Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1002/int.v19:7 | Int. J. Intell. Syst. |
Keywords | DocType | Volume |
time series,time series data,fuzzy clustering | Journal | 19 |
Issue | Citations | PageRank |
7 | 2 | 0.46 |
References | Authors | |
5 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael Berthold | 1 | 1452 | 158.49 |
| Marco Ortolani | 2 | 209 | 21.31 |
| David E. Patterson | 3 | 31 | 6.01 |
| Frank Höppner | 4 | 16 | 2.27 |
| Ondine Callan | 5 | 2 | 0.46 |
| Heiko Hofer | 6 | 20 | 2.40 |