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access icon free Multiscale complex network constructed from chaotic time series

  • Author(s): J.C. Sun 1
    • View affiliations
    • Affiliations: 1: School of Software and Communication Engineering, Jiangxi University of Finance and Economics, Maple Road No. 632, Nanchang 330013, People's Republic of China
  • Source: Volume 49, Issue 17, 15 August 2013, p. 1078 – 1079
    DOI:  10.1049/el.2013.1599 , Print ISSN 0013-5194, Online ISSN 1350-911X
© The Institution of Engineering and Technology
Received 09/05/2013, Published

Complex networks play a significant role in modern complex systems sciences in that they allow for the quantitative analysis of the structural properties of systems composed of different interacting entities. Recently, intensive efforts have been made to apply network-based concepts also for the analysis of time series. In this reported work, multiscale complex networks from the chaotic time series are constructed by a decomposition strategy. Since different components exist in the time series, it was found that the constructed network inherits the multiscale properties of the time series in its structure. For example, periodic series and noisy series convert into regular networks and random networks, respectively. A novel method for the chaotic time series analysis is provided.

Inspec keywords: network analysis; time series; chaos

Other keywords: chaotic time series analysis; regular networks; complex systems; multiscale complex network; decomposition strategy; noisy series; random networks; periodic series

Subjects: General circuit analysis and synthesis methods; Chaotic behaviour in circuits

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