Performance Monitoring of High-Speed NRZ Signals Using Machine Learning Techniques
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
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 )