Deep Learning Regression vs. Classification for QoT Estimation in SMF and FMF Links

M. A. Amirabadi, M. Kahaei, S. Nezamalhosseini, A. Carena
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引用次数: 2

Abstract

We investigate deep learning-based regression and classification for quality of transmission estimation in single-mode and few-mode fiber links. Results show efficiency and low complexity in both methods, however, regression performs better and classification is faster.
深度学习回归与SMF和FMF链接中QoT估计的分类
我们研究了基于深度学习的回归和分类,用于单模和少模光纤链路的传输质量估计。结果表明,两种方法均具有较好的效率和较低的复杂度,但回归性能更好,分类速度更快。
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