Thermodynamics of the binary symmetric channel

Evgeny Verbitskiy*

*Corresponding author for this work

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We study a hidden Markov process which is the result of a transmission of the binary symmetric Markov source over the memoryless binary symmetric channel. This process has been studied extensively in Information Theory and is often used as a benchmark case for the so-called denoising algorithms. Exploiting the link between this process and the 1D Random Field Ising Model (RFIM), we are able to identify the Gibbs potential of the resulting Hidden Markov process. Moreover, we obtain a stronger bound on the memory decay rate. We conclude with a discussion on implications of our results for the development of denoising algorithms.

Original languageEnglish
Article number2
Number of pages9
JournalPacific journal of mathematics for industry
Publication statusPublished - 14-Mar-2016


  • Hidden Markov models
  • Gibbs states
  • Thermodynamic formalism
  • Denoising

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