Memory efficient PCA methods for large group ICA

Principal component analysis (PCA) is widely used for data reduction in group independent component analysis (ICA) of fMRI data. Commonly, group-level PCA of temporally concatenated datasets is computed prior to ICA of the group principal components. This work focuses on reducing very high dimension...

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Bibliographic Details
Main Authors: Srinivas eRachakonda, Rogers F Silva, Jingyu eLiu, Vince D Calhoun
Format: Article
Language:English
Published: Frontiers Media S.A. 2016-02-01
Series:Frontiers in Neuroscience
Subjects:
PCA
SVD
Evd
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnins.2016.00017/full