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A P300 speller is one of applications the brain computer interface (BCI), introduced by Farwell and Donchin in 1988 N. In this paper proposed a new method for increase the accuracy of classification P300 speller. Uses a dataset for (16) healthy subjects. The new method including is feature extraction using Principle Component Analysis (PCA), and the classification using Support Vector Machine Linear (SVML). As it was calculated performance and activity of each electrode whether correlated or uncorrelated of speller task. Show that the proposed method is accurate and efficient.

A PROPOSED METHOD FOR INCREASE ACCURACY OF CLASSIFICATION P300 SPELLER