Conditions of the correctness for the algebra of estimates calculation algorithms with μ-operators over a set of binary-data recognition problems

This paper is aimed to show that specialized neural networks can be useful for finding exact solutions of the recognition problems involving binary data. For this purpose, as an original subclass, we take the subclass of estimates calculation algorithms (ECAs) in which all algorithms correspond to t...

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Veröffentlicht in:Pattern recognition and image analysis Jg. 27; H. 2; S. 166 - 174
Hauptverfasser: Dyusembaev, A. E., Grishko, M. V.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Moscow Pleiades Publishing 01.04.2017
Schlagworte:
Computer Science
Image Processing and Computer Vision
Mathematical Method in Pattern Recognition
Pattern Recognition
correctness
algebra
μ-block
estimates calculation algorithm
neural network
ISSN:1054-6618, 1555-6212
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Zusammenfassung:This paper is aimed to show that specialized neural networks can be useful for finding exact solutions of the recognition problems involving binary data. For this purpose, as an original subclass, we take the subclass of estimates calculation algorithms (ECAs) in which all algorithms correspond to three-level multilayer neural networks (μ-blocks). The correctness conditions are defined that allow a correct algorithm to be constructed in the algebra over this ECA subclass for each Ω-regular recognition problem. This approach does not require additional constraints, except for a trivial one, on the system of ECA support sets.
ISSN:1054-6618
1555-6212
DOI:10.1134/S1054661817020043