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Learning from the Optical Spectrum: Soft-Failure Identification and Localization [Invited]

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Abstract

The availability of coarse-resolution cost-effective Optical Spectrum Analyzers (OSA) allows its widespread deployment in operators’ networks. In this paper, several machine learning approaches for failure identification and localization that take advantage of OSAs are presented.

© 2018 The Author(s)

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