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|Author(s):||Jeffrey A. Jargon; Xiaoxia Wu; Alan Willner;|
|Title:||Optical performance monitoring using artificial neural networks trained with eye-diagram parameters|
|Published:||January 01, 2009|
|Abstract:||We developed artificial neural network models to simultaneously identify three separate impairments that can degrade optical channels, namely optical signal-to-noise ratio, chromatic dispersion, and polarization mode dispersion. The neural networks were trained with parameters derived from eye diagrams to create models that can predict levels of concurrent impairments. This method provides a means of monitoring optical performance with diagnostic capabilities.|
|Citation:||IEEE Photonics Technology Letters|
|Keywords:||artificial neural network, chromatic dispersion, differential group delay, eye diagram, optical performance monitoring, optical signal-to-noise ratio|
|PDF version:||Click here to retrieve PDF version of paper (505KB)|