Sparse component analysis and blind source separation of underdetermined mixtures

Authors:
P. Georgiev;F. Theis;A. Cichocki
Affiliations:
Dept. of Electr. Comput. & Eng. Comput. Sci., Univ. of Cincinnati, OH, USA;-;-
Venue:
IEEE Transactions on Neural Networks
Year:
2005

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Abstract

In this letter, we solve the problem of identifying matrices S ∈ Rn×N and A ∈ Rm×n knowing only their multiplication X = AS, under some conditions, expressed either in terms of A and sparsity of S (identifiability conditions), or in terms of X (sparse component analysis (SCA) conditions). We present algorithms for such identification and illustrate them by examples.