Time series characterization via horizontal visibility graph and Information Theory
Autor: | Bruna Amin Gonçalves, Martín Gómez Ravetti, Laura C. Carpi, Osvaldo A. Rosso |
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Rok vydání: | 2016 |
Předmět: |
COMPLEX NETWORKS
Statistics and Probability Fractional Brownian motion Theoretical computer science Series (mathematics) Dynamical systems theory Ciencias Físicas Visibility graph Complex network Condensed Matter Physics Degree distribution Information theory 01 natural sciences TIME SERIES ANALYSIS INFORMATION THEORY QUANTIFIERS 010305 fluids & plasmas Astronomía 0103 physical sciences Probability distribution 010306 general physics Algorithm CIENCIAS NATURALES Y EXACTAS Mathematics |
Zdroj: | Physica A: Statistical Mechanics and its Applications. 464:93-102 |
ISSN: | 0378-4371 |
Popis: | Complex networks theory have gained wider applicability since methods for transformation of time series to networks were proposed and successfully tested. In the last few years, horizontal visibility graph has become a popular method due to its simplicity and good results when applied to natural and artificially generated data. In this work, we explore different ways of extracting information from the network constructed from the horizontal visibility graph and evaluated by Information Theory quantifiers. Most works use the degreedistribution of the network, however, we found alternative probability distributions, more efficient than the degree distribution in characterizing dynamical systems. In particular, we find that, when using distributions based on distances and amplitude values, significant shorter time series are required. We analyze fractional Brownian motion time series, and a paleoclimatic proxy record of ENSO from the Pallcacocha Lake to study dynamical changes during the Holocene. Fil: Gonçalves, Bruna Amin. Universidade Federal de Minas Gerais; Brasil Fil: Carpi, Laura. Universidad Politécnica de Catalunya; España Fil: Rosso, Osvaldo Aníbal. Universidade Federal de Alagoas; Brasil. Instituto Tecnológico de Buenos Aires; Argentina. Universidad de los Andes; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Ravetti, Martín G.. Universidade Federal de Minas Gerais; Brasil |
Databáze: | OpenAIRE |
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