Title :
Fuzzy information granules in time series data
Author :
Ortolani, Marco ; Hofer, Heiko ; Patterson, David ; Höppner, Frank ; Berthold, Michael R.
fDate :
6/24/1905 12:00:00 AM
Abstract :
It is often desirable to summarize a set of time series through typical shapes in order to analyze them. The algorithm presented here compares pieces of different time series in order to find similar shapes. The use of a fuzzy clustering technique based on fuzzy c-means allows us to consider such subsets belonging to typical shapes with a degree of membership. Additionally, this matching is invariant with respect to a scaling of the time series. The algorithm is demonstrated on a widely known set of data taken from the ECG rhythm analysis experiments performed at MIT laboratories
Keywords :
electrocardiography; fuzzy set theory; medical signal detection; optimisation; pattern clustering; time series; ECG rhythm analysis; fuzzy c-means; fuzzy clustering; fuzzy set theory; optimization; shape recognition; time series; Algorithm design and analysis; Clustering algorithms; Data analysis; Electrocardiography; Information analysis; Performance analysis; Prototypes; Rhythm; Shape; Time series analysis;
Conference_Titel :
Fuzzy Systems, 2002. FUZZ-IEEE'02. Proceedings of the 2002 IEEE International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7280-8
DOI :
10.1109/FUZZ.2002.1005077