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|Author(s):||Jeffrey A. Jargon; Xiaoxia Wu; Alan Willner; Loukas Paraschis;|
|Title:||Optical performance monitoring of (Q)PSK data channels using artificial neural networks trained with parameters derived from delay-tap asynchronous diagrams|
|Published:||February 15, 2011|
|Abstract:||We demonstrate a technique of using artificial neural networks trained with parameters derived from delay-tap asynchronous diagrams for optical performance monitoring of phase shift keying (PSK) data signals. We show that asynchronous diagrams from balanced detection give superior results compared to direct detection in a 40 Gb/s binary PSK system. Experimental demonstration in a 100 Gb/s quadrature PSK system verifies the effectiveness of the proposed technique.|
|Citation:||IEEE Photonics Technology Letters|
|Keywords:||neural networks, optical fiber communication, optical performance monitoring, phase modulation|
|Research Areas:||Electronics & Telecommunications, Measurement Solutions, Optoelectronics|