Fusing Physics to Fiber Nonlinearity Model for Optical Networks Based on Physics-Guided Neural Networks-Reference-Cited by-同舟云学术

Fusing Physics to Fiber Nonlinearity Model for Optical Networks Based on Physics-Guided Neural Networks

Published:2022-09-01 Issue:17 Volume:40 Page:5793-5802
ISSN:0733-8724
Container-title:Journal of Lightwave Technology
language:
Short-container-title:J. Lightwave Technol.

Author:

Liu Xiaomin¹,Fan Yunyun¹,Zhang Yihao¹,Cai Meng¹,Liu Lei¹,Yi Lilin¹^ORCID,Hu Weisheng¹^ORCID,Zhuge Qunbi¹^ORCID

Affiliation:

1. State Key Laboratory of Advanced Optical Communication Systems and Networks, Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, China

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Shanghai Rising-Star Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atomic and Molecular Physics, and Optics

Link

http://xplorestaging.ieee.org/ielx7/50/9867899/09802856.pdf?arnumber=9802856

Reference26 articles.

1. Application of Machine Learning in Fiber Nonlinearity Modeling and Monitoring for Elastic Optical Networks

2. Machine learning techniques for quality of transmission estimation in optical networks

3. Hybrid Machine Learning EDFA Model

4. Augmenting physical models with deep networks for complex dynamics forecasting;le guen;Journal of Statistical Mechanics Theory and Experiment,2021

5. Physics informed deep learning (part I): Data-driven discovery of nonlinear partial differential equations;raissi,2017

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