Abstract
In this work, we evaluate machine learning (offline) and evolutionary strategy (online) techniques for the Raman pump power optimization. Experimental results show that, although reusable and accurate, online tools may be time-consuming for reconfigurable amplifiers.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 27th OptoElectronics and Communications Conference (OECC) and 2022 International Conference on Photonics in Switching and Computing |
| Number of pages | 4 |
| Publisher | IEEE |
| Publication date | 6 Jul 2022 |
| Pages | 1-4 |
| Article number | 9850067 |
| ISBN (Print) | 978-1-6654-8606-4 |
| DOIs | |
| Publication status | Published - 6 Jul 2022 |
| Event | 27th OptoElectronics and Communications Conference (OECC) and 2022 International Conference on Photonics in Switching and Computing (PSC) - Toyama International Conference Center, Toyama, Japan Duration: 3 Jul 2022 → 6 Jul 2022 https://www.oeccpsc2022.org/about_oecc.html |
Conference
| Conference | 27th OptoElectronics and Communications Conference (OECC) and 2022 International Conference on Photonics in Switching and Computing (PSC) |
|---|---|
| Location | Toyama International Conference Center |
| Country/Territory | Japan |
| City | Toyama |
| Period | 03/07/2022 → 06/07/2022 |
| Internet address |
Keywords
- Stimulated emission
- Shape
- Optical switches
- Pumps
- Optimization methods
- Machine learning
- Artificial neural networks
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