Standard

Dynamic neural network-based methods for compensation of nonlinear effects in multimode communication lines. / Sidelnikov, O. S.; Redyuk, A. A.; Sygletos, S.

In: Quantum Electronics, Vol. 47, No. 12, 2017, p. 1147-1149.

Research output: Contribution to journal › Article › peer-review

Harvard

Sidelnikov, OS, Redyuk, AA & Sygletos, S 2017, 'Dynamic neural network-based methods for compensation of nonlinear effects in multimode communication lines', Quantum Electronics, vol. 47, no. 12, pp. 1147-1149. https://doi.org/10.1070/QEL16535

APA

Sidelnikov, O. S., Redyuk, A. A., & Sygletos, S. (2017). Dynamic neural network-based methods for compensation of nonlinear effects in multimode communication lines. Quantum Electronics, 47(12), 1147-1149. https://doi.org/10.1070/QEL16535

Vancouver

Sidelnikov OS, Redyuk AA, Sygletos S. Dynamic neural network-based methods for compensation of nonlinear effects in multimode communication lines. Quantum Electronics. 2017;47(12):1147-1149. doi: 10.1070/QEL16535

Author

Sidelnikov, O. S. ; Redyuk, A. A. ; Sygletos, S. / Dynamic neural network-based methods for compensation of nonlinear effects in multimode communication lines. In: Quantum Electronics. 2017 ; Vol. 47, No. 12. pp. 1147-1149.

BibTeX

@article{bc373121001d4eee860d797c778751a0,
title = "Dynamic neural network-based methods for compensation of nonlinear effects in multimode communication lines",
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 = "Mathematical modelling., Neural networks, Nonlinear effects, Optical fibre",
author = "Sidelnikov, {O. S.} and Redyuk, {A. A.} and S. Sygletos",
year = "2017",
doi = "10.1070/QEL16535",
language = "English",
volume = "47",
pages = "1147--1149",
journal = "Quantum Electronics",
issn = "1063-7818",
publisher = "Turpion Ltd.",
number = "12",

}

RIS

TY - JOUR

T1 - Dynamic neural network-based methods for compensation of nonlinear effects in multimode communication lines

AU - Sidelnikov, O. S.

AU - Redyuk, A. A.

AU - Sygletos, S.

PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

KW - Mathematical modelling.

KW - Neural networks

KW - Nonlinear effects

KW - Optical fibre

UR - http://www.scopus.com/inward/record.url?scp=85040975228&partnerID=8YFLogxK

U2 - 10.1070/QEL16535

DO - 10.1070/QEL16535

M3 - Article

AN - SCOPUS:85040975228

VL - 47

SP - 1147

EP - 1149

JO - Quantum Electronics

JF - Quantum Electronics

SN - 1063-7818

IS - 12

ER -

ID: 9332578