Blind Detection of Independent Dynamic Components |
Lars Kai Hansen, Jan Larsen, Thomas Kolenda
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| 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. |
| Keywords | BIC, ICA, Chat room, keywords, Datamine |
| Type | Conference paper [With referee] |
| Conference | IEEE International Conference on Acoustics, Speech, and Signal Processing 2001 |
| Year | 2001 Vol. 5 pp. 3197--3200 |
| Electronic version(s) | [pdf] |
| BibTeX data | [bibtex] |
| IMM Group(s) | Intelligent Signal Processing |