Parametric S-Parameter Prediction Using Deep Learning

被引：0
|
作者：
Bansal, Vinayak [1 ]
Feng, Lihong [2 ]
de la Rubia, Valentin [3 ]
Benner, Peter [2 ]
机构：
[1] Indian Inst Technol, Dept Chem Engn, Delhi, India
[2] Max Planck Inst Dynam Complex Tech Syst, Computat Methods Syst & Control Theory, Magdeburg, Germany
[3] Univ Politecn Madrid, Dept Matemat Aplicada TIC, Madrid, Spain
来源：
2024 IEEE 33RD CONFERENCE ON ELECTRICAL PERFORMANCE OF ELECTRONIC PACKAGING AND SYSTEMS, EPEPS 2024 | 2024年
关键词：
S-parameter; convolutional autoencoder; feed-forward neural network;
D O I：
10.1109/EPEPS61853.2024.10754126
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
We construct a neural network model of Sparameters, from which the S-parameters can be quickly predicted. Numerical tests on a filter model show that the proposed method accurately predicts the S-parameters with multiple sharp resonances.
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收藏
页数：3
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