TITLE: Blind detection of independent dynamic components
AUTHORS: Lars Kai Hansen, Jan Larsen, Thomas Kolenda,
Informatics and Mathematical Modelling, Building 321
Technical University of Denmark, DK-2800 Lyngby, Denmark
In certain applications of independent component analysis (ICA)
it any of interest
to test hypotheses concerning the number of components or simply
to test whether a given number of components is significant relative
to a ``white noise'' null hypothesis. We estimate probabilities of
such competing hypotheses
for ICA based on dynamic decorrelation.
are evaluated in the so-called Bayesian information criterion
approximation, however, they are able to detect the
content of dynamic components as efficient
as an unbiased test set estimator.
Apperas in proc. of ICASSP-2001, Salt Lake City, USA, May 2001.