Physics-Informed Deep Neural Network for Inhomogeneous Magnetized Plasma Parameter Inversion-Reference-Cited by-同舟云学术

Physics-Informed Deep Neural Network for Inhomogeneous Magnetized Plasma Parameter Inversion

Published:2022-04 Issue:4 Volume:21 Page:828-832
ISSN:1536-1225
Container-title:IEEE Antennas and Wireless Propagation Letters
language:
Short-container-title:Antennas Wirel. Propag. Lett.

Author:

Zhang Yangyang¹^ORCID,Fu Haiyang¹^ORCID,Qin Yilan¹,Wang Kangning¹,Ma Jiayu¹

Affiliation:

1. Key Laboratory for Information Science of Electromagnetic Waves (Ministry of Education), School of Information Science and Engineering, Fudan University, Shanghai, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/7727/9750267/09709153.pdf?arnumber=9709153

Reference22 articles.

1. Neural Network Model for Parameter Inversion in Electromagnetic Wave and Plasma Interaction Systems

2. Reduced-order modeling methods of electromagnetic wave propagation in magnetized plasmas

3. Physics-informed machine learning

4. Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

5. Automatic differentiation in machine learning: A survey;baydin;J Mach Learn Res,2017

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