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Discontinuity, Nonlinearity, and Complexity

Dimitry Volchenkov (editor), Dumitru Baleanu (editor)

Dimitry Volchenkov(editor)

Mathematics & Statistics, Texas Tech University, 1108 Memorial Circle, Lubbock, TX 79409, USA


Dumitru Baleanu (editor)

Cankaya University, Ankara, Turkey; Institute of Space Sciences, Magurele-Bucharest, Romania


Relation Between Autocorrelation Sequence and Average Shortest-Path Length in a Time Serie to Network Mapping

Discontinuity, Nonlinearity, and Complexity 8(2) (2019) 241--246 | DOI:10.5890/DNC.2019.06.010

Amanda Leite de Camargo, Marcio Eisencraft

Universidade Federal do ABC, Santo André, Brazil and Escola Polit´ecnica, University of São Paulo, São Paulo, Brazil

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An invertible mapping between time series and networks was recently proposed. It can be used as a tool to figure out properties of the mapped time series. In the present work we use controlled artificial signals to numerically investigate how correlation properties of time series are mapped in the topological measures of associated networks. More specifically, we employ filtered uniform white noise and analyse how the autocorrelation sequence influences the average shortest-path length.


This study was financed in part by the Coordenação de Aperfeic¸oamento de Pessoal de Nível Superior - Brazil (CAPES) - Finance Code 001. M.E. was partially supported by CNPq (grant 309275/2016-4).


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