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PCB based power delivery network analysis using transfer learning and artificial neural networks
Publikationstyp
Conference Paper
Date Issued
2024-05
Sprache
English
Citation
SPI 2024 - 28th IEEE Workshop on Signal and Power Integrity, Proceedings
Contribution to Conference
Publisher DOI
Scopus ID
Publisher
IEEE
ISBN
979-8-3503-8293-8
In this paper, the applicability of transfer learning (TL) combined with artificial neural networks (ANNs) for power integrity analysis of printed circuit boards (PCBs) is investigated. Reusing already existing data samples from a database enables to reduce the amount of data samples required for a new problem setting. Here, more than 30 000 electromagnetic numerical simulations are evaluated of different PCB shapes, geometries, and used materials. The format and processing of the data is adapted at hand, e.g. the plane capacitance is used as one additional input feature. If less than 50 training samples are available the error is reduced by a factor 2 using TL.
Subjects
Artificial Neural Networks
Power Integrity
Printed Circuit Boards
SI/PI-Database
Transfer Learning
MLE@TUHH
DDC Class
600: Technology