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    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/122285


    题名: Performance Monitoring of High-Speed NRZ Signals Using Machine Learning Techniques
    作者: Yao, Chun-Chen;Zheng, Jun-Yuan;Jou, Jau-Ji;Yang, Chun-Liang
    关键词: Signal performance monitoring;artificial neural network (ANN);Machine learning
    日期: 2021-11-16
    上传时间: 2022-02-26 12:10:39 (UTC+8)
    摘要: Advances in high-speed communication network technologies have spurred interest in signal performance monitoring. This study proposed a 25-Gb/s non-return-to-zero (NRZ) signal performance monitoring method using an artificial neural network (ANN), which can estimate the five parameters of Q factor, signal-to-noise ratio, time jitter, rise time, and fall time. Using 5000 data sets and adopting seven neurons in the hidden layer, the mean relative errors of the five estimated parameters are about 5.76% to 11.74%. This parameter extraction technique based on machine learning can apply to real-time optical network performance monitoring for high-speed NRZ signals.
    DOI: 10.1109/ISPACS51563.2021.9650979
    显示于类别:[電機工程學系暨研究所] 會議論文

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