Control Systems and Computers, N4, 2018, Article 1


Upr. sist. maš., 2018, Issue 4 (276), pp. 3-20.

UDC 004.8 + 004.032.26

Goltsev Alexander D., Doctor of Technical Sciences, head of the department, E-mail:,

Gritsenko Volodymyr I., Corresponding member of the Ukrainian academy of sciences, Director, E-mail:

International Research and Training Center for Information Technologies and Systems of the NAS and MES of Ukraine, Glushkov ave., 40, Kyiv, 03187, Ukraine

Neural Network Technologies in the Problem of Handwriting Recognition

Introduction the “Department of Neural Network Information Processing Technologies” of the “International Scientific and Educational Center for Information Technologies and Systems” is the heir to the “Department of Biological and Medical Cybernetics”, which was organized by Academician Amosov in 1962. Currently, the goal of research is to develop effective neural network information processing technologies based on computer simulation of the neural organization of the human brain and the mechanisms of its thinking. The developed neural network technologies are intended for the use in solving actual practical problems related to the field of Artificial Intelligence.

The purpose of the article is to describe some of the department’s work related to the field of image recognition and classification, in particular, the task of character image recognition.

Methods – basic definitions, recommendations and conclusions are based on the analysis of the results of own research.

Results – in the article, based on the results of a series of experiments comparing the LiRA classifier and the modular neural network, it is shown that the latest version of the modular neural network has a higher efficiency (recognition ability) than the LiRA classifier, although it is slightly inferior in speed.

Conclusion – the neurobiological relevance of the LiRA classifier and the modular neural network opens up the possibility of creating on their basis intelligent information technologies that function similarly to the human brain.

Download full text! (On Russian).

Keywords: neurons, neural layers, trained connections, LiRA-features, inhibitory connections.

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Received 22.10.18