On the Generalization of Machine-Learning-aided QoT Estimation in Optical Networks-Reference-Cited by-同舟云学术

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On the Generalization of Machine-Learning-aided QoT Estimation in Optical Networks

Published:2023-05-05 Issue: Volume: Page:
ISSN:
Container-title:2023 32nd Wireless and Optical Communications Conference (WOCC)
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Author:

Gao Hanyu¹,Zhang Liang²,Zhang Bin¹,Chen Xiaoliang¹,Li Zhaohui¹

Affiliation:

1. School of Electronics and Information Technology, Sun Yat-sen University,Guangdong Provincial Key Labratory of Optoelectronic, Information Processing Chips and Systems,Guangzhou,China

2. George Mason University,Department of Electrical and Computer Engineering,Fairfax,VA,USA,22030

Funder

NSFC

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10139315/10138944/10139536.pdf?arnumber=10139536

Reference17 articles.

1. On the benefits of domain adaptation techniques for quality of transmission estimation in optical networks

2. Model transfer of QoT prediction in optical networks based on artificial neural networks

3. Using Active Learning to Decrease Probes for QoT Estimation in Optical Networks

4. Active learning literature survey;settles;Computer Sciences Technical Report 1648 University of Wisconsin-Madison,2009

5. Transfer Learning for Neural Networks-Based Equalizers in Coherent Optical Systems

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