71221

Автор(ы): 

Автор(ов): 

3

Параметры публикации

Тип публикации: 

Доклад

Название: 

New Algorithms of Generation of Mathematical Models of Electroencephalogram Signals

ISBN/ISSN: 

978-1-6654-9702-2

DOI: 

10.1109/MLSD55143.2022.9934604

Наименование конференции: 

  • 2022 15th International Conference Management of large-scale system development (MLSD)

Наименование источника: 

  • Proceedings of the 15th International Conference Management of Large-Scale System Development (MLSD)

Город: 

  • Москва

Издательство: 

  • IEEE

Год издания: 

2022

Страницы: 

https://ieeexplore.ieee.org/document/9934604
Аннотация
In this paper we propose new approaches to the control of mathematical models of electroencephalogram signals, and also discuss ways to adjust their parameters. The developed models are based on the simulation of postsynaptic impulses using a combination of Gaussians with random amplitudes and mean values. The width parameter is estimated by calculating the convolution of the electroencephalogram signal with the Gaussian and subsequent statistical analysis of the results. The adequacy of the resulting model was verified using neural networks, random forest, and method of expert assessments.

Библиографическая ссылка: 

Туровский Я.А., Киселев Е.А., Борзунов С.В. New Algorithms of Generation of Mathematical Models of Electroencephalogram Signals / Proceedings of the 15th International Conference Management of Large-Scale System Development (MLSD). М.: IEEE, 2022. С. https://ieeexplore.ieee.org/document/9934604.