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Universality Classes and Information-Theoretic Measures of Complexity via Group Entropies
We introduce a class of information measures based on group entropies, allowing us to describe the information-theoretical properties of complex systems. These entropic measures are nonadditive, and are mathematically deduced from a series of natural axioms. In addition, we require extensivity in or...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7136250/ https://www.ncbi.nlm.nih.gov/pubmed/32249779 http://dx.doi.org/10.1038/s41598-020-60188-y |
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author | Tempesta, Piergiulio Jensen, Henrik Jeldtoft |
author_facet | Tempesta, Piergiulio Jensen, Henrik Jeldtoft |
author_sort | Tempesta, Piergiulio |
collection | PubMed |
description | We introduce a class of information measures based on group entropies, allowing us to describe the information-theoretical properties of complex systems. These entropic measures are nonadditive, and are mathematically deduced from a series of natural axioms. In addition, we require extensivity in order to ensure that our information measures are meaningful. The entropic measures proposed are suitably defined for describing universality classes of complex systems, each characterized by a specific state space growth rate function. |
format | Online Article Text |
id | pubmed-7136250 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-71362502020-04-11 Universality Classes and Information-Theoretic Measures of Complexity via Group Entropies Tempesta, Piergiulio Jensen, Henrik Jeldtoft Sci Rep Article We introduce a class of information measures based on group entropies, allowing us to describe the information-theoretical properties of complex systems. These entropic measures are nonadditive, and are mathematically deduced from a series of natural axioms. In addition, we require extensivity in order to ensure that our information measures are meaningful. The entropic measures proposed are suitably defined for describing universality classes of complex systems, each characterized by a specific state space growth rate function. Nature Publishing Group UK 2020-04-06 /pmc/articles/PMC7136250/ /pubmed/32249779 http://dx.doi.org/10.1038/s41598-020-60188-y Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Tempesta, Piergiulio Jensen, Henrik Jeldtoft Universality Classes and Information-Theoretic Measures of Complexity via Group Entropies |
title | Universality Classes and Information-Theoretic Measures of Complexity via Group Entropies |
title_full | Universality Classes and Information-Theoretic Measures of Complexity via Group Entropies |
title_fullStr | Universality Classes and Information-Theoretic Measures of Complexity via Group Entropies |
title_full_unstemmed | Universality Classes and Information-Theoretic Measures of Complexity via Group Entropies |
title_short | Universality Classes and Information-Theoretic Measures of Complexity via Group Entropies |
title_sort | universality classes and information-theoretic measures of complexity via group entropies |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7136250/ https://www.ncbi.nlm.nih.gov/pubmed/32249779 http://dx.doi.org/10.1038/s41598-020-60188-y |
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