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Guessing with Distributed Encoders

Two correlated sources emit a pair of sequences, each of which is observed by a different encoder. Each encoder produces a rate-limited description of the sequence it observes, and the two descriptions are presented to a guessing device that repeatedly produces sequence pairs until correct. The numb...

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Detalles Bibliográficos
Autores principales: Bracher, Annina, Lapidoth, Amos, Pfister, Christoph
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514780/
https://www.ncbi.nlm.nih.gov/pubmed/33267013
http://dx.doi.org/10.3390/e21030298
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author Bracher, Annina
Lapidoth, Amos
Pfister, Christoph
author_facet Bracher, Annina
Lapidoth, Amos
Pfister, Christoph
author_sort Bracher, Annina
collection PubMed
description Two correlated sources emit a pair of sequences, each of which is observed by a different encoder. Each encoder produces a rate-limited description of the sequence it observes, and the two descriptions are presented to a guessing device that repeatedly produces sequence pairs until correct. The number of guesses until correct is random, and it is required that it have a moment (of some prespecified order) that tends to one as the length of the sequences tends to infinity. The description rate pairs that allow this are characterized in terms of the Rényi entropy and the Arimoto–Rényi conditional entropy of the joint law of the sources. This solves the guessing analog of the Slepian–Wolf distributed source-coding problem. The achievability is based on random binning, which is analyzed using a technique by Rosenthal.
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spelling pubmed-75147802020-11-09 Guessing with Distributed Encoders Bracher, Annina Lapidoth, Amos Pfister, Christoph Entropy (Basel) Article Two correlated sources emit a pair of sequences, each of which is observed by a different encoder. Each encoder produces a rate-limited description of the sequence it observes, and the two descriptions are presented to a guessing device that repeatedly produces sequence pairs until correct. The number of guesses until correct is random, and it is required that it have a moment (of some prespecified order) that tends to one as the length of the sequences tends to infinity. The description rate pairs that allow this are characterized in terms of the Rényi entropy and the Arimoto–Rényi conditional entropy of the joint law of the sources. This solves the guessing analog of the Slepian–Wolf distributed source-coding problem. The achievability is based on random binning, which is analyzed using a technique by Rosenthal. MDPI 2019-03-19 /pmc/articles/PMC7514780/ /pubmed/33267013 http://dx.doi.org/10.3390/e21030298 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Bracher, Annina
Lapidoth, Amos
Pfister, Christoph
Guessing with Distributed Encoders
title Guessing with Distributed Encoders
title_full Guessing with Distributed Encoders
title_fullStr Guessing with Distributed Encoders
title_full_unstemmed Guessing with Distributed Encoders
title_short Guessing with Distributed Encoders
title_sort guessing with distributed encoders
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514780/
https://www.ncbi.nlm.nih.gov/pubmed/33267013
http://dx.doi.org/10.3390/e21030298
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