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Machine learning algorithms for emulation of nonlinear optical fibre impairments
Jones, Rasmus Thomas
(PhD Student)
Zibar, Darko
(Main Supervisor)
Forchhammer, Søren Otto
(Examiner)
Carena, Andrea
(Examiner)
Okonkwo, Chigo
(Examiner)
Yankov, Metodi Plamenov
(Supervisor)
Overview
Fingerprint
Publications
(1)
Project Details
Status
Finished
Effective start/end date
01/11/2015
→
23/01/2019
Funding
Samfinansierede - Virksomhed
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Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
Machine Learning Method
Engineering
100%
Optical Communication System
Engineering
100%
Machine Learning
Computer Science
100%
Optical Communication
Computer Science
100%
Fibre Channel
Engineering
75%
Channel Model
Engineering
75%
Nonlinear Effect
Engineering
50%
Solitary Wave
Physics
42%
Research output
Publications per year
2019
2019
2019
1
Ph.D. thesis
Publications per year
Publications per year
Machine Learning Methods in Coherent Optical Communication Systems
Jones, R. T.,
2019
, Kgs. Lyngby:
Technical University of Denmark
.
140 p.
Research output
:
Book/Report
›
Ph.D. thesis
Open Access
File
Optical Communication System
100%
Machine Learning Method
100%
Machine Learning
100%
Optical Communication
100%
Learning System
100%
2683
Downloads (Pure)