Performance Monitoring of High-Speed NRZ Signals Using Machine Learning Techniques | |
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學年 | 110 |
學期 | 1 |
發表日期 | 2021-11-16 |
作品名稱 | Performance Monitoring of High-Speed NRZ Signals Using Machine Learning Techniques |
作品名稱(其他語言) | |
著者 | Chun-Chen Yao; Jun-Yuan Zheng; Jau-Ji Jou; Chun-Liang Yang |
作品所屬單位 | |
出版者 | |
會議名稱 | 2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) |
會議地點 | Hualien,Taiwan |
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. |
關鍵字 | Signal performance monitoring;artificial neural network (ANN);Machine learning |
語言 | en |
收錄於 | |
會議性質 | 國際 |
校內研討會地點 | 無 |
研討會時間 | 20211116~20211119 |
通訊作者 | |
國別 | TWN |
公開徵稿 | |
出版型式 | |
出處 | |
相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/122285 ) |
SDGS | 優質教育,產業創新與基礎設施 |