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Approximating Information Measures for Fields
We supply corrected proofs of the invariance of completion and the chain rule for the Shannon information measures of arbitrary fields, as stated by Dębowski in 2009. Our corrected proofs rest on a number of auxiliary approximation results for Shannon information measures, which may be of an indepen...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516512/ https://www.ncbi.nlm.nih.gov/pubmed/33285857 http://dx.doi.org/10.3390/e22010079 |
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author | Dębowski, Łukasz |
author_facet | Dębowski, Łukasz |
author_sort | Dębowski, Łukasz |
collection | PubMed |
description | We supply corrected proofs of the invariance of completion and the chain rule for the Shannon information measures of arbitrary fields, as stated by Dębowski in 2009. Our corrected proofs rest on a number of auxiliary approximation results for Shannon information measures, which may be of an independent interest. As also discussed briefly in this article, the generalized calculus of Shannon information measures for fields, including the invariance of completion and the chain rule, is useful in particular for studying the ergodic decomposition of stationary processes and its links with statistical modeling of natural language. |
format | Online Article Text |
id | pubmed-7516512 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75165122020-11-09 Approximating Information Measures for Fields Dębowski, Łukasz Entropy (Basel) Article We supply corrected proofs of the invariance of completion and the chain rule for the Shannon information measures of arbitrary fields, as stated by Dębowski in 2009. Our corrected proofs rest on a number of auxiliary approximation results for Shannon information measures, which may be of an independent interest. As also discussed briefly in this article, the generalized calculus of Shannon information measures for fields, including the invariance of completion and the chain rule, is useful in particular for studying the ergodic decomposition of stationary processes and its links with statistical modeling of natural language. MDPI 2020-01-09 /pmc/articles/PMC7516512/ /pubmed/33285857 http://dx.doi.org/10.3390/e22010079 Text en © 2020 by the author. 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 Dębowski, Łukasz Approximating Information Measures for Fields |
title | Approximating Information Measures for Fields |
title_full | Approximating Information Measures for Fields |
title_fullStr | Approximating Information Measures for Fields |
title_full_unstemmed | Approximating Information Measures for Fields |
title_short | Approximating Information Measures for Fields |
title_sort | approximating information measures for fields |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516512/ https://www.ncbi.nlm.nih.gov/pubmed/33285857 http://dx.doi.org/10.3390/e22010079 |
work_keys_str_mv | AT debowskiłukasz approximatinginformationmeasuresforfields |