2014 IEEE International Conference on Image Processing (ICIP) 2014
DOI: 10.1109/icip.2014.7026215
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Sparse blind source separation for partially correlated sources

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Cited by 2 publications
(4 citation statements)
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“…Subsequently, even theoretically decorrelated components exhibit some correlation, customarily named chance correlations, which can be regarded as partial correlation between the components. However, it has been well established that partial correlations dramatically hamper the efficiency of component separation methods (Bobin et al 2014a(Bobin et al , 2015.…”
Section: Sparse Component Separation For Cmb Reconstructionmentioning
confidence: 99%
“…Subsequently, even theoretically decorrelated components exhibit some correlation, customarily named chance correlations, which can be regarded as partial correlation between the components. However, it has been well established that partial correlations dramatically hamper the efficiency of component separation methods (Bobin et al 2014a(Bobin et al , 2015.…”
Section: Sparse Component Separation For Cmb Reconstructionmentioning
confidence: 99%
“…This algorithm has been shown to be very effective in distinguishing partially correlated sources. For more details, we refer to Bobin et al (2014a).…”
Section: Sparse Reconstruction Of the Cmb Polarization Mapsmentioning
confidence: 99%
“…The rationale of this algorithm relies on a weighting scheme that aims at penalizing correlated entries, which are the most detrimental for separation. This algorithm first means that some diagonal weight matrix Q (Bobin et al 2014a) needs to be defined, and secondly that the minimization problem in Eq. (15) needs to be substituted by Bobin et al (2014a) have shown that partially correlated samples are related to non-sparse columns of the source matrix S. Based on this relationship, it adaptively updates the weight matrix with respect to the estimated sources during the iterations of the algorithm.…”
Section: Sparse Reconstruction Of the Cmb Polarization Mapsmentioning
confidence: 99%
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