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

O. S. Sidelnikov; A. A. Redyuk; S. Sygletos

doi:10.1070/QEL16535

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

O. S. Sidelnikov, A. A. Redyuk, S. Sygletos

Результат исследования: Научные публикации в периодических изданиях › статья › рецензирование

6 Цитирования (Scopus)

Аннотация

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.

Язык оригинала	английский
Страницы (с-по)	1147-1149
Число страниц	3
Журнал	Quantum Electronics
Том	47
Номер выпуска	12
DOI	https://doi.org/10.1070/QEL16535
Состояние	Опубликовано - 2017

Доступ к документу

10.1070/QEL16535

Link to publication in Scopus

Fingerprint Подробные сведения о темах исследования «Dynamic neural network-based methods for compensation of nonlinear effects in multimode communication lines». Вместе они формируют уникальный семантический отпечаток (fingerprint).

Цитировать

@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",

}

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

В: Quantum Electronics, Том 47, № 12, 2017, стр. 1147-1149.

Результат исследования: Научные публикации в периодических изданиях › статья › рецензирование

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 -