Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
Scheme of Signal Processing in a Multimode Communication Receiver Based on Convolutional Neural Networks. / Sidelnikov, O. S.; Redyuk, A. A.; Fedoruk, M. P.
в: Bulletin of the Lebedev Physics Institute, Том 50, 09.2023, стр. S336-S342.Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
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TY - JOUR
T1 - Scheme of Signal Processing in a Multimode Communication Receiver Based on Convolutional Neural Networks
AU - Sidelnikov, O. S.
AU - Redyuk, A. A.
AU - Fedoruk, M. P.
N1 - The work of M.P. Fedoruk (theoretical analysis) was supported by the Russian Science Foundation (grant no. 20-11-20040). The work of O.S. Sidelnikov (mathematical modeling) was supported by the State Assignment for Fundamental Research, no. FSUS-2020-0034.
PY - 2023/9
Y1 - 2023/9
N2 - A scheme for optical signal processing in a multimode communication receiver based on deep convolutional neural networks and simulating the digital back propagation algorithm is proposed. For this scheme, the effectiveness of compensation for nonlinear intramode and intermode distortions is evaluated.
AB - A scheme for optical signal processing in a multimode communication receiver based on deep convolutional neural networks and simulating the digital back propagation algorithm is proposed. For this scheme, the effectiveness of compensation for nonlinear intramode and intermode distortions is evaluated.
KW - convolutional neural networks
KW - fiber optic communication systems
KW - multimode fiber
KW - nonlinearity compensation
KW - optical fiber nonlinearity
UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85169926771&origin=inward&txGid=44a8387dddfd56f7da5e98b607e68648
UR - https://www.mendeley.com/catalogue/ab2341fd-7009-315e-8afe-4c6b12988f7c/
U2 - 10.3103/S1068335623150150
DO - 10.3103/S1068335623150150
M3 - Article
VL - 50
SP - S336-S342
JO - Bulletin of the Lebedev Physics Institute
JF - Bulletin of the Lebedev Physics Institute
SN - 1068-3356
ER -
ID: 55558708