Permutation entropy and its main biomedical and econophysics applications: A review

Entropy is a powerful tool for the analysis of time series, as it allows describing the probability distributions of the possible state of a system, and therefore the information encoded in it. Nevertheless, important information may be codified also in the temporal dynamics, an aspect which is not...

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Detalhes bibliográficos
Autores: Zanin, Massimiliano, Zunino, Luciano José, Rosso, Osvaldo Anibal, Papo, David
Tipo de documento: artigo
Estado:Versão publicada
Data de publicação:2012
País:Argentina
Recursos:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositório:CONICET Digital (CONICET)
Idioma:inglês
OAI Identifier:oai:ri.conicet.gov.ar:11336/197305
Acesso em linha:http://hdl.handle.net/11336/197305
Access Level:Acceso aberto
Palavra-chave:ECONOPHYSICS
EEG
EPILEPSY
FORBIDDEN PATTERNS
PERMUTATION ENTROPY
SHANNON ENTROPY
https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
Descrição
Resumo:Entropy is a powerful tool for the analysis of time series, as it allows describing the probability distributions of the possible state of a system, and therefore the information encoded in it. Nevertheless, important information may be codified also in the temporal dynamics, an aspect which is not usually taken into account. The idea of calculating entropy based on permutation patterns (that is, permutations defined by the order relations among values of a time series) has received a lot of attention in the last years, especially for the understanding of complex and chaotic systems. Permutation entropy directly accounts for the temporal information contained in the time series; furthermore, it has the quality of simplicity, robustness and very low computational cost. To celebrate the tenth anniversary of the original work, here we analyze the theoretical foundations of the permutation entropy, as well as the main recent applications to the analysis of economical markets and to the understanding of biomedical systems.