The Entropy of a Binary Hidden Markov Process
Information Theory
2009-11-11 v1 Statistical Mechanics
math.IT
Statistics Theory
Statistics Theory
Abstract
The entropy of a binary symmetric Hidden Markov Process is calculated as an expansion in the noise parameter epsilon. We map the problem onto a one-dimensional Ising model in a large field of random signs and calculate the expansion coefficients up to second order in epsilon. Using a conjecture we extend the calculation to 11th order and discuss the convergence of the resulting series.
Keywords
Cite
@article{arxiv.cs/0507060,
title = {The Entropy of a Binary Hidden Markov Process},
author = {O. Zuk and I. Kanter and E. Domany},
journal= {arXiv preprint arXiv:cs/0507060},
year = {2009}
}