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Optical Frequency Comb Noise Characterization Using Machine Learning
Giovanni Brajato, Lars Lundberg, Victor Torres-Company, Darko Zi · 2019-04-23 · via eess.SP updates on arXiv.org

A novel tool, based on Bayesian filtering framework and expectation maximization algorithm, is numerically and experimentally demonstrated for accurate frequency comb noise characterization. The tool is statistically optimum in a mean-square-error-sense, works at wide range of SNRs and offers more accurate noise estimation compared to conventional methods.

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