Journal
IEEE SIGNAL PROCESSING LETTERS
Volume 12, Issue 2, Pages 105-108Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LSP.2001.838216
Keywords
Bayesian modeling; cluster analysis; density estimation; histograms; optimization; signal detection
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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 realtime 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.
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