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

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  • 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.
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    Cited by:

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    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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