"JOURNAL OF RADIO ELECTRONICS" (Zhurnal Radioelektroniki ISSN 1684-1719, N 10, 2018

contents of issue      DOI  10.30898/1684-1719.2018.10.4     full text in Russian (pdf)  

Method for recognizing the shape of objects of domain structures in magneto-optical materials based on direct-propagation neural networks


A. V. Bragin, M. V. Gerasimov, R. R. Navletov, D. V. Pyanzin

National Research Mordovia State University, Bolshevistskaya str. 68, Saransk 430005, Russia


The paper is received on September 30, 2018


Abstract. The article proposes a method for recognizing objects in the labyrinth domain structures of magneto-optical materials and classification using a neural network. Domain structure objects come in a variety of forms. The authors have compiled a classification of types of domain structures on the basis of practical results and a literature review. The features of domain classification that significantly affect the choice of methods and algorithms for solving problems are considered.

The classification is based on the analysis of six coefficients of object shape by two neural networks. The structures of neural networks and learning results are presented.

This method allows recogning nine types of domains with simple and complex shapes and can be used for analyzing images of objects in electronics, physics, chemistry, biology, medicine similar in form with domains.

An example of object image recognition in magneto-optical materials is presented. This method of recognition is implemented in the software.

The developed software is used at the Department of radio engineering of the Moscow state University. N. P. Ogareva", for the study of magneto-optical and semiconductor materials.

Keywords: neural network, object recognition, classification, domains, magneto-optical materials.


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For citation:

A. V. Bragin, M. V. Gerasimov, R. R. Navletov, D. V. Pyanzin.  Method for recognizing the shape of objects of domain structures in magneto-optical materials based on direct-propagation neural networks. Zhurnal Radioelektroniki - Journal of Radio Electronics. 2018. No. 10. Available at http://jre.cplire.ru/jre/oct18/4/text.pdf

DOI  10.30898/1684-1719.2018.10.4