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Implementation of cooperative communications using ultrasonic wireless terminals Ses-üstü telsi̇z termi̇naller kullanilarak i̇şbi̇rli̇kli̇ i̇leti̇şi̇mi̇n gerçekleşti̇ri̇lmesi̇

2011-07-21
Özdemir, Özgür
Yılmaz, Ali Özgür
Herdem, Saadetdin
In this paper, a feature filtering algorithm for brain-computer interface which includes classification of EEG data is proposed. By this method, the features are evaluated according to a criterion based on the Mahalanobis distance between the classes. For some EEG data classification problems, the problem may be determining the features to be extracted, however for the problem of distinguishing between right, left and forward movement imagination, the features that most benefits in classification cannot be determined beforehand. Therefore, features are selected method from a set of all possible features by the proposed filtering to increase the performance and speed of the classifier