Fuzzy information granules in time series data

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.