Modelling self-similar parabolic pulses in optical fibres with a neural network


We expand our previous analysis of nonlinear pulse shaping in optical fibres using machine learning [Opt. Laser Technol., 131 (2020) 106439] to the case of pulse propagation in the presence of gain/loss, with a special focus on the generation of self-similar parabolic pulses. We use a supervised feedforward neural network paradigm to solve the direct and inverse problems relating to the pulse shaping, bypassing the need for direct numerical solution of the governing propagation model.

Publication DOI:
Divisions: College of Engineering & Physical Sciences > Aston Institute of Photonics Technology (AIPT)
Additional Information: Creative Commons Attribution 4.0 International (CC BY 4.0)
Publication ISSN: 2666-9501
Last Modified: 20 May 2024 07:36
Date Deposited: 19 Feb 2021 10:56
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Related URLs: https://www.sci ... 0146?via%3Dihub (Publisher URL)
PURE Output Type: Article
Published Date: 2021-05
Published Online Date: 2021-02-16
Accepted Date: 2021-02-11
Authors: Boscolo, Sonia (ORCID Profile 0000-0001-5388-2893)
Dudley, John M.
Finot, Christophe



Version: Accepted Version

License: Creative Commons Attribution

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