@CONFERENCE\{IMM2001-0827,
    author       = "L. K. Hansen and J. Larsen and T. Kolenda",
    title        = "Blind Detection of Independent Dynamic Components",
    year         = "2001",
    keywords     = "{BIC,} {ICA,} Chat room, keywords, Datamine",
    pages        = "3197--3200",
    booktitle    = "{IEEE} International Conference on Acoustics, Speech, and Signal Processing 2001",
    volume       = "5",
    series       = "",
    editor       = "",
    publisher    = "",
    organization = "",
    address      = "",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/827-full.html",
    abstract     = "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."
}