Abstract
In this paper I present a Minimum Description Length Estimator for number of sources in an anechoic mixture of sparse signals. The criterion is roughly equal to the sum of negative normalized maximum log-likelihood and the logarithm of number of sources. Numerical evidence supports this approach and compares favorabily to both the Akaike (AIC) and Bayesian (BIC) Information Criteria. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Balan, R. (2007). Estimator for number of sources using Minimum Description Length criterion for blind sparse source mixtures. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4666 LNCS, pp. 333–340). Springer Verlag. https://doi.org/10.1007/978-3-540-74494-8_42
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