NOTICE: Due to a lapse in annual appropriations, most of this website is not being updated. Learn more.
Form submissions will still be accepted but will not receive responses at this time. Sections of this site for programs using non-appropriated funds (such as NVLAP) or those that are excepted from the shutdown (such as CHIPS and NVD) will continue to be updated.
An official website of the United States government
Here’s how you know
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
Secure .gov websites use HTTPS
A lock (
) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.
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
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 October 27, 2025)