Abstract
This paper treats segmentation of time patterns as a heuristic search problem. Segmentation is formulated in terms of image restoration. An observed pattern, which is the stochastically deformed image of a pure image consisting of a number of regimes, is to be segmented to recover the regimed structure. Standard statistical decision methods are not very useful here because of the computational difficulties involved. The search process described here consists of application of a sequence of heuristic-adaptive operators. Each operator is designed to detect certain flaws in previous segmentations and make modifications accordingly. The search path thus generated ends in a loop from among which the final solution is chosen by an evaluating function. Results of experiments with simulated data are presented and discussed.
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Research supported in part by an NSF research grant on pattern recognition (GJ-31007X2) and an ONR research contract on computer systems performance evaluation (NOOO14-67-A-0191-0026-01) while the author was at the Division of Applied Mathematics, Brown University, Rhode Island.
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Ang, BT. A Heuristic-adaptive procedure for segmentation of time patterns. International Journal of Computer and Information Sciences 4, 329–348 (1975). https://doi.org/10.1007/BF00979373
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DOI: https://doi.org/10.1007/BF00979373