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Incremental Non-Gaussian Analysis on Multivariate EEG Signal Data
Kam Swee NG Hyung-Jeong YANG Soo-Hyung KIM Sun-Hee KIM
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2012/12/01
Online ISSN: 1745-1361
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Artificial Intelligence, Data Mining
EEG, independent component analysis, principle component analysis, incremental model,
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In this paper, we propose a novel incremental method for discovering latent variables from multivariate data with high efficiency. It integrates non-Gaussianity and an adaptive incremental model in an unsupervised way to extract informative features. Our proposed method discovers a small number of compact features from a very large number of features and can still achieve good predictive performance in EEG signals. The promising EEG signal classification results from our experiments prove that this approach can successfully extract important features. Our proposed method also has low memory requirements and computational costs.