Abstract
Recently, sparse component analysis has become one of the most powerful tools for the blind source separation problem, under the hypothesis that the sources are sparse in a given domain. The multidisciplinary characteristic of this problem and its comprehensive formulation allows its applicability in several areas of interest such as hyperspectral images, speech, audio, seismic reflection…