An invariant of finitary codes with finite expected square root coding length
Probability
2007-07-13 v1 Information Theory
math.IT
Abstract
Let and be probability vectors with the same entropy . Denote by the Bernoulli shift indexed by with marginal distribution . Suppose that is a measure preserving homomorphism from to . We prove that if the coding length of has a finite 1/2 moment, then , where is the {\dof informational variance} of . In this result, which sharpens a theorem of Parry (1979), the 1/2 moment cannot be replaced by a lower moment. On the other hand, for any , we exhibit probability vectors and that are not permutations of each other, such that there exists a finitary isomorphism from to where the coding lengths of and of its inverse have a finite moment. We also present an extension to ergodic Markov chains.
Cite
@article{arxiv.math/0309120,
title = {An invariant of finitary codes with finite expected square root coding length},
author = {Nate Harvey and Yuval Peres},
journal= {arXiv preprint arXiv:math/0309120},
year = {2007}
}
Comments
18 pages