Summary

Proceedings of the 2013 International Symposium on Nonlinear Theory and its Applications

2013

Session Number:B1L-A

Session:

Number:189

Nonlinear time series analysis of marked point process data

Koji Iwayama,  Yoshito Hirata,  Kazuyuki Aihara,  

pp.189-192

Publication Date:

Online ISSN:2188-5079

DOI:10.15248/proc.2.189

PDF download (704.5KB)

Summary:
Marked point process data are time series of discrete events which have some values as marks. A definition of a distance for marked point process data allows us to apply nonlinear time series analysis for marked point process data. However, the existing method uses only approximations of distances due to computational complexity. Here, we calculate exact values of distances and apply some methods of nonlinear time series analysis to a series of local maxima from a Rössler model. Results indicate the effectiveness of distance-based approach to analyze marked point process data.

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