Инд. авторы:	Sidelnikov O.S., Redyuk A.A., Sygletos S.
Заглавие:	Equalization performance and complexity analysis of dynamic deep neural networks in long haul transmission systems
Библ. ссылка:	Sidelnikov O.S., Redyuk A.A., Sygletos S. Equalization performance and complexity analysis of dynamic deep neural networks in long haul transmission systems // Optics Express. - 2018. - Vol.26. - Iss. 25. - P.32765-32776. - ISSN 1094-4087.
Внешние системы:	DOI: 10.1364/OE.26.032765; РИНЦ: 38676187; SCOPUS: 2-s2.0-85058151001; WoS: 000452612200035;
Реферат:	eng: We investigate the application of dynamic deep neural networks for nonlinear equalization in long haul transmission systems. Through extensive numerical analysis we identify their optimum dimensions and calculate their computational complexity as a function of system length. Performing comparison with traditional back-propagation based nonlinear compensation of 2 steps-per-span and 2 samples-per-symbol, we demonstrate equivalent mitigation performance at significantly lower computational cost. (C) 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
Ключевые слова:	CHANNEL; DISPERSION; FIBER NONLINEARITY COMPENSATION;
Издано:	2018
Физ. характеристика:	с.32765-32776