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- W2150764079 abstract "This paper presents an algorithm for classifying single-trial electroencephalogram (EEG) during the preparation of self-paced tapping. It combines common spatial subspace decomposition with Fisher discriminant analysis to extract features from multichannel EEG. Three features are obtained based on Bereitschaftspotential and event-related desynchronization. Finally, a perceptron neural network is trained as the classifier. This algorithm was applied to the data set <self-paced 1s> of BCI Competition 2003 with a classification accuracy of 84% on the test set." @default.
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- W2150764079 date "2004-06-01" @default.
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- W2150764079 title "BCI Competition 2003—Data Set IV: An Algorithm Based on CSSD and FDA for Classifying Single-Trial EEG" @default.
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- W2150764079 doi "https://doi.org/10.1109/tbme.2004.826697" @default.
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