Open Access

An Energy-Based Similarity Measure for Time Series

  • Abdel-Ouahab Boudraa1, 2Email author,
  • Jean-Christophe Cexus2,
  • Mathieu Groussat1 and
  • Pierre Brunagel1
EURASIP Journal on Advances in Signal Processing20072008:135892

https://doi.org/10.1155/2008/135892

Received: 27 August 2006

Accepted: 24 July 2007

Published: 29 July 2007

Abstract

A new similarity measure, called SimilB, for time series analysis, based on the cross- -energy operator (2004), is introduced. is a nonlinear measure which quantifies the interaction between two time series. Compared to Euclidean distance (ED) or the Pearson correlation coefficient (CC), SimilB includes the temporal information and relative changes of the time series using the first and second derivatives of the time series. SimilB is well suited for both nonstationary and stationary time series and particularly those presenting discontinuities. Some new properties of are presented. Particularly, we show that as similarity measure is robust to both scale and time shift. SimilB is illustrated with synthetic time series and an artificial dataset and compared to the CC and the ED measures.

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Authors’ Affiliations

(1)
IRENav, Ecole Navale, Lanvéoc Poulmic
(2)
E3I2, EA 3876, ENSIETA

Copyright

© Abdel-Ouahab Boudraa et al. 2008

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.