USING NON-NEGTIVE MATRIX FACTORAZATION TO EXTRACT ATTENTION-RELATED EEG FEATURES
应用非负矩阵分解方法提取注意力相关脑电特征

The fundamental of non-negative matrix factorization algorithm was introduced. It is used to extract EEG power spectrum feature. Artificial neural network is employed as classifier. Three level attention mental tasks are designed to test the method. Ten subjects attended the experiment. The classification accuracies indicate that the NMF technique is a powerful feature extractor in high-dimensional feature space. The average classification accuracy of ten subjects achieves 88%, it is higher obviously than that of principal component analysis and direct method.