Conference paper
Machine learning concepts in coherent optical communication systems
In
Proceedings of Signal Processing in Photonic Communications
—
2014
Abstract
Powerful statistical signal processing methods, used by the machine learning community, are addressed and linked to current problems in coherent optical communication. Bayesian filtering methods are presented and applied for nonlinear dynamic state tracking. © 2014 OSA.
| Language: | English |
|---|---|
| Publisher: | Optical Society of America (OSA) |
| Year: | 2014 |
| Proceedings: | Signal Processing in Photonic Communications |
| ISBN: | 1557527377 and 9781557527370 |
| Types: | Conference paper |
| ORCIDs: | Zibar, Darko |
Keywords
Artificial intelligence Atomic and Molecular Physics, and Optics Bayesian filtering Coherent optical communication systems Coherent optical communications Current problems Dynamic state tracking Instrumentation Learning systems Machine learning communities Optical communication Signal processing Statistical signal processing
