to select a wavelet basis for classification. It uses a strategy defined by Wickerhauser and Coifman and proposes a new additive criterion describing the contrast between classes. Its performance is compared with other approaches on simulated signals and on experimental EEG signals for brain-computer interface applications.