TY - GEN
T1 - Noise-Resistant Crowd Equalisation for Optical Communication Systems Based on Machine Learning
AU - Nurlybayeva, Karina
AU - Ron, Diego Argüello
AU - Kamalian-Kopae, Morteza
AU - Turitsyna, Elena
AU - Turitsyn, Sergei
PY - 2022
Y1 - 2022
N2 - We propose a solution to noisy neural networks employed in future optical communication systems. The proposed approach includes breaking down large networks into smaller ones and forming”crowds” using these elementary networks.
AB - We propose a solution to noisy neural networks employed in future optical communication systems. The proposed approach includes breaking down large networks into smaller ones and forming”crowds” using these elementary networks.
UR - http://www.scopus.com/inward/record.url?scp=85146757464&partnerID=8YFLogxK
UR - https://opg.optica.org/abstract.cfm?uri=FiO-2022-FM3D.2
U2 - 10.1364/FIO.2022.FM3D.2
DO - 10.1364/FIO.2022.FM3D.2
M3 - Conference publication
AN - SCOPUS:85146757464
T3 - Optics InfoBase Conference Papers
BT - Frontiers in Optics, FiO 2022
T2 - Frontiers in Optics, FiO 2022
Y2 - 17 October 2022 through 20 October 2022
ER -