The entropy of a binary Hidden Markov Process

Or Zuk*, Ido Kanter, Eytan Domany

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

30 Scopus citations


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 languageAmerican English
Pages (from-to)343-360
Number of pages18
JournalJournal of Statistical Physics
Issue number3-4
StatePublished - Sep 2005
Externally publishedYes

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.


  • Entropy
  • Hidden Markov Process
  • Random-field Ising model


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