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Non-Negative Matrix Factorizations of Spontaneous Electroencephalographic Signals for Classification

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3 Author(s)
Liu Mingyu ; Key Lab. of Biomed. Inf. Eng. of Minist. of Educ., Xi''an Jiaotong Univ. ; Wang Jue ; Zheng Chongxun

Non-negative matrix factorization (NMF) is an algorithm that is able to learn a parts-based representation. The paper proposes a new spontaneous EEG classification method for attention-related tasks. NMF was employed as feature extraction tool, which leads to more localized and sparse features than other two reference methods: power spectrum method and principal component analysis. With conventional back propagation neural network classifier, several experiments were carried out. It was showed that the NMF-ANN structure preserved the spatio-temporal characteristics of EEG signals

Published in:

Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the

Date of Conference:

17-18 Jan. 2006