Measuring the similarity between trajectories using clustering techniques.
A clustering method has been developed to group signals that display similar dynamic behavior. The procedure involves using the method of time delay embedding to construct a trajectory in state space from a time series. Certain features that characterize the geometry of the trajectory have been defined. These features were subjected to a series of statistical tests to determine their usefulness in a hierarchical clustering analysis. The latter is aimed at finding groups of similar trajectories. The trajectory-based clustering algorithm has been applied to simulated data, which included both stochastic data generated by a linear AR model, and nonlinear data generated by a Duffing oscillator. The results show that the algorithm works reliably in both cases.
Jansen
Ben H.
BH
Department of Electrical Engineering and Bioengineering Research Center, University of Houston, Houston, Texas 77204-4793.
Nyberg
Henrik N.
HN