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Training of neural networks to perform optical performance monitoring of a combination of accumulated signal nonlinearity, CD, PMD, and OSNR

Published

Author(s)

Jeffrey A. Jargon, Xiaoxia Wu, Louis Christen, Alan Willner

Abstract

We propose a technique using artificial neural networks to simultaneously identify fiber nonlinearity, OSNR, CD, and PMD from eye-diagram and eye-histogram parameters. A correlation coefficient of 0.97 is obtained for a set of testing data.
Proceedings Title
The 21st Annual Meeting of The IEEE Lasers & Electro-Optics Society
Conference Dates
November 9-13, 2008
Conference Location
Newport Beach, CA

Keywords

Artificial neural network, chromatic dispersion, nonlinearity, optical signal-to-noise ratio, performance monitoring, polarization-mode dispersion.

Citation

Jargon, J. , Wu, X. , Christen, L. and Willner, A. (2008), Training of neural networks to perform optical performance monitoring of a combination of accumulated signal nonlinearity, CD, PMD, and OSNR, The 21st Annual Meeting of The IEEE Lasers & Electro-Optics Society, Newport Beach, CA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=33153 (Accessed July 22, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created November 1, 2008, Updated February 19, 2017