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Kvantovaya Elektronika, 2017, Volume 47, Number 12, Pages 1147–1149 (Mi qe16728)  

This article is cited in 8 scientific papers (total in 8 papers)

Special Issue 'Optical Fibres and Their Applications'

Dynamic neural network-based methods for compensation of nonlinear effects in multimode communication lines

O. S. Sidelnikovab, A. A. Redyukab, S. Sygletosc

a Novosibirsk State University
b Institute of Computational Technologies, Siberian Branch of the Russian Academy of Sciences, Novosibirsk
c Aston University, England
Full-text PDF (595 kB) Citations (8)
References:
Abstract: We consider neural network-based schemes of digital signal processing. It is shown that the use of a dynamic neural network-based scheme of signal processing ensures an increase in the optical signal transmission quality in comparison with that provided by other methods for nonlinear distortion compensation.
Keywords: optical fibre, nonlinear effects, neural networks, mathematical modelling.
Funding agency Grant number
Russian Science Foundation 17-72-30006
Received: 16.10.2017
English version:
Quantum Electronics, 2017, Volume 47, Issue 12, Pages 1147–1149
DOI: https://doi.org/10.1070/QEL16535
Bibliographic databases:
Document Type: Article
Language: Russian


Citation: O. S. Sidelnikov, A. A. Redyuk, S. Sygletos, “Dynamic neural network-based methods for compensation of nonlinear effects in multimode communication lines”, Kvantovaya Elektronika, 47:12 (2017), 1147–1149 [Quantum Electron., 47:12 (2017), 1147–1149]
Linking options:
  • https://www.mathnet.ru/eng/qe16728
  • https://www.mathnet.ru/eng/qe/v47/i12/p1147
  • This publication is cited in the following 8 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Квантовая электроника Quantum Electronics
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    Abstract page:240
    Full-text PDF :87
    References:30
    First page:15
     
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