Modeling Radio-Frequency Devices Based on Deep Learning Technique
An advanced method of modeling radio-frequency (RF) devices based on a deep learning technique is proposed for accurate prediction of S parameters. The S parameters of RF devices calculated by full-wave electromagnetic solvers along with the metallic geometry of the structure, permittivity and thick...
Main Authors: | Zhimin Guan, Peng Zhao, Xianbing Wang, Gaofeng Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-07-01
|
Series: | Electronics |
Subjects: | |
Online Access: | https://www.mdpi.com/2079-9292/10/14/1710 |
Similar Items
-
Evaluation of Pilot-Scale Radio Frequency Heating Uniformity for Beef Sausage Pasteurization Process
by: Ke Wang, et al.
Published: (2022-04-01) -
Onsite Non-Line-of-Sight Imaging via Online Calibration
by: Zhengqing Pan, et al.
Published: (2022-01-01) -
Gradient Estimation for Ultra Low Precision POT and Additive POT Quantization
by: Huruy Tesfai, et al.
Published: (2023-01-01) -
Non-Uniform Synthetic Aperture Radiometer Image Reconstruction Based on Deep Convolutional Neural Network
by: Chengwang Xiao, et al.
Published: (2022-05-01) -
Whitecap Fraction Parameterization and Understanding with Deep Neural Network
by: Shuyi Zhou, et al.
Published: (2022-12-01)