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

E. V. Sedov, I. S. Chekhovskoy*, J. E. Prilepsky, M. P. Fedoruk

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)1105-1109
Number of pages5
JournalQuantum Electronics
Volume50
Issue number12
DOIs
Publication statusPublished - 31 Dec 2020

Bibliographical 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).

Keywords

  • inverse scattering problem method
  • machine learning
  • neural networks
  • nonlinear Fourier transform
  • nonlinear Schrödinger equation
  • optical telecommunication systems
  • wavelength-division multiplexing
  • Zakharov - Shabat problem

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