Blind detection of independent dynamic components

Authors:
L. K. Hansen;J. Larsen;T. Kolenda
Affiliations:
Dept. for Math. Modelling, Tech. Univ. of Denmark, Lyngby, Denmark;-;-
Venue:
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 05
Year:
2001

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Abstract

In certain applications of independent component analysis (ICA) it is 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 efficiently as an unbiased test set estimator.