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Design Optimisation of Power-Efficient Submarine Line through Machine Learning
- Source :
- Conference on Lasers and Electro-Optics.
- Publication Year :
- 2020
- Publisher :
- Optica Publishing Group, 2020.
-
Abstract
- An optimised subsea system design for energy-efficient SDM operation is demonstrated using machine learning. The removal of gain-flattening filters employed in submarine optical amplifiers can result in capacity gains at no additional overall repeater cost.<br />Comment: CLEO 2020
- Subjects :
- Signal Processing (eess.SP)
Optical amplifier
Repeater
Artificial neural network
business.industry
Computer science
Optical communication
Submarine
ComputerApplications_COMPUTERSINOTHERSYSTEMS
02 engineering and technology
021001 nanoscience & nanotechnology
Machine learning
computer.software_genre
01 natural sciences
010309 optics
0103 physical sciences
FOS: Electrical engineering, electronic engineering, information engineering
Systems design
Artificial intelligence
Electrical Engineering and Systems Science - Signal Processing
0210 nano-technology
business
computer
Structured systems analysis and design method
Subsea
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Conference on Lasers and Electro-Optics
- Accession number :
- edsair.doi.dedup.....1b17b7bd80efe790a51cf766d3cdb8ea
- Full Text :
- https://doi.org/10.1364/cleo_si.2020.sth4m.5