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Subspace identification through blind source separation

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2 Author(s)
M. Grosse-Wentrup ; Inst. of Autom. Control Eng., Tech. Univ. Munich, Germany ; M. Buss

Given a linear and instantaneous mixture model, we prove that for blind source separation (BSS) algorithms based on mutual information, only sources with non-Gaussian distribution are consistently reconstructed independent of initial conditions. This allows the identification of non-Gaussian sources and consequently the identification of signal and noise subspaces through BSS. The results are illustrated with a simple example, and the implications for a variety of signal processing applications, such as denoising and model identification, are discussed.

Published in:

IEEE Signal Processing Letters  (Volume:13 ,  Issue: 2 )