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Optimization of modal reflection parameters of PCB connector and common-mode choke using Gaussian process regression and segmentation
Citation Link: https://doi.org/10.15480/882.17176
Publikationstyp
Conference Paper
Date Issued
2026
Sprache
English
TORE-DOI
Citation
International Symposium on Electromagnetic Compatibility, EMC Europe 2026
Contribution to Conference
Publisher
Institute of Electrical and Electronics Engineers
In this contribution the electrical properties of a high-speed signal transition from a connector onto a printed circuit board (PCB) followed by a common-mode choke (CMC) in a surface mount package in terms of its modal, i.e., differentialand common-mode, reflection parameters has been investigated. An implementation of segmentation, i.e. domain decomposition and subsequent composition of subdomains, in combination with Gaussian process regression (GPR) to optimize the reflections of the PCB connectors and CMC integration on the board is presented and analyzed. GPR is used with Bayesian optimization to find an optimal set of design parameters for a 3D electromagnetic model developed in a full-wave electromagnetic field solver up to 20 GHz. The results indicate that an engineeringinformed domain decomposition strategy can reduce the computational burden of GPR-based optimization by lowering the per-evaluation full-wave cost. This surrogate-based optimization approach reduces the number of required full-wave simulations, enabling more efficient use of computational resources.
Subjects
Gaussian Process Regression
Bayesian Optimization
high-speed interconnects
PCB connectors
machine learning
common-mode choke packages
design optimization
DDC Class
510: Mathematics
More Funding Information
This project has received funding from the European Union’s EU Framework Programme for Research and Innovation Europe Horizon (Grant Agreement No. 101169295, for Doctoral Candidates 1–15) and DMU (De Montfort University, for Doctoral Candidate 16). Project website: pattern-dn.eu/
Publisher‘s Creditline
Author accepted manuscript (AAM) with CC-BY license and without embargo.
Publication version
acceptedVersion
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Name
AAM_EMC_EUROPE_2026_PATTERN.pdf
Type
Main Article
Size
1.37 MB
Format
Adobe PDF