@inproceedings{8cd26e08fff84b11896f1eadd73bb922,
title = "Computing continuous nonlinear fourier spectrum of optical signal with artificial neural networks",
abstract = "We propose the artificial neural network architecture that can efficiently perform the nonlinear Fourier optical signal processing. The performance of the new method is analysed considering the error between the precomputed and predicted nonlinear spectra.",
author = "Egor Sedov and Jaroslaw Prilepsky and Igor Chekhovskoy and Sergei Turitsyn",
note = "Funding Information: This work was supported by the RSF grant 17-72-30006 (ES, ST), by the grant of the President of the RF MK-677.2020.9 (IC), by the EPSRC grant TRANSNET (ES, ST), Leverhulme Trust project RPG-2018-063 (JP, SK). References [1] V. Zakharov and A. Shabat, “Exact theory of two-dimensional self-focusing and one-dimensional self-modulation of waves in nonlinear media,” Sov. Phys. JETP 34, 62–69 (1972). [2] S. K. Turitsyn, et al. “Nonlinear Fourier transform for optical data processing and transmission: advances and perspectives,” Optica 4, 307–322 (2017). [3] S. Turitsyn, E. Sedov, A. Redyuk, and M. Fedoruk, “Nonlinear spectrum of conventional OFDM and WDM return-to-zero signals in nonlinear channel,” J. Light. Technol. 38, 352–358 (2019).; 2021 European Quantum Electronics Conference, EQEC 2021 - Part of 2021 Conference on Lasers and Electro-Optics Europe, CLEO 2021 ; Conference date: 21-06-2021 Through 25-06-2021",
year = "2021",
language = "English",
series = "Optics InfoBase Conference Papers",
publisher = "The Optical Society",
booktitle = "European Quantum Electronics Conference, EQEC 2021",
address = "United States",
}