Context trees, variable length Markov chains and dynamical sources.

Infinite random sequences of letters can be viewed as stochastic chains or as strings produced by a source, in the sense of information theory. The relationship between Variable Length Markov Chains (VLMC) and probabilistic dynamical sources is studied. We establish a probabilistic frame for context trees and VLMC and we prove that any VLMC is a dynamical source for which we explicitly build the mapping. On two examples, the "comb" and the "bamboo blossom", we find a necessary and sufficient condition for the existence and the uniqueness of a stationary probability measure for the VLMC. These two examples are detailed in order to provide the associated Dirichlet series as well as the generating functions of word occurrences.

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Additional Info

Field Value
Source Séminaire de Probabilités XLIV
Author Cénac, Peggy, Chauvin, Brigitte, Paccaut, Frédéric, Pouyanne, Nicolas
Maintainer CCSD
Last Updated May 14, 2026, 03:19 (UTC)
Created May 14, 2026, 03:19 (UTC)
Identifier ISBN: 978-3-642-27460-2
Language en
contributor Institut de Mathématiques de Bourgogne [Dijon] (IMB) ; Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)
creator Cénac, Peggy
date 2012-05-14T00:00:00
harvest_object_id 0435e07a-db73-407a-9da8-c3da8b9b7520
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2025-03-31T00:00:00
relation info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-642-27461-9_1
set_spec type:COUV