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This document presents a comprehensive survey on the applications of machine learning (ML) in low-cost non-coherent optical systems, particularly focusing on optical performance monitoring (OPM), modulation format identification (MFI), and baud rate identification (BRI). It highlights the potential of ML to enhance adaptability and intelligent control in future optical networks, addressing challenges related to network performance monitoring and optimization without the need for signal recovery. The paper a

Author

samia DRIZ

Language

EN