KFU. Card publication. Muscle tone control system based on LIF model neural network

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

MUSCLE TONE CONTROL SYSTEM BASED ON LIF MODEL NEURAL NETWORK

Form of presentation

Articles in international journals and collections

Year of publication

2022

Язык

английский

Authors, employees of KFU

Baltina Tatyana Valerevna, author

Sachenkov Oskar Aleksandrovich, author

Kharin Nikita Vyacheslavovich, author

Authors, postgraduates KFU

Kharin Nikita Vyacheslavovich, postgraduate kfu

Authors, students KFU

Ivanova Anastasiya Denisovna, author

Bibliographic description in the original language

Ivanova A. Muscle tone control system based on LIF model neural network/A. Ivanova, N. Kharin, T. Baltina and O. Sachenkov. IEEE Xplore: VIII International Conference on Information Technology and Nanotechnology (ITNT), 2022. - P. 1-4, doi: 10.1109/ITNT55410.2022.9848650.

Annotation

The article describes the solution to the control problem using machine learning. The article presents a model to simulate muscle tone. Based on spiking neural network control system was designed. The task of the neural network was to find a control function to maintain the muscle length. A LIF model of a spiking neural network was used. Excitatory signal was produced by muscle activity. Inhibitor signal was produced by motor neuron activity. Numerical simulations were performed and analyzed. A critical value of synapse weight was found. This value can be understood as a bifurcation parameter of the dynamic system.

Keywords

spiking neural network, control system, mathematical model, artificial neural network

The name of the journal

2022 8th International Conference on Information Technology and Nanotechnology, ITNT 2022

URL

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137846165&doi=10.1109%2fITNT55410.2022.9848650&partnerID=40&md5=b73e7726b7af2603344b322f2ccdab56

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=271201&p_lang=2

Resource files

File name	Size (MB)	Format
Muscle_tone_control_system_based_on_LIF_model_neural_network.pdf	3,68	pdf	show / download

Full metadata record

Field DC	Value	Language
dc.contributor.author	Baltina Tatyana Valerevna	ru_RU
dc.contributor.author	Sachenkov Oskar Aleksandrovich	ru_RU
dc.contributor.author	Kharin Nikita Vyacheslavovich	ru_RU
dc.contributor.author	Ivanova Anastasiya Denisovna	ru_RU
dc.contributor.author	Kharin Nikita Vyacheslavovich	ru_RU
dc.date.accessioned	2022-01-01T00:00:00Z	ru_RU
dc.date.available	2022-01-01T00:00:00Z	ru_RU
dc.date.issued	2022	ru_RU
dc.identifier.citation	Ivanova A. Muscle tone control system based on LIF model neural network/A. Ivanova, N. Kharin, T. Baltina and O. Sachenkov. IEEE Xplore: VIII International Conference on Information Technology and Nanotechnology (ITNT), 2022. - P. 1-4, doi: 10.1109/ITNT55410.2022.9848650.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=271201&p_lang=2	ru_RU
dc.description.abstract	2022 8th International Conference on Information Technology and Nanotechnology, ITNT 2022	ru_RU
dc.description.abstract	The article describes the solution to the control problem using machine learning. The article presents a model to simulate muscle tone. Based on spiking neural network control system was designed. The task of the neural network was to find a control function to maintain the muscle length. A LIF model of a spiking neural network was used. Excitatory signal was produced by muscle activity. Inhibitor signal was produced by motor neuron activity. Numerical simulations were performed and analyzed. A critical value of synapse weight was found. This value can be understood as a bifurcation parameter of the dynamic system.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	spiking neural network	ru_RU
dc.subject	control system	ru_RU
dc.subject	mathematical model	ru_RU
dc.subject	artificial neural network	ru_RU
dc.title	Muscle tone control system based on LIF model neural network	ru_RU
dc.type	Articles in international journals and collections	ru_RU