Faster universal modeling for two source classes

A. Nowbakht, F.M.J. Willems

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The Universal Modeling algorithms proposed in [2] for two general classes of finite-context sources are reviewed. The above methods were constructed by viewing a model structure as a partition of the context space and realizing that a partition can be reached through successive splits. Here we start by constructing recursive counting algorithms to count all models belonging to the two classes and use the algorithms to perform the Bayesian Mixture. The resulting methods lead to computationally more efficient Universal Modeling algorithms.
Original languageEnglish
Title of host publication23rd symposium on information theory in the Benelux
EditorsB. Macq, J.-J. Quisquater
Place of PublicationEnschede
PublisherWerkgemeenschap voor Informatie- en Communicatietheorie (WIC)
ISBN (Print)90-71048-16-0
Publication statusPublished - 2002
Event2002 Symposium on Information Theory in the Benelux (SITB 2002) - Louvain-la-Neuve, Belgium
Duration: 29 May 200231 May 2002
Conference number: 23


Conference2002 Symposium on Information Theory in the Benelux (SITB 2002)
Abbreviated titleSITB 2002


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