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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....
In head MRI image sequences, the boundary of each encephalic tissue is highly complicated and irregular. It is a real challenge to traditional 3D modeling algorithms. Support vector machine (SVM) based on statistical learning theory has solid theoretical foundation. sphere-shaped SVM (SSSVM) was originally developed for solving some special classification problems. In this paper, it is extended to...
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