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Optical Performance Monitoring Using Artificial Neural Networks Trained with Parameters Derived from Delay-Tap Asynchronous Sampling

Published

Author(s)

Jeffrey A. Jargon, Xiaoxia Wu, Alan Willner

Abstract

We demonstrate a technique for optical performance monitoring by simultaneously identifying optical signal-to-noise ratio (OSNR), chromatic dispersion (CD), and polarization-mode dispersion (PMD) using artificial neural networks trained with parameters derived from delay-tap asynchronous sampling.
Proceedings Title
Tech. Dig., Optical Fiber Communication Conf. (OFC)
Conference Dates
March 22-26, 2009
Conference Location
San Diego, CA

Keywords

artificial neural network, asynchronous sampling, chromatic dispersion, optical performance monitoring, optical signal-to-noise ratio, polarization-mode dispersion

Citation

Jargon, J. , Wu, X. and Willner, A. (2009), Optical Performance Monitoring Using Artificial Neural Networks Trained with Parameters Derived from Delay-Tap Asynchronous Sampling, Tech. Dig., Optical Fiber Communication Conf. (OFC), San Diego, CA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=33186 (Accessed June 18, 2024)

Issues

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

Created March 20, 2009, Updated February 19, 2017