An Algorithm for Optimal Partitioning of Data on an Interval

Author name not available (Why is that?)

Publication date: 17 September 2003

Abstract: Many signal processing problems can be solved by maximizing the fitness of a segmented model over all possible partitions of the data interval. This letter describes a simple but powerful algorithm that searches the exponentially large space of partitions of

N

data points in time

O (N^{2})

. The algorithm is guaranteed to find the exact global optimum, automatically determines the model order (the number of segments), has a convenient real-time mode, can be extended to higher dimensional data spaces, and solves a surprising variety of problems in signal detection and characterization, density estimation, cluster analysis and classification.

Has companion code repository: https://github.com/as4378/opart

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