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
emails: lkhansen,jl,thko@imm.dtu.dk
www: http://eivind.imm.dtu.dk


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. The probabilities 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.