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The classification of mental tasks is one of key issues of EEG-based brain computer interface (BCI). Differentiating classes of mental tasks from EEG signals is challenging because EEG signals are nonstationary and nonlinear. Owing to its powerful capacity in solving nonlinearity problems, support vector machine (SVM) method has been widely used as a classification tool. Traditional SVMs, however,...
The classification of mental tasks is one of the key issues of Brain Computer Interface (BCI). Owing to its powerful capacity in solving non-linearity problems, Support Vector Machine (SVM) has been widely used in classification. Traditional SVM, however, assumes that each feature of a sample contributes equally to classification accuracy, which is not necessarily true in real world applications....
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