Self-organized recurrence networks

Gang Liu, Hui Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Network theory leads to a new way to investigate the dynamics of complex systems. As a result, many methods were proposed to construct a network from nonlinear time series. However, most previous works focused on deriving the adjacency matrix to represent the complex network and extract network-theoretic measures. Although the adjacency matrix provides connectivity information of nodes and edges, the network geometry can take variable forms. The definite network topology remains unknown. This paper develops a self-organizing approach to derive the steady geometric structure of a network from the adjacency matrix. As such, novel network-theoretic measures can be achieved based on actual node-to-node distances in the self-organized network topology.

Original languageEnglish (US)
Title of host publicationIIE Annual Conference and Expo 2014
PublisherInstitute of Industrial Engineers
Pages149-158
Number of pages10
ISBN (Electronic)9780983762430
StatePublished - Jan 1 2014
EventIIE Annual Conference and Expo 2014 - Montreal, Canada
Duration: May 31 2014Jun 3 2014

Publication series

NameIIE Annual Conference and Expo 2014

Other

OtherIIE Annual Conference and Expo 2014
CountryCanada
CityMontreal
Period5/31/146/3/14

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering
  • Control and Systems Engineering

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  • Cite this

    Liu, G., & Yang, H. (2014). Self-organized recurrence networks. In IIE Annual Conference and Expo 2014 (pp. 149-158). (IIE Annual Conference and Expo 2014). Institute of Industrial Engineers.