Fuzzy Information Granules in Time Series Data

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2004
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Ortolani, Marco
Patterson, David
Höppner, Frank
Callan, Ondine
Hofer, Heiko
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International Journal of Intelligent Systems. 2004, 19(7), pp. 607-618. ISSN 0884-8173. eISSN 1098-111X. Available under: doi: 10.1002/int.20013
Zusammenfassung

Often, it is desirable to represent a set of time series through typical shapes in order to detect common patterns. The algorithm presented here compares pieces of a different time series in order to find such similar shapes. The use of a fuzzy clustering technique based on fuzzy c-means allows us to detect shapes that belong to a certain group of typical shapes with a degree of membership. Modifications to the original algorithm also allow this matching to be invariant with respect to a scaling of the time series. The algorithm is demonstrated on a widely known set of data taken from the electrocardiogram (ECG) rhythm analysis experiments performed at the Massachusetts Institute of Technology (MIT) laboratories and on data from protein mass spectrography. © 2004 Wiley Periodicals, Inc.

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ISO 690BERTHOLD, Michael R., Marco ORTOLANI, David PATTERSON, Frank HÖPPNER, Ondine CALLAN, Heiko HOFER, 2004. Fuzzy Information Granules in Time Series Data. In: International Journal of Intelligent Systems. 2004, 19(7), pp. 607-618. ISSN 0884-8173. eISSN 1098-111X. Available under: doi: 10.1002/int.20013
BibTex
@article{Berthold2004Fuzzy-24047,
  year={2004},
  doi={10.1002/int.20013},
  title={Fuzzy Information Granules in Time Series Data},
  number={7},
  volume={19},
  issn={0884-8173},
  journal={International Journal of Intelligent Systems},
  pages={607--618},
  author={Berthold, Michael R. and Ortolani, Marco and Patterson, David and Höppner, Frank and Callan, Ondine and Hofer, Heiko}
}
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