Sidelnikov, O S, Redyuk, A A and Sygletos, S (2017). Dynamic neural network-based methods for compensation of nonlinear effects in multimode communication lines. Quantum Electronics, 47 (12), pp. 1147-1149.
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.
| Publication DOI: | https://doi.org/10.1070/QEL16535 |
|---|---|
| Divisions: | College of Engineering & Physical Sciences > Aston Institute of Photonics Technology (AIPT) College of Engineering & Physical Sciences |
| Additional Information: | © 2017 Kvantovaya Elektronika, Turpion Ltd and IOP Publishing Ltd. Funding: Russian Science Foundation (Project No. 17-72-30006). |
| Uncontrolled Keywords: | Mathematical modelling. Neural networks Nonlinear effects Optical fibre |
| Publication ISSN: | 1468-4799 |
| Last Modified: | 30 Oct 2024 08:32 |
| Date Deposited: | 25 Jun 2019 14:34 |
| Full Text Link: | |
| Related URLs: |
https://www.sco ... eca4d46782c6f7b
(Scopus URL) http://iopscien ... 0/QEL16535/meta (Publisher URL) |
PURE Output Type: | Article |
| Published Date: | 2017-12-31 |
| Accepted Date: | 2017-10-16 |
| Authors: |
Sidelnikov, O S
Redyuk, A A Sygletos, S ( 
0000-0003-2063-8733)
|
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