Summary

the 2014 International Symposium on Nonlinear Theory and its Applications

2014

Session Number:B2L-B

Session:

Number:B2L-B2

Generating surrogate time series from complex networks

Michael Small,  

pp.313-316

Publication Date:2014/9/14

Online ISSN:2188-5079

DOI:10.34385/proc.46.B2L-B2

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Summary:
The method of surrogate data is now well established and provides a framework for generating random signals that may then be used to test specific statistical hypotheses. We propose to extend this rationale to the various complex network reconstruction methods. Starting with an experimental time series we suggest building a complex network that represents the underlying dynamics of that signal. Then, using that network we generate random equivalent time series. This paper provides a brief review and road-map.