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- W1533009621 abstract "A simple algorithm finds the partition of a data interval optimizing the fitness of a model that represents the underlying signal as constant over the elements of the partition. Using dynamic programming the exponentially large space of partitions of N data points is implicitly but exhaustively searched in time O(N2). This paper also describes an extension to optimal partitions of higher dimensional data spaces, with application to multivariate signal processing, image processing, cluster analysis, density estimation in 3‐dimensional redshift surveys, etc. The algorithm finds the exact global optimum, automatically determines the model order (the number of segments), and has a convenient real‐time mode." @default.
- W1533009621 created "2016-06-24" @default.
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- W1533009621 date "2005-01-01" @default.
- W1533009621 modified "2023-09-26" @default.
- W1533009621 title "Density Estimation via Optimal Segmentation" @default.
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- W1533009621 doi "https://doi.org/10.1063/1.2149784" @default.
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