Entropy: From thermodynamics to information processing
| dc.contributor.author | Natal, Jordão | |
| dc.contributor.author | Ávila, Ivonete [UNESP] | |
| dc.contributor.author | Tsukahara, Victor Batista | |
| dc.contributor.author | Pinheiro, Marcelo | |
| dc.contributor.author | Maciel, Carlos Dias | |
| dc.contributor.institution | Universidade de São Paulo (USP) | |
| dc.contributor.institution | Universidade Estadual Paulista (UNESP) | |
| dc.contributor.institution | Versatus Studio | |
| dc.date.accessioned | 2022-05-01T09:47:29Z | |
| dc.date.available | 2022-05-01T09:47:29Z | |
| dc.date.issued | 2021-10-01 | |
| dc.description.abstract | Entropy is a concept that emerged in the 19th century. It used to be associated with heat harnessed by a thermal machine to perform work during the Industrial Revolution. However, there was an unprecedented scientific revolution in the 20th century due to one of its most essential innovations, i.e., the information theory, which also encompasses the concept of entropy. Therefore, the following question is naturally raised: “what is the difference, if any, between concepts of entropy in each field of knowledge?” There are misconceptions, as there have been multiple attempts to conciliate the entropy of thermodynamics with that of information theory. Entropy is most commonly defined as “disorder”, although it is not a good analogy since “order” is a subjective human concept, and “disorder” cannot always be obtained from entropy. Therefore, this paper presents a historical background on the evolution of the term “entropy”, and provides mathematical evidence and logical arguments regarding its interconnection in various scientific areas, with the objective of providing a theoretical review and reference material for a broad audience. | en |
| dc.description.affiliation | Signal Processing Laboratory Department of Electrical and Computing Engineering University of São Paulo (USP) | |
| dc.description.affiliation | Laboratory of Combustion and Carbon Captur Department of Energy School of Engineering State University of São Paulo (Unesp) | |
| dc.description.affiliation | Versatus Studio | |
| dc.description.affiliationUnesp | Laboratory of Combustion and Carbon Captur Department of Energy School of Engineering State University of São Paulo (Unesp) | |
| dc.description.sponsorship | Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) | |
| dc.description.sponsorship | Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) | |
| dc.description.sponsorshipId | FAPESP: 2014/50851-0 | |
| dc.description.sponsorshipId | FAPESP: 2018/19150-6 | |
| dc.description.sponsorshipId | CNPq: 465755/2014-3 | |
| dc.identifier | http://dx.doi.org/10.3390/e23101340 | |
| dc.identifier.citation | Entropy, v. 23, n. 10, 2021. | |
| dc.identifier.doi | 10.3390/e23101340 | |
| dc.identifier.issn | 1099-4300 | |
| dc.identifier.scopus | 2-s2.0-85117918305 | |
| dc.identifier.uri | http://hdl.handle.net/11449/233741 | |
| dc.language.iso | eng | |
| dc.relation.ispartof | Entropy | |
| dc.source | Scopus | |
| dc.subject | Entropy | |
| dc.subject | Information theory | |
| dc.subject | Thermodynamics | |
| dc.title | Entropy: From thermodynamics to information processing | en |
| dc.type | Resenha | |
| dspace.entity.type | Publication | |
| unesp.department | Energia - FEG | pt |
