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Optical performance monitoring of PSK Data Channels using artificial neural networks trained with parameters derived from delay-tap asynchronous diagrams via balanced detection

Published

Author(s)

Jeffrey A. Jargon, Xiaoxia Wu, Zhensheng Jia, Loukas Paraschis, Ronald Skoog, Alan Willner

Abstract

We demonstrate a technique of using artificial neural networks for optical performance monitoring of PSK data signals. Parameters for training are derived from delay-tap asynchronous diagrams using balanced detection. We also compare the results with the case of using direct detection.
Proceedings Title
35th European Conference on Optical Communications
Conference Dates
September 20-24, 2009
Conference Location
Vienna

Keywords

artificial neural network, asynchronous sampling, balanced detection, optical performance monitoring

Citation

Jargon, J. , Wu, X. , Jia, Z. , Paraschis, L. , Skoog, R. and Willner, A. (2009), Optical performance monitoring of PSK Data Channels using artificial neural networks trained with parameters derived from delay-tap asynchronous diagrams via balanced detection, 35th European Conference on Optical Communications, Vienna, -1, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=902574 (Accessed March 29, 2024)
Created September 20, 2009, Updated February 19, 2017