Monaural ICA of white noise mixtures is hard

Lars Kai Hansen, Kaare Brandt Petersen

AbstractSeparation of monaural linear mixtures of `white' source signals
is fundamentally ill-posed. In some situations it is not possible
to find the mixing coefficients for the full `blind' problem. If
the mixing coefficients are known, the structure of the source
prior distribution determines the source reconstruction error. If
the prior is strongly multi-modal source reconstruction is
possible with low error, while source signals from the typical
`long tailed' distributions used in many ICA settings can not be
reconstructed. We provide a qualitative discussion of the limits
of monaural blind separation of white noise signals and give a set
of `no go' cases.
TypeConference paper [With referee]
ConferenceProceedings of ICA'2003 Fourth Int. Symp.. on Independent Component Analysis and Blind Signal Separation, Nara Japan, April 4,
Year2003    pp. 815-820
Electronic version(s)[pdf]
BibTeX data [bibtex]
IMM Group(s)Intelligent Signal Processing


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