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Heuristic segmentation of a nonstationary time series Kensuke Fukuda,1,2,3
 

Summary: Heuristic segmentation of a nonstationary time series
Kensuke Fukuda,1,2,3
H. Eugene Stanley,2
and Lui´s A. Nunes Amaral3
1
NTT Network Innovation Laboratories, Tokyo 180-8585, Japan
2
Center for Polymer Studies and Department of Physics, Boston University, Boston, Massachusetts 02215, USA
3
Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, USA
Received 4 August 2003; published 25 February 2004
Many phenomena, both natural and human influenced, give rise to signals whose statistical properties
change under time translation, i.e., are nonstationary. For some practical purposes, a nonstationary time series
can be seen as a concatenation of stationary segments. However, the exact segmentation of a nonstationary
time series is a hard computational problem which cannot be solved exactly by existing methods. For this
reason, heuristic methods have been proposed. Using one such method, it has been reported that for several
cases of interest--e.g., heart beat data and Internet traffic fluctuations--the distribution of durations of these
stationary segments decays with a power-law tail. A potential technical difficulty that has not been thoroughly
investigated is that a nonstationary time series with a scalefree power-law distribution of stationary segments
is harder to segment than other nonstationary time series because of the wider range of possible segment

  

Source: Amaral, Luis A.N. - Department of Chemical and Biological Engineering, Northwestern University
Stanley, H. Eugene - Department of Physics, Boston University

 

Collections: Biology and Medicine; Computer Technologies and Information Sciences; Materials Science; Physics