Faster universal modeling for two source classes
A. Nowbakht, Fmj Frans Willems · TU/e Research Portal · 2002
Abstract. The Universal Modeling algorithms proposed in [2] for two general classes of finite-context sources are reviewed. The above meth-ods 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 al-gorithms 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. 1