A Transceiver-Configuration-Independent 2-D Electromagnetic Full-Wave Inversion Scheme Based on End-to-End Artificial Neural Networks-Reference-Cited by-同舟云学术

A Transceiver-Configuration-Independent 2-D Electromagnetic Full-Wave Inversion Scheme Based on End-to-End Artificial Neural Networks

Published:2023-05 Issue:5 Volume:71 Page:4600-4605
ISSN:0018-926X
Container-title:IEEE Transactions on Antennas and Propagation
language:
Short-container-title:IEEE Trans. Antennas Propagat.

Author:

Li Jiawen¹^ORCID,Hu Hao-Jie¹,Wang Jianwen¹^ORCID,Zhuang Mingwei¹^ORCID,Xiao Li-Ye¹^ORCID,Liu Qing Huo²^ORCID

Affiliation:

1. Institute of Electromagnetics and Acoustics, Fujian Provincial Key Laboratory of Electromagnetic Wave Science and Detection Technology, Xiamen University, Xiamen, China

2. Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/8/10116028/10068421.pdf?arnumber=10068421

Reference23 articles.

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

2. Three-dimensional parallel distributed inversion of CSEM data using a direct forward solver

3. Special section: Testing inversion algorithms against experimental data

4. Fast Electromagnetic Inversion of Inhomogeneous Scatterers Embedded in Layered Media by Born Approximation and 3-D U-Net

5. Super-Resolution 3-D Microwave Imaging of Objects With High Contrasts by a Semijoin Extreme Learning Machine

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