Инд. авторы:	Sorokina M., Sygletos S., Turitsyn S.
Заглавие:	Sparse identification for nonlinear optical communication systems: SINO method
Библ. ссылка:	Sorokina M., Sygletos S., Turitsyn S. Sparse identification for nonlinear optical communication systems: SINO method // Optics Express. - 2016. - Vol.24. - Iss. 26. - P.30433-30443. - ISSN 1094-4087.
Внешние системы:	DOI: 10.1364/OE.24.030433; SCOPUS: 2-s2.0-85009343136;
Реферат:	eng: We introduce a low complexity machine learning method method (based on lasso regression, which promotes sparsity, to identify the interaction between symbols in different time slots and to select the minimum number relevant perturbation terms that are employed) for nonlinearity mitigation. The immense intricacy of the problem calls for the development of 'smart'methodology, simplifying the analysis without losing the key features that are important for recovery of transmitted data. The proposed sparse identification method for optical systems (SINO) allows to determine the minimal (optimal) number of degrees of freedom required for adaptive mitigation of detrimental nonlinear effects. We demonstrate successful application of the SINO method both for standard fiber communication links (over 3 dB gain) and for fewmode spatial-division-multiplexing systems. © 2016 Optical Society of America.
Ключевые слова:	Standard fibers; Spatial Division Multiplexing; Number of degrees of freedom; Nonlinear effect; Non-linear optical; Machine learning methods; Nonlinear optics; Identification method; Optical communication; Multiplexing equipment; Learning systems; Degrees of freedom (mechanics); Adaptive optics; Lasso regressions;
Издано:	2016
Физ. характеристика:	с.30433-30443