Customized Design of Frequency-Selective Surfaces Using the Vector-Graph-Feature-Extraction Deep-Neural-Network (VGFE-DNN) Method-Reference-Cited by-同舟云学术

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Customized Design of Frequency-Selective Surfaces Using the Vector-Graph-Feature-Extraction Deep-Neural-Network (VGFE-DNN) Method

Published:2024-08 Issue:8 Volume:72 Page:6795-6800
ISSN:0018-926X
Container-title:IEEE Transactions on Antennas and Propagation
language:
Short-container-title:IEEE Trans. Antennas Propagat.

Author:

Gao Jiale¹^ORCID,Lv Jingyan²,Fu Ziming³,Wu Yanghui¹^ORCID,Gu Wenhua¹^ORCID

Affiliation:

1. School of Microelectronics and the School of Integrated Circuits, Key Laboratory of Near-Range RF Sensing ICs and Microsystems, Ministry of Education, Nanjing University of Science and Technology, Nanjing, China

2. School of Microelectronics and the School of Integrated Circuits, Nanjing University of Science and Technology, Nanjing, China

3. Department of Artificial Intelligence, Nanyang Technological University, Nanyang Avenue, Singapore

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/8/10633212/10565795.pdf?arnumber=10565795

Reference16 articles.

1. Light Propagation with Phase Discontinuities: Generalized Laws of Reflection and Refraction

2. Design of a Broadband High-Gain Omnidirectional Antenna With Low Cross Polarization Based on Characteristic Mode Theory

3. Prediction of the Electromagnetic Shielding Effectiveness of Metal Grid Using Neural Network Algorithm

4. Stretchable Broadband Absorbers Based on the Hauberk Structure

5. Deep neural networks for the evaluation and design of photonic devices

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