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International Theoretical Science Journal
Volume 61 >>> № 1 JANUARY — FEBRUARY 2025
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DOI 10.34229/KCA2522-9664.25.1.17
UDC 004.93:004.89
V.M. Opanasenko1, Sh.Kh. Fazilov2, N.M. Mirzaev3,
Sh.S. Kakharov4


1 V.M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine

 vlopanas@ukr.net

2 Digital Technologies and Artificial Intelligence Research Institute, Tashkent, Uzbekistan

 sh.fazilov@gmail.com

3 Digital Technologies and Artificial Intelligence Research Institute, Tashkent, Uzbekistan

 m.n.mirzaev@yahoo.com

4 Kokand University,
Kokand, Uzbekistan

 sh.kaxarov93@gmail.com

A MODEL OF RECOGNITION ALGORITHMS BASED ON THRESHOLD FUNCTIONS
FOR ASSESSING PROXIMITY OF OBJECTS

Abstract. A model of recognition algorithms for solving the problems of classifying the objects presented in a feature space of large dimensions is constructed. A new approach to developing such a model is proposed based on constructing a set of representative features and determining a suitable set of n/a three-dimensional threshold functions in the process of generating an extreme recognition algorithm. A structural description of the proposed model of recognition algorithms in the form of a sequence of computational procedures is given. Parameterization of these algorithms has been carried out, which makes it possible to set and solve the problem of determining an extreme recognition algorithm within the limits of the created model. The results of a comparative analysis of the proposed and known recognition algorithms are given.

Keywords: pattern recognition, model of recognition algorithms, algorithms for calculating estimates, subset of strongly related features, representative feature, three-dimensional threshold function.


full text

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