Literature DB >> 33670121

The Entropy Universe.

Maria Ribeiro1,2, Teresa Henriques3,4, Luísa Castro3, André Souto5,6,7, Luís Antunes1,2, Cristina Costa-Santos3,4, Andreia Teixeira3,4,8.   

Abstract

About 160 years ago, the concept of entropy was introduced in thermodynamics by Rudolf Clausius. Since then, it has been continually extended, interpreted, and applied by researchers in many scientific fields, such as general physics, information theory, chaos theory, data mining, and mathematical linguistics. This paper presents The Entropy Universe, which aims to review the many variants of entropies applied to time-series. The purpose is to answer research questions such as: How did each entropy emerge? What is the mathematical definition of each variant of entropy? How are entropies related to each other? What are the most applied scientific fields for each entropy? We describe in-depth the relationship between the most applied entropies in time-series for different scientific fields, establishing bases for researchers to properly choose the variant of entropy most suitable for their data. The number of citations over the past sixteen years of each paper proposing a new entropy was also accessed. The Shannon/differential, the Tsallis, the sample, the permutation, and the approximate entropies were the most cited ones. Based on the ten research areas with the most significant number of records obtained in the Web of Science and Scopus, the areas in which the entropies are more applied are computer science, physics, mathematics, and engineering. The universe of entropies is growing each day, either due to the introducing new variants either due to novel applications. Knowing each entropy's strengths and of limitations is essential to ensure the proper improvement of this research field.

Entities:  

Keywords:  application areas; entropy measures; information theory; time-series

Year:  2021        PMID: 33670121     DOI: 10.3390/e23020222

Source DB:  PubMed          Journal:  Entropy (Basel)        ISSN: 1099-4300            Impact factor:   2.524


  6 in total

1.  Estimation of different types of entropies for the Kumaraswamy distribution.

Authors:  Abdulhakim A Al-Babtain; Ibrahim Elbatal; Christophe Chesneau; Mohammed Elgarhy
Journal:  PLoS One       Date:  2021-03-30       Impact factor: 3.240

2.  EntropyHub: An open-source toolkit for entropic time series analysis.

Authors:  Matthew W Flood; Bernd Grimm
Journal:  PLoS One       Date:  2021-11-04       Impact factor: 3.240

3.  Entropy Method of Road Safety Management: Case Study of the Russian Federation.

Authors:  Artur I Petrov
Journal:  Entropy (Basel)       Date:  2022-01-25       Impact factor: 2.524

4.  Non-linear Methods Predominant in Fetal Heart Rate Analysis: A Systematic Review.

Authors:  Maria Ribeiro; João Monteiro-Santos; Luísa Castro; Luís Antunes; Cristina Costa-Santos; Andreia Teixeira; Teresa S Henriques
Journal:  Front Med (Lausanne)       Date:  2021-11-30

5.  Pressure Injury Link to Entropy of Abdominal Temperature.

Authors:  Nikhil Padhye; Denise Rios; Vaunette Fay; Sandra K Hanneman
Journal:  Entropy (Basel)       Date:  2022-08-15       Impact factor: 2.738

6.  CEPS: An Open Access MATLAB Graphical User Interface (GUI) for the Analysis of Complexity and Entropy in Physiological Signals.

Authors:  David Mayor; Deepak Panday; Hari Kala Kandel; Tony Steffert; Duncan Banks
Journal:  Entropy (Basel)       Date:  2021-03-08       Impact factor: 2.524

  6 in total

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