Neural networks : the official journal of the International Neural Network Society
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Noise in electroencephalography data (EEG) is an ubiquitous problem that limits the performance of brain computer interfaces (BCI). While typical EEG artifacts are usually removed by trial rejection or by filtering, noise induced in the data by the subject's failure to produce the required mental state is very harmful. ⋯ In this manner, our method effectively "cleans" the training data and thus allows better BCI classification. Preliminary results conducted on a data set of 43 naive subjects show a significant improvement for 74% of the subjects.