Email this article Nonparametric Algorithms for Estimating the States of Natural Objects
- Authors: Lapko A.V.1,2, Lapko V.A.1,2
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Affiliations:
- Institute of Computational Modeling, Siberian Branch
- Reshetnev Siberian State University of Science and Technology
- Issue: Vol 54, No 5 (2018)
- Pages: 451-456
- Section: Analysis and Synthesis of Signals and Images
- URL: https://journals.rcsi.science/8756-6990/article/view/212557
- DOI: https://doi.org/10.3103/S8756699018050047
- ID: 212557
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Abstract
Modifications of a nonparametric pattern recognition algorithm corresponding to the maximum likelihood criterion with additional decision functions are considered. The synthesis of the proposed algorithms is based on the analysis of the ratios of the estimates of the probability density distributions of random variables in classes and their functionals with input thresholds. The choice of the thresholds is determined by specific features of the classification problem. The results obtained are applied for assessing the states of forest tracts on the basis of remote sensing data.
About the authors
A. V. Lapko
Institute of Computational Modeling, Siberian Branch; Reshetnev Siberian State University of Science and Technology
Author for correspondence.
Email: lapko@icm.krasn.ru
Russian Federation, Academgorodok-50, 44, Krasnoyarsk, 660036; pr. Krasnoyarskii rabochii 31, Krasnoyarsk, 660037
V. A. Lapko
Institute of Computational Modeling, Siberian Branch; Reshetnev Siberian State University of Science and Technology
Email: lapko@icm.krasn.ru
Russian Federation, Academgorodok-50, 44, Krasnoyarsk, 660036; pr. Krasnoyarskii rabochii 31, Krasnoyarsk, 660037
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