An Algorithm for Optimal Partitioning of Data on an Interval
Numerical Analysis
2025-10-20 v2 Astrophysics
Computational Engineering, Finance, and Science
Data Structures and Algorithms
Information Theory
Numerical Analysis
Combinatorics
math.IT
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 data points in time . 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.
Cite
@article{arxiv.math/0309285,
title = {An Algorithm for Optimal Partitioning of Data on an Interval},
author = {Brad Jackson and Jeffrey D. Scargle and David Barnes and Sundararajan Arabhi and Alina Alt and Peter Gioumousis and Elyus Gwin and Paungkaew Sangtrakulcharoen and Linda Tan and Tun Tao Tsai},
journal= {arXiv preprint arXiv:math/0309285},
year = {2025}
}
Comments
3 pages, 1 figure, submitted to IEEE Signal Processing Letters, revised version with added references