Blind separation of non-circular sources
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Blind source separation is now a well known problem. When a priori information about the propagation or the geometry of the array is not available, the model can be generalized to a blind source separation model. It supposes the statistical independence of the sources and their non-gaussianity. In this paper, we focus on an algorithm, called canonical correlation analysis, based on the use of second order statistics.
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