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ICA
2012
Springer

A Canonical Correlation Analysis Based Method for Improving BSS of Two Related Data Sets

8 years 2 months ago
A Canonical Correlation Analysis Based Method for Improving BSS of Two Related Data Sets
We consider an extension of ICA and BSS for separating mutually dependent and independent components from two related data sets. We propose a new method which first uses canonical correlation analysis for detecting subspaces of independent and dependent components. Different ICA and BSS methods can after this be used for final separation of these components. Our method has a sound theoretical basis, and it is straightforward to implement and computationally not demanding. Experimental results on synthetic and real-world fMRI data sets demonstrate its good performance.
Juha Karhunen, Tele Hao, Jarkko Ylipaavalniemi
Added 24 Apr 2012
Updated 24 Apr 2012
Type Journal
Year 2012
Where ICA
Authors Juha Karhunen, Tele Hao, Jarkko Ylipaavalniemi
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