The entropy of a binary Hidden Markov Process

Or Zuk; Ido Kanter; Eytan Domany

doi:10.1007/s10955-005-7576-y

The entropy of a binary Hidden Markov Process

Or Zuk^*, Ido Kanter, Eytan Domany

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

30 Scopus citations

Abstract

The entropy of a binary symmetric Hidden Markov Process is calculated as an expansion in the noise parameter ε. 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 ε. Using a conjecture we extend the calculation to 11th order and discuss the convergence of the resulting series.

Original language	English
Pages (from-to)	343-360
Number of pages	18
Journal	Journal of Statistical Physics
Volume	121
Issue number	3-4
DOIs	https://doi.org/10.1007/s10955-005-7576-y
State	Published - Sep 2005
Externally published	Yes

Bibliographical note

Funding Information:
I.K. thanks N. Merhav for very helpful comments, and the Einstein Center for Theoretical Physics for partial support. This work was partially supported by grants from the Minerva Foundation and by the European Community’s Human Potential Programme under Contract HPRN-CT-2002-00319, STIPCO.

Keywords

Entropy
Hidden Markov Process
Random-field Ising model

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10.1007/s10955-005-7576-y

Cite this

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AB - The entropy of a binary symmetric Hidden Markov Process is calculated as an expansion in the noise parameter ε. 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 ε. Using a conjecture we extend the calculation to 11th order and discuss the convergence of the resulting series.

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KW - Random-field Ising model

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The entropy of a binary Hidden Markov Process

Abstract

Bibliographical note

Keywords

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