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Network analysis of time series under the constraint of fixed nearest neighbors

Author

Listed:
  • Dong, Yan
  • Huang, Wenwen
  • Liu, Zonghua
  • Guan, Shuguang

Abstract

In this paper, we carried out network analysis for typical time series, such as periodic signals, chaotic maps, Gaussian white noise, and fractal Brownian motions. By reconstructing the phase space for a given time series, we can generate a network under the constraint of fixed nearest neighbors. The mapped networks are then analyzed from both the statistical properties, such as degree distribution, clustering coefficient, betweenness, etc, as well as the local topological structures, i.e., network motifs. It is shown that time series of different nature can be distinguished from these two aspects of the constructed networks.

Suggested Citation

  • Dong, Yan & Huang, Wenwen & Liu, Zonghua & Guan, Shuguang, 2013. "Network analysis of time series under the constraint of fixed nearest neighbors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 967-973.
  • Handle: RePEc:eee:phsmap:v:392:y:2013:i:4:p:967-973
    DOI: 10.1016/j.physa.2012.10.014
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    References listed on IDEAS

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    1. Yang, Yue & Wang, Jianbo & Yang, Huijie & Mang, Jingshi, 2009. "Visibility graph approach to exchange rate series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(20), pages 4431-4437.
    2. Xie, Wen-Jie & Zhou, Wei-Xing, 2011. "Horizontal visibility graphs transformed from fractional Brownian motions: Topological properties versus the Hurst index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3592-3601.
    3. Gutin, Gregory & Mansour, Toufik & Severini, Simone, 2011. "A characterization of horizontal visibility graphs and combinatorics on words," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(12), pages 2421-2428.
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    Cited by:

    1. Tang, Jinjun & Wang, Yinhai & Wang, Hua & Zhang, Shen & Liu, Fang, 2014. "Dynamic analysis of traffic time series at different temporal scales: A complex networks approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 303-315.
    2. Wang, Minggang & Tian, Lixin & Xu, Hua & Li, Weiyu & Du, Ruijin & Dong, Gaogao & Wang, Jie & Gu, Jiani, 2017. "Systemic risk and spatiotemporal dynamics of the consumer market of China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 188-204.
    3. Provata, A. & Panagakou, E., 2014. "Abstract phase space networks describing reactive dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 181-193.
    4. Wang, Minggang & Tian, Lixin, 2016. "From time series to complex networks: The phase space coarse graining," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 456-468.

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