NEUROBIOLOGICAL PROPERTIES OF THE STRUCTURE OF THE PARALLEL-HIERARCHICAL NETWORK AND ITS USAGE FOR PATTERN RECOGNITION
Leonid Timchenko
tumchenko_li@gsuite.duit.edu.uaState University of Infrastructure and Technology (Ukraine)
https://orcid.org/0000-0001-5056-5913
Natalia Kokriatskaia
State University of Infrastructure and Technology (Ukraine)
https://orcid.org/0000-0001-8025-8172
Volodymyr Tverdomed
State University of Infrastructure and Technology (Ukraine)
Anatolii Horban
State University of Infrastructure and Technology (Ukraine)
Oleksandr Sobovyi
State University of Infrastructure and Technology (Ukraine)
https://orcid.org/0000-0002-6287-6193
Liudmyla Pogrebniak
Kruty Heroes Military Institute of Telecommunications and Information Technologies (Ukraine)
Nelia Burlaka
Vinnytsia Mykhailo Kotsiubynskyi State Pedagogical University (Ukraine)
Yurii Didenko
State University of Infrastructure and Technology (Ukraine)
Maksym Kozyr
State University of Infrastructure and Technology (Ukraine)
https://orcid.org/0009-0007-2564-6552
Ainur Kozbakova
Almaty Technological University, The Institute of Institute of Information and Computational Technologies CS MHES (Ukraine)
Abstract
The paper presents the analysis of neurobiological data on the existence of the structure of a parallel-hierarchical network. Discussed method of parallel-hierarchical transformation based on population coding and its application for the pattern recognition task. Based on the analysis, we can conclude that using the methods proposed, it is possible to measure the geometric parameters and properties of images, which can significantly increase the efficiency of processing, in particular estimating the center of mass based on moment characteristics. Experimental results demonstrate that due to various destabilizing factors, accurately measuring the energy center coordinates of laser beam spot images is challenging. However, training the PI network and classifying the fragments into "good" and "bad" can considerably enhance the accuracy of these measurements.
Keywords:
parallel-hierarchical network, population coding, pattern recognition task, laser, center of images, proceeding of imagesReferences
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Authors
Leonid Timchenkotumchenko_li@gsuite.duit.edu.ua
State University of Infrastructure and Technology Ukraine
https://orcid.org/0000-0001-5056-5913
Authors
Natalia KokriatskaiaState University of Infrastructure and Technology Ukraine
https://orcid.org/0000-0001-8025-8172
Authors
Volodymyr TverdomedState University of Infrastructure and Technology Ukraine
Authors
Anatolii HorbanState University of Infrastructure and Technology Ukraine
Authors
Oleksandr SobovyiState University of Infrastructure and Technology Ukraine
https://orcid.org/0000-0002-6287-6193
Authors
Liudmyla PogrebniakKruty Heroes Military Institute of Telecommunications and Information Technologies Ukraine
Authors
Nelia BurlakaVinnytsia Mykhailo Kotsiubynskyi State Pedagogical University Ukraine
Authors
Yurii DidenkoState University of Infrastructure and Technology Ukraine
Authors
Maksym KozyrState University of Infrastructure and Technology Ukraine
https://orcid.org/0009-0007-2564-6552
Authors
Ainur KozbakovaAlmaty Technological University, The Institute of Institute of Information and Computational Technologies CS MHES Ukraine
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