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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
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.
Received: 16.10.2017
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
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