Kotlyar, Oleksandr, Kamalian Kopae, Morteza, Prilepsky, Jaroslaw E., Pankratova, Maryna and Turitsyn, Sergei K. (2019). Machine learning for performance improvement of periodic NFT-based communication system. IN: 2019 European Conference on Optical Communications. Royal Dublin Society, 2019-09-22 - 2019-09-26.
Abstract
We compare performance of several machine learning methods, including support vector machine, k-nearest neighbours, k-means clustering, and Gaussian mixture model, used for increasing transmission reach in the optical communication system based on the periodic nonlinear Fourier transform signal processing
| Divisions: | College of Engineering & Physical Sciences > Aston Institute of Photonics Technology (AIPT) College of Engineering & Physical Sciences Aston University (General) |
|---|---|
| Additional Information: | © The Authors |
| Event Title: | 2019 European Conference on Optical Communications |
| Event Type: | Other |
| Event Location: | Royal Dublin Society |
| Event Dates: | 2019-09-22 - 2019-09-26 |
| Last Modified: | 31 Oct 2024 08:45 |
| Date Deposited: | 05 Jul 2019 15:46 | PURE Output Type: | Paper |
| Published Date: | 2019-09-26 |
| Accepted Date: | 2019-07-01 |
| Authors: |
Kotlyar, Oleksandr
(
0000-0002-2744-0132)
Kamalian Kopae, Morteza (
0000-0002-6278-976X)
Prilepsky, Jaroslaw E. (
0000-0002-3035-4112)
Pankratova, Maryna (
0000-0002-5974-6160)
Turitsyn, Sergei K. (
0000-0003-0101-3834)
|
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)