Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
Complex Fully Connected Neural Networks for Nonlinearity Compensation in Long-Haul Transmission Systems. / Bogdanov, Stepan; Sidelnikov, Oleg.
2021 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. (2021 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2021; Том 2021-January).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
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TY - GEN
T1 - Complex Fully Connected Neural Networks for Nonlinearity Compensation in Long-Haul Transmission Systems
AU - Bogdanov, Stepan
AU - Sidelnikov, Oleg
N1 - Funding Information: The work was supported by grant of the President of the Russian Federation (MK-915.2020.9). Publisher Copyright: © 2021 IEEE.
PY - 2021/6
Y1 - 2021/6
N2 - Signal nonlinear impairments have been one of the fundamental limiting factors for the further development of optical communication systems operating at broader bandwidth and longer distances. To tackle this problem, a number of techniques have been proposed. One of the promising approaches is the development of nonlinear equalizers (NLE) based on neural networks. Such equalizers provide high accuracy of symbol classification, requiring acceptable computational resources [1].
AB - Signal nonlinear impairments have been one of the fundamental limiting factors for the further development of optical communication systems operating at broader bandwidth and longer distances. To tackle this problem, a number of techniques have been proposed. One of the promising approaches is the development of nonlinear equalizers (NLE) based on neural networks. Such equalizers provide high accuracy of symbol classification, requiring acceptable computational resources [1].
UR - http://www.scopus.com/inward/record.url?scp=85121251004&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/b1ac3a09-d8f5-3c8d-8a31-c0f96a52cd11/
U2 - 10.1109/CLEO/Europe-EQEC52157.2021.9592658
DO - 10.1109/CLEO/Europe-EQEC52157.2021.9592658
M3 - Conference contribution
AN - SCOPUS:85121251004
SN - 9781665418768
T3 - 2021 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2021
BT - 2021 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2021
Y2 - 21 June 2021 through 25 June 2021
ER -
ID: 35029067