Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
Conferences > SELED > 2023 > JTu4A > JTu4A.27

Adaptive neural-network-metric based workflow for mode decomposition in multimode optical fibers

Roman A. Rudamenko, Emil A. Milikov, Viacheslav V. Zemlyakov, and Jiexing Gao

Not Accessible

Your library or personal account may give you access

Abstract

Multimode fibers can be employed for mode division multiplexed communication systems with the paradigm of multiple-input multiple-output. Revealing individual modal components at the receiver side can be completed via computer vision(CV) approaches. The fully neural-network-based workflow implemented in experiment.

© 2023 The Author(s)

PDF Article
More Like This
Deep Learning Network-based Optical Vector-Eigenmode Decomposition for Mode-Division Multiplexing Links

JianJun Li, Rui Zhang, Feng Yang, and Feng Wen
FD4.2 Frontiers in Optics (FiO) 2023

Microring-based programmable coherent optical neural networks

Jiahui Wang, Sean P. Rodrigues, Ercan M. Dede, and Shanhui Fan
SM4J.3 CLEO: Science and Innovations (CLEO:S&I) 2023

Image Sensors Based on Nonlinear Optical Neural Networks

Mandar M. Sohoni, Tianyu Wang, Logan G. Wright, Martin M. Stein, Shi-Yuan Ma, Tatsuhiro Onodera, Maxwell G. Anderson, and Peter L. McMahon
STu4F.3 CLEO: Science and Innovations (CLEO:S&I) 2023

View More...
Select as filters
Select Topics Cancel
Top
       
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.
Privacy | Terms of Use