Advances in Radio Science
Advances in Radio Science
ARS
Articles | Volume 21
Articles | Volume 21
https://doi.org/10.5194/ars-21-77-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ars-21-77-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 21
01 Dec 2023
 | 01 Dec 2023

AI Models for Supporting SI Analysis on PCB Net Structures: Comparing Linear and Non-Linear Data Sources

Julian Withöft, Werner John, Emre Ecik, Ralf Brüning, and Jürgen Götze

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Short summary
In this paper, a two-stage artificial intelligence framework for supporting the signal integrity compliant printed circuit board design process has been developed. This framework was applied to compare linear and non-linear data, which showed that the non-linear data source gains advantages over the linear data in terms of attainable regression accuracy. For the investigated application however, the linear model can be utilized directly or by utilizing transfer learning for adequate results.
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