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Pisma v Zhurnal Tekhnicheskoi Fiziki, 2019, Volume 45, Issue 4, Pages 6–7
DOI: https://doi.org/10.21883/PJTF.2019.04.47326.17587 (Mi pjtf5523) 		 
A method of helical wave front demultiplexing

D. A. Stankevich

Volgograd State University
Full-text PDF (70 kB)
DOI: https://doi.org/10.21883/PJTF.2019.04.47326.17587
Abstract: Machine learning methods were used to construct a demultiplexer for helical wave front separation into orthogonal modes. The accuracy of wave front demultiplexing into eight modes at a signal-to-noise ratio of –3 dB is about 95% in a broad range of signal carrier frequencies. For nonstationary parameters of signals, the proposed demultiplexer accuracy exceeds that of the classical correlation method.
Funding agency Grant number
Russian Science Foundation 18-79-00080
Received: 13.11.2018
Revised: 13.11.2018
Accepted: 19.11.2018
English version:
Technical Physics Letters, 2019, Volume 45, Issue 2, Pages 126–128
DOI: https://doi.org/10.1134/S1063785019020330
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: D. A. Stankevich, “A method of helical wave front demultiplexing”, Pisma v Zhurnal Tekhnicheskoi Fiziki, 45:4 (2019), 6–7; Tech. Phys. Lett., 45:2 (2019), 126–128
Citation in format AMSBIB
\Bibitem{Sta19}
\by D.~A.~Stankevich
\paper A method of helical wave front demultiplexing
\jour Pisma v Zhurnal Tekhnicheskoi Fiziki
\yr 2019
\vol 45
\issue 4
\pages 6--7
\mathnet{http://mi.mathnet.ru/pjtf5523}
\crossref{https://doi.org/10.21883/PJTF.2019.04.47326.17587}
\elib{https://elibrary.ru/item.asp?id=37481319}
\transl
\jour Tech. Phys. Lett.
\yr 2019
\vol 45
\issue 2
\pages 126--128
\crossref{https://doi.org/10.1134/S1063785019020330}
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