Identifiability Issues in Noisy ICA
Mike E. Davies · IEEE Signal Processing Letters · 2004
We consider the identifiability of the statistical model for noisy independent component analysis showing that while the mixing process is identifiable, the noise covariance is only partially so. This raises questions as to the performance of certain maximum-likelihood algorithms for blind source separation in the presence of noise.