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Application of neural networks to determine the discrete spectrum of the direct Zakharov - Shabat problem. / Sedov, E. V.; Chekhovskoy, I. S.; Prilepsky, J. E. et al.

In: Quantum Electronics, Vol. 50, No. 12, 12.2020, p. 1105-1109.

Research output: Contribution to journal › Article › peer-review

Harvard

Sedov, EV, Chekhovskoy, IS, Prilepsky, JE & Fedoruk, MP 2020, 'Application of neural networks to determine the discrete spectrum of the direct Zakharov - Shabat problem', Quantum Electronics, vol. 50, no. 12, pp. 1105-1109. https://doi.org/10.1070/QEL17463

APA

Sedov, E. V., Chekhovskoy, I. S., Prilepsky, J. E., & Fedoruk, M. P. (2020). Application of neural networks to determine the discrete spectrum of the direct Zakharov - Shabat problem. Quantum Electronics, 50(12), 1105-1109. https://doi.org/10.1070/QEL17463

Vancouver

Sedov EV, Chekhovskoy IS, Prilepsky JE, Fedoruk MP. Application of neural networks to determine the discrete spectrum of the direct Zakharov - Shabat problem. Quantum Electronics. 2020 Dec;50(12):1105-1109. doi: 10.1070/QEL17463

Author

Sedov, E. V. ; Chekhovskoy, I. S. ; Prilepsky, J. E. et al. / Application of neural networks to determine the discrete spectrum of the direct Zakharov - Shabat problem. In: Quantum Electronics. 2020 ; Vol. 50, No. 12. pp. 1105-1109.

BibTeX

@article{1ee36bf2638845c3b296e43b84f23f37,
title = "Application of neural networks to determine the discrete spectrum of the direct Zakharov - Shabat problem",
abstract = "A neural network architecture is proposed to determine the number of solitons generated by random processes in optical wavelength-division multiplexed telecommunication systems with QPSK, 16-QAM, 64-QAM, and 1024-QAM modulation. The dependence of the prediction quality of a neural network with a special architecture on the number of soliton modes in the signal and the parameters of this signal is studied. ",
keywords = "inverse scattering problem method, machine learning, neural networks, nonlinear Fourier transform, nonlinear Schr{\"o}dinger equation, optical telecommunication systems, wavelength-division multiplexing, Zakharov - Shabat problem",
author = "Sedov, {E. V.} and Chekhovskoy, {I. S.} and Prilepsky, {J. E.} and Fedoruk, {M. P.}",
note = "Funding Information: The work was supported by the Fund of the President of the Russian Federation for State Support of Young Russian Scientists (Grant No. MK-677.2020.9). The work of I.S. Chekhovskoy was supported by the state assignment for fundamental research (FSUS-2020-0034), and the work of J.E. Prilepsky was supported by the Leverhulme Trust (Project RPG-2018-063). Publisher Copyright: {\textcopyright} 2020 Kvantovaya Elektronika, Turpion Ltd and IOP Publishing Ltd. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.",
year = "2020",
month = dec,
doi = "10.1070/QEL17463",
language = "English",
volume = "50",
pages = "1105--1109",
journal = "Quantum Electronics",
issn = "1063-7818",
publisher = "Turpion Ltd.",
number = "12",

}

RIS

TY - JOUR

T1 - Application of neural networks to determine the discrete spectrum of the direct Zakharov - Shabat problem

AU - Sedov, E. V.

AU - Chekhovskoy, I. S.

AU - Prilepsky, J. E.

AU - Fedoruk, M. P.

N1 - Funding Information: The work was supported by the Fund of the President of the Russian Federation for State Support of Young Russian Scientists (Grant No. MK-677.2020.9). The work of I.S. Chekhovskoy was supported by the state assignment for fundamental research (FSUS-2020-0034), and the work of J.E. Prilepsky was supported by the Leverhulme Trust (Project RPG-2018-063). Publisher Copyright: © 2020 Kvantovaya Elektronika, Turpion Ltd and IOP Publishing Ltd. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020/12

Y1 - 2020/12

N2 - A neural network architecture is proposed to determine the number of solitons generated by random processes in optical wavelength-division multiplexed telecommunication systems with QPSK, 16-QAM, 64-QAM, and 1024-QAM modulation. The dependence of the prediction quality of a neural network with a special architecture on the number of soliton modes in the signal and the parameters of this signal is studied.

AB - A neural network architecture is proposed to determine the number of solitons generated by random processes in optical wavelength-division multiplexed telecommunication systems with QPSK, 16-QAM, 64-QAM, and 1024-QAM modulation. The dependence of the prediction quality of a neural network with a special architecture on the number of soliton modes in the signal and the parameters of this signal is studied.

KW - inverse scattering problem method

KW - machine learning

KW - neural networks

KW - nonlinear Fourier transform

KW - nonlinear Schrödinger equation

KW - optical telecommunication systems

KW - wavelength-division multiplexing

KW - Zakharov - Shabat problem

UR - http://www.scopus.com/inward/record.url?scp=85098275474&partnerID=8YFLogxK

U2 - 10.1070/QEL17463

DO - 10.1070/QEL17463

M3 - Article

AN - SCOPUS:85098275474

VL - 50

SP - 1105

EP - 1109

JO - Quantum Electronics

JF - Quantum Electronics

SN - 1063-7818

IS - 12

ER -

ID: 27296719