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A Low-cost OSNR Monitoring Method Using Frequency Spectra of Low-speed Sampling Signals

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Abstract

A low-cost OSNR monitoring method using artificial neural networks trained by frequency spectra of low-speed sampling signals is proposed. The monitoring range from 10.5 to 28.5 dB with error less than ± 0.5 dB is achieved.

© 2020 The Author(s)

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