IEEE Transactions on Information Theory · 2002 · 21 citations · 6 references
Tree LanguageEngineeringBethe TreeInformation TheoryEntropyMarkov Chain FieldsStrong LawAlgorithmic Information TheoryShannon-mcmillan TheoremMarkov KernelTree AutomatonProbability TheoryComputer ScienceDiscrete MathematicsProbabilistic Graph TheoryKolmogorov Complexity
We study the strong law of large numbers and the Shannon-McMillan theorem for Markov chain fields on trees. First, we prove the strong law of large numbers for the frequencies of occurrence of states and ordered couples of states for Markov chain fields on trees. Then, we prove the Shannon-McMillan theorem with almost everywhere (a.e.) convergence for Markov chain fields on trees. We prove the results on a Bethe tree and then just state the analogous results on a rooted Cayley tree. In the proof, a new technique for establishing the strong limit theorem in probability theory is applied.
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Markov Random Fields on an Infinite Tree
Frank Spitzer · The Annals of Probability · 1975 · 198 citations · Full text
Entropic aspects of random fields on trees
Thomas Berger, Z. Ye · IEEE Transactions on Information Theory · 1990 · 70 citations
Automorphism Invariant Measures on Trees
Robin Pemantle · The Annals of Probability · 1992 · 50 citations · Full text