BUILDING OF RECOGNITION OPERATORS IN CONDITION OF FEATURES’ CORRELATIONS
Науковий журнал «Радіоелектроніка, інформатика, управління»
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BUILDING OF RECOGNITION OPERATORS IN CONDITION OF FEATURES’ CORRELATIONS |
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Fazilov, Sh. Kh.; Tashkent University of information technologies, Tashkent, Uzbekistan Mirzaev, N. M.; Tashkent University of information technologies, Tashkent, Uzbekistan Mirzaev, O. N.; Tashkent University of information technologies, Tashkent, Uzbekistan |
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pattern recognition, model of recognition operators, potential function, features’ correlations, subset of strongly correlated features, representative feature, preferred correlation model. |
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The problem of recognizing of patterns given in the space of correlated features is considered. The new approach to the building of model<br />of recognition operators, which considers the correlation of given features, is proposed. The building of the model is carried out for potential<br />function type recognition operators. The main idea of the proposed approach is formation of uncorrelated subsets of strongly correlated<br />features and extracting preferred correlation model for each of subsets of strongly correlated features. Analysis of the results shows that the<br />considered recognition operators are used in cases when there is a certain correlation between objects belonging to the same class. When the<br />expression of this relationship is weak, classical model of recognition operators is used. The main advantage of the proposed recognition<br />operators is to improve the accuracy and the significant reduction in the volume of computational operations in recognition of unknown<br />objects, which allows them to use when building recognition systems working in real time. |
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Zaporizhzhya National Technical University 2016-04-15 00:00:00 |
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application/pdf http://ric.zntu.edu.ua/article/view/66502 |
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Radio Electronics, Computer Science, Control; No 1 (2016): Radio Electronics, Computer Science, Control |
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ru |
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Copyright (c) 2016 Sh. Kh. Fazilov, N. M. Mirzaev, O. N. Mirzaev |
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