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.

引用

页数：3

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