Literature DB >> 29856442

Turbulence correction with artificial neural networks.

Sanjaya Lohani, Ryan T Glasser.   

Abstract

We design an optical feedback network making use of machine learning (ML) techniques and demonstrate via simulations its ability to correct for the effects of turbulent propagation on optical modes. This artificial neural network scheme relies only on measuring the intensity profile of the distorted modes, making the approach simple and robust. The network results in the generation of various mode profiles at the transmitter that, after propagation through turbulence, closely resemble the desired target mode. The corrected optical mode profiles at the receiver are found to be nearly identical to the desired profiles, with near-zero mean square error indices. We are hopeful that the present results combining the fields of ML and optical communications will greatly enhance the robustness of free-space optical links.

Entities:  

Year:  2018        PMID: 29856442     DOI: 10.1364/OL.43.002611

Source DB:  PubMed          Journal:  Opt Lett        ISSN: 0146-9592            Impact factor:   3.776


  4 in total

1.  Deep-learning-based high-resolution recognition of fractional-spatial-mode-encoded data for free-space optical communications.

Authors:  Youngbin Na; Do-Kyeong Ko
Journal:  Sci Rep       Date:  2021-01-29       Impact factor: 4.379

2.  Compensation-free high-dimensional free-space optical communication using turbulence-resilient vector beams.

Authors:  Ziyi Zhu; Molly Janasik; Alexander Fyffe; Darrick Hay; Yiyu Zhou; Brian Kantor; Taylor Winder; Robert W Boyd; Gerd Leuchs; Zhimin Shi
Journal:  Nat Commun       Date:  2021-03-12       Impact factor: 14.919

3.  Index Evaluation of Different Hospital Management Modes Based on Deep Learning Model.

Authors:  Jinai Li; Yan Wang
Journal:  Comput Intell Neurosci       Date:  2022-04-27

4.  Adaptive demodulation by deep-learning-based identification of fractional orbital angular momentum modes with structural distortion due to atmospheric turbulence.

Authors:  Youngbin Na; Do-Kyeong Ko
Journal:  Sci Rep       Date:  2021-12-06       Impact factor: 4.379

  4 in total

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