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- Algorithm
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- 2013-03-04
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- msreddy
Description: 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.
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