Literature DB >> 18362361

From time series to complex networks: the visibility graph.

Lucas Lacasa1, Bartolo Luque, Fernando Ballesteros, Jordi Luque, Juan Carlos Nuño.   

Abstract

In this work we present a simple and fast computational method, the visibility algorithm, that converts a time series into a graph. The constructed graph inherits several properties of the series in its structure. Thereby, periodic series convert into regular graphs, and random series do so into random graphs. Moreover, fractal series convert into scale-free networks, enhancing the fact that power law degree distributions are related to fractality, something highly discussed recently. Some remarkable examples and analytical tools are outlined to test the method's reliability. Many different measures, recently developed in the complex network theory, could by means of this new approach characterize time series from a new point of view.

Year:  2008        PMID: 18362361      PMCID: PMC2278201          DOI: 10.1073/pnas.0709247105

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  7 in total

1.  Emergence of scaling in random networks

Authors: 
Journal:  Science       Date:  1999-10-15       Impact factor: 47.728

2.  Self-similarity of complex networks.

Authors:  Chaoming Song; Shlomo Havlin; Hernán A Makse
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3.  Modeling bursts and heavy tails in human dynamics.

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4.  Fractality in complex networks: critical and supercritical skeletons.

Authors:  J S Kim; K-I Goh; G Salvi; E Oh; B Kahng; D Kim
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2007-01-29

5.  Skeleton and fractal scaling in complex networks.

Authors:  K-I Goh; G Salvi; B Kahng; D Kim
Journal:  Phys Rev Lett       Date:  2006-01-11       Impact factor: 9.161

6.  Collective dynamics of 'small-world' networks.

Authors:  D J Watts; S H Strogatz
Journal:  Nature       Date:  1998-06-04       Impact factor: 49.962

7.  Complex network from pseudoperiodic time series: topology versus dynamics.

Authors:  J Zhang; M Small
Journal:  Phys Rev Lett       Date:  2006-06-14       Impact factor: 9.161

  7 in total
  93 in total

1.  Visibility Graph Based Time Series Analysis.

Authors:  Mutua Stephen; Changgui Gu; Huijie Yang
Journal:  PLoS One       Date:  2015-11-16       Impact factor: 3.240

2.  Characterizing air quality data from complex network perspective.

Authors:  Xinghua Fan; Li Wang; Huihui Xu; Shasha Li; Lixin Tian
Journal:  Environ Sci Pollut Res Int       Date:  2015-10-22       Impact factor: 4.223

3.  Superfamily phenomena and motifs of networks induced from time series.

Authors:  Xiaoke Xu; Jie Zhang; Michael Small
Journal:  Proc Natl Acad Sci U S A       Date:  2008-12-08       Impact factor: 11.205

4.  Analysis of heart rate signals during meditation using visibility graph complexity.

Authors:  Mahda Nasrolahzadeh; Zeynab Mohammadpoory; Javad Haddadnia
Journal:  Cogn Neurodyn       Date:  2018-08-27       Impact factor: 5.082

5.  Decoding cortical brain states from widefield calcium imaging data using visibility graph.

Authors:  Li Zhu; Christian R Lee; David J Margolis; Laleh Najafizadeh
Journal:  Biomed Opt Express       Date:  2018-06-07       Impact factor: 3.732

6.  Temperature time series analysis at Yucatan using natural and horizontal visibility algorithms.

Authors:  J Alberto Rosales-Pérez; Efrain Canto-Lugo; David Valdés-Lozano; Rodrigo Huerta-Quintanilla
Journal:  PLoS One       Date:  2019-12-19       Impact factor: 3.240

Review 7.  Clinical correlates of graph theory findings in temporal lobe epilepsy.

Authors:  Zulfi Haneef; Sharon Chiang
Journal:  Seizure       Date:  2014-07-23       Impact factor: 3.184

8.  WLPVG approach to the analysis of EEG-based functional brain network under manual acupuncture.

Authors:  Xin Pei; Jiang Wang; Bin Deng; Xile Wei; Haitao Yu
Journal:  Cogn Neurodyn       Date:  2014-06-03       Impact factor: 5.082

9.  Using symbolic networks to analyse dynamical properties of disease outbreaks.

Authors:  José L Herrera-Diestra; Javier M Buldú; Mario Chavez; Johann H Martínez
Journal:  Proc Math Phys Eng Sci       Date:  2020-04-29       Impact factor: 2.704

10.  A recurrence network approach for the analysis of skin blood flow dynamics in response to loading pressure.

Authors:  Fuyuan Liao; Yih-Kuen Jan
Journal:  J Biomed Graph Comput       Date:  2012-06
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