Noise-Resistant Crowd Equalisation for Optical Communication Systems Based on Machine Learning

Karina Nurlybayeva, Diego Argüello Ron*, Morteza Kamalian-Kopae, Elena Turitsyna, Sergei Turitsyn

*Corresponding author for this work

Research output: Chapter in Book/Published conference outputConference publication

Abstract

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.

Original languageEnglish
Title of host publicationFrontiers in Optics, FiO 2022
ISBN (Electronic)9781557528209
DOIs
Publication statusPublished - 2022
EventFrontiers in Optics, FiO 2022 - Rochester, United States
Duration: 17 Oct 202220 Oct 2022

Publication series

NameOptics InfoBase Conference Papers

Conference

ConferenceFrontiers in Optics, FiO 2022
Country/TerritoryUnited States
CityRochester
Period17/10/2220/10/22

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