Network analysis of time series under the constraint of fixed nearest neighbors
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.
Volume (Year): 392 (2013)
Issue (Month): 4 ()
|Contact details of provider:|| Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/|
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- 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.
- 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.
When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:392:y:2013:i:4:p:967-973. See general information about how to correct material in RePEc.
If references are entirely missing, you can add them using this form.