Journal of Radio Electronics. eISSN 1684-1719. 2026. №4
Full text in Russian (pdf)
DOI: https://doi.org/10.30898/1684-1719.2026.4.3
NEURAL NETWORK Simulation OF ELECTROMAGNETIC
RADIATION FROM electronic COMPUTING DEVICES
Z.M. Gizatullin, I.D. Fatykhov, R.S. Nurtdinov
Kazan National Research Technical University
named after A.N. Tupolev-KAI,
420111, Russia, Kazan, Karl Marx str., 10
The paper was received March 03, 2026.
Abstract. The relevance of research electromagnetic radiation from electronic computing devices is dictated by aspects of biological safety, information security, and electromagnetic compatibility. The use of artificial neural networks to study electromagnetic radiation represents a transition from classical deterministic models to data mining, which has certain advantages over analytical approaches and physical measurements. The practical technique for constructing a nonlinear approximating function of electromagnetic radiation from electronic computing devices using neural network simulation based on physical measurement data at discrete frequencies this article proposes. Personal computers are considered as electronic computing devices. To demonstrate the feasibility of using this tool, a test experimental setup for preparing training and test data was created. The mean absolute percentage error is used to evaluate the quality of the problem solution for the test set. Training was performed over 220 epochs, and the mean absolute percentage error for the test set was 22%. Examples of predicting electromagnetic radiation intensity using a trained neural network are provided. The obtained results demonstrate the capabilities of neural network simulation in solving electromagnetic compatibility problems.
Key words: artificial neural network, electromagnetic radiation, electronic computing device, experiment, training, simulation.
Financing: the study was conducted under the state assignment of the Ministry of Science and Higher Education FZSU-2026-0007 (R&D registration No. 126020516513-4)
Corresponding author: Gizatullin Zinnur Marselevich, gzm_zinnur@mail.ru
References
1. Myrova L. O., Grachev N. N., Nikitina V. N. Vliyanie opasnykh izluchenii na cheloveka [The influence of hazardous radiation on humans]. M.: OOO Vizavi, 2017. (In Russian)
2. Keller R. B. Design for Electromagnetic Compatibility-In a Nutshell: Theory and Practice. Springer Nature, 2023.
3. Gizatullin Z. M., Shlejmovich M. P. Research of the Radiated Electromagnetic Interference from Power Devices of the Aircraft under Modernization // Russian Aeronautics. 2023. №. 3. S. 596-604.
4. Nuriev M. G., Gizatullin R. M., Gizatullin Z. M. Physical modeling of electromagnetic interferences in the unmanned aerial vehicle in the case of high-voltage transmission line impact // Russian Aeronautics. 2018. №. 2. S. 293-298.
5. Kalyashina A. V., Fatkullina L. F. Matematicheskoe modelirovanie protsessa obrabotki zashumlennykh signalov [Mathematical modeling of the process of processing noisy signals] // Nauchno-tekhnicheskii vestnik Povolzh'ya. 2023. №. 6. S. 65-68.
6. Gataullin B. I., Khaerova E. I., Tumbinskaya M. V. Razrabotka trenazhera dlya virtual'noi laboratorii inzhenerno-tekhnicheskoi zashchity informatsii [Development of a simulator for a virtual laboratory of engineering and technical information security] // Pravovaya informatika. 2025. №. 4. S. 46-53. - https://doi.org/10.24412/1994-1404-2025-4-46-53 (In Russian)
7. Sharipov R. R., Khalimov A. Z., Perukhin M. YU. Razrabotka programmno-laboratornogo kompleksa dlya izucheniya kriptografii na ehllipticheskikh krivykh [Development of a software and laboratory complex for studying cryptography on elliptic curves] // Computational Nanotechnology. 2025. Т. 12, №. 4. S. 71-80. https://doi.org/10.33693/2313-223X-2025-12-4-71-80 (In Russian)
8. Sharipov R. R., Katasev A. S. Analiz klaviaturnogo pocherka pol'zovatelei infokommunikatsionnykh sistem na osnove poligaussovogo algoritma [Analysis of keyboard handwriting of users of infocommunication systems based on the polygaussian algorithm] // Informatsiya i bezopasnost'. 2016. Т. 19, №. 4. S. 587-590. (In Russian)
9. Brunton S. L., Kutz J. N. Data-driven science and engineering: Machine learning, dynamical systems, and control. Cambridge University Press, 2022.
10. Gizatullin Z. M., Fatykhov I. D., Nurtdinov R. S. Prognozirovanie pobochnogo ehlektromagnitnogo izlucheniya ot preobrazovatelya ehlektroehnergii s ispol'zovaniem iskusstvennoi neironnoi seti [Prediction of spurious electromagnetic emission from an electric power converter using an artificial neural network.] // Zhurnal radioehlektroniki. 2025. №. 8. https://doi.org/10.30898/1684-1719.2025.8.13 (In Russian)
11. Kuksenko S. P. and etc. Razrabotka programmnogo obespecheniya dlya modelirovaniya radioelektronnyh sredstv s uchetom elektromagnitnoj sovmestimosti v TUSUR [Development of software for modeling radio-electronic equipment taking into account electromagnetic compatibility at TUSUR] // Nanoindustriya. 2023. T. 16, № S9-1(119). S. 170-178. (In Russian)
12. Safina R. M. Zadacha Keldysha dlya uravneniya smeshannogo tipa s sil'nym kharakteristicheskim vyrozhdeniem i singulyarnym koehffitsientom [The Keldysh problem for a mixed-type equation with strong characteristic degeneration and a singular coefficient] // Izvestiya vysshikh uchebnykh zavedenii. Matematika. 2017. №. 8. S. 53-61. https://doi.org/10.3103/S1066369X17080059 (In Russian)
13. GOST R. 51318.22-99. Sovmestimost' tekhnicheskikh sredstv ehlektromagnitnaya. Radiopomekhi industrial'nye ot oborudovaniya informatsionnykh tekhnologii. Normy i metody ispytanii [Electromagnetic compatibility of technical equipment. Industrial radio interference from information technology equipment. Standards and test methods] // M.: Izd-vo standartov. 2001. (In Russian)
14. Gizatullin Z. M. i dr. Prostaya metodika issledovaniya elektromagnitnogo izlucheniya ot elektronnyh sredstv [A simple method for studying electromagnetic radiation from electronic devices] //ZHurnal radioelektroniki. 2016. №. 9. S. 7-7. (In Russian)
15. Gizatullin Z. M. i dr. Metod obnaruzheniya konturov na osnove vesovoi modeli izobrazheniya [Contour detection method based on a weighted image model] //Komp'yuternaya optika. 2020. T. 44. №. 3. S. 393-400. https://doi.org/10.18287/2412-6179-CO-615 (In Russian)
16. Gizatullin Z. M. i dr. Povyshenie ustojchivosti detektora konturov Kenni k vozdejstviyu pomekh [Increasing the stability of the Canny contour detector to interference] //Nauchno-tekhnicheskij vestnik Povolzh'ya. 2023. №. 7. S. 25-28. (In Russian)
17. Andreyanov N. V., Sytnik A. S., Shleimovich M. P. Programmno-apparatnyi kompleks dlya obnaruzheniya obektov na izobrazheniyakh v intellektual'noi transportnoi sisteme dlya sel'khoztekhniki [Software and hardware complex for detecting objects in images in an intelligent transport system for agricultural machinery] // Vestnik NTSBZHD. 2021. №. 4(50). S. 14-24. (In Russian)
18. Lyasheva M. M. i dr. Metod szhatiya izobrazhenii na osnove analiza vesov detaliziruyushchikh koehffitsientov veivlet-preobrazovaniya [Image compression method based on the analysis of the weights of detailing coefficients of the wavelet transform] //Inzhenernyi vestnik Dona. 2024. №. 10 (118). S. 230-238. (In Russian)
19. Luo M., Huang K. M. Prediction of the electromagnetic field in metallic enclosures using artificial neural networks // Progress In Electromagnetics Research. 2011. Т. 116. S. 171-184. https://doi.org/10.2528/PIER11031101
20. Khadse C. B., Chaudhari M. A., Borghate V. B. Electromagnetic compatibility estimator using scaled conjugate gradient backpropagation based artificial neural network //IEEE Transactions on Industrial Informatics. 2016. Т. 13. №. 3. S. 1036-1045. – https://doi.org/10.1109/TII.2016.2605623
21. Evdokimova T. S., Shleimovich M. P. Otsenka ehffektivnosti metoda rasshireniya naborov dannykh na osnove glubokogo obucheniya s podkrepleniem [Evaluation of the efficiency of the method for expanding data sets based on deep reinforcement learning] //Inzhenernyi vestnik Dona. 2025. №. 2 (122). S. 232-241. (In Russian)
22. Gizatullin Z.M. Tekhnologiya prognozirovaniya i povysheniya ehlektromagnitnoi sovmestimosti tsifrovykh ehlektronnykh sredstv pri vneshnikh vysokochastotnykh impul'snykh ehlektromagnitnykh vozdeistviyakh [Technology of forecasting and increasing electromagnetic compatibility of digital electronic devices under external high-frequency pulsed electromagnetic influences] // Tekhnologii ehlektromagnitnoi sovmestimosti. 2010. №. 3(34). S. 22-29. (In Russian)
23. Kvasnikov A. A., Kuksenko S. P. Obzor ekspertnyh sistem po elektromagnitnoj sovmestimosti tekhnicheskih sredstv [Review of expert systems for electromagnetic compatibility of technical means] //Doklady Tomskogo gosudarstvennogo universiteta sistem upravleniya i radioelektroniki. 2021. Т. 24. №. 4. S. 7-18. https://doi.org/10.21293/1818-0442-2021-24-4-7-18 (In Russian)
24. Safina R. M., Shkinderov M. S., Mubarakov R. R. Pomekhoustojchivost' sistem kontrolya i upravleniya dostupom v zdaniya pri vozdejstvii elektromagnitnyh pomekh po seti elektropitaniya [Noise immunity of control and management systems for access to buildings under the influence of electromagnetic interference through the power supply network] //Zhurnal radioehlektroniki. 2021. №. 6. https://doi.org/10.30898/1684-1719.2021.6.9 (In Russian)
25. Gizatullin Z. M., Gizatullin R. M. Analiz kachestva ehlektroehnergii v odnofaznoi seti ehlektropitaniya 220 Vol't 50 Gerts [Analysis of the quality of electric power in a single-phase power supply network 220 Volt 50 Hz] //Izvestiya vysshikh uchebnykh zavedenii. Problemy ehnergetiki. 2012. №. 7-8. S. 63-71.
For citation:
Gizatullin Z.M., Fatykhov I.D., Nurtdinov R.S. Neural network simulation of electromagnetic radiation from electronic computing devices. // Journal of Radio Electronics. – 2026. – № 4. https://doi.org/10.30898/1684-1719.2026.4.3 (In Russian)