Publication

Thermodynamics of the binary symmetric channel

Verbitskiy, E., 14-Mar-2016, In : Pacific journal of mathematics for industry. 8, 9 p., 2.

Research output: Contribution to journalArticleAcademicpeer-review

APA

Verbitskiy, E. (2016). Thermodynamics of the binary symmetric channel. Pacific journal of mathematics for industry, 8, [2]. https://doi.org/10.1186/s40736-015-0021-5

Author

Verbitskiy, Evgeny. / Thermodynamics of the binary symmetric channel. In: Pacific journal of mathematics for industry. 2016 ; Vol. 8.

Harvard

Verbitskiy, E 2016, 'Thermodynamics of the binary symmetric channel', Pacific journal of mathematics for industry, vol. 8, 2. https://doi.org/10.1186/s40736-015-0021-5

Standard

Thermodynamics of the binary symmetric channel. / Verbitskiy, Evgeny.

In: Pacific journal of mathematics for industry, Vol. 8, 2, 14.03.2016.

Research output: Contribution to journalArticleAcademicpeer-review

Vancouver

Verbitskiy E. Thermodynamics of the binary symmetric channel. Pacific journal of mathematics for industry. 2016 Mar 14;8. 2. https://doi.org/10.1186/s40736-015-0021-5


BibTeX

@article{5a2995e6081144bea692a24ec8781387,
title = "Thermodynamics of the binary symmetric channel",
abstract = "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.",
keywords = "Hidden Markov models, Gibbs states, Thermodynamic formalism, Denoising, HIDDEN MARKOV-PROCESSES, ENTROPY",
author = "Evgeny Verbitskiy",
year = "2016",
month = "3",
day = "14",
doi = "10.1186/s40736-015-0021-5",
language = "English",
volume = "8",
journal = "Pacific journal of mathematics for industry",
issn = "2198-4115",
publisher = "SPRINGER",

}

RIS

TY - JOUR

T1 - Thermodynamics of the binary symmetric channel

AU - Verbitskiy, Evgeny

PY - 2016/3/14

Y1 - 2016/3/14

N2 - 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.

AB - 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.

KW - Hidden Markov models

KW - Gibbs states

KW - Thermodynamic formalism

KW - Denoising

KW - HIDDEN MARKOV-PROCESSES

KW - ENTROPY

U2 - 10.1186/s40736-015-0021-5

DO - 10.1186/s40736-015-0021-5

M3 - Article

VL - 8

JO - Pacific journal of mathematics for industry

JF - Pacific journal of mathematics for industry

SN - 2198-4115

M1 - 2

ER -

ID: 65927676