# Separation of Correlated Astrophysical Sources Using Multiple-Lag Data Covariance Matrices

@article{Bedini2004SeparationOC, title={Separation of Correlated Astrophysical Sources Using Multiple-Lag Data Covariance Matrices}, author={Luigi Bedini and Diego Herranz and Emanuele Salerno and Carlo Baccigalupi and Ercan Engin Kuruoglu and Anna Tonazzini}, journal={EURASIP Journal on Advances in Signal Processing}, year={2004}, volume={2005}, pages={1-13} }

This paper proposes a new strategy to separate astrophysical sources that are mutually correlated. This strategy is based on second-order statistics and exploits prior information about the possible structure of the mixing matrix. Unlike ICA blind separation approaches, where the sources are assumed mutually independent and no prior knowledge is assumed about the mixing matrix, our strategy allows the independence assumption to be relaxed and performs the separation of even significantly…

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