Bayesian Optimization for Stack-Up Design
Abstract
Black-box function optimization is a challenging problem worldwide. Bayesian Optimization is a powerful method used to handle the optimization of functions, which are usually too costly for evaluation. Non-convex black-box function optimization arises in many applied problems. One example of such kind of problems is the PCB stack-up design. With its various covariance functions and different values of hyper-parameters Bayesian Optimization is applied for five-dimensional stack-up design optimization. The results obtained using the Bayesian Optimization are compared with results of other methods.
Recommended Citation
Z. Kiguradze et al., "Bayesian Optimization for Stack-Up Design," Proceedings of the 2019 IEEE International Symposium on Electromagnetic Compatibility, Signal and Power Integrity (2019, New Orleans, LA), pp. 629 - 634, Institute of Electrical and Electronics Engineers (IEEE), Jul 2019.
The definitive version is available at https://doi.org/10.1109/ISEMC.2019.8825227
Meeting Name
2019 IEEE International Symposium on Electromagnetic Compatibility, Signal and Power Integrity, EMC+SIPI 2019 (2019: Jul. 22-26, New Orleans, LA)
Department(s)
Electrical and Computer Engineering
Research Center/Lab(s)
Electromagnetic Compatibility (EMC) Laboratory
Keywords and Phrases
Bayesian Optimization; Gaussian Process; PCB Stack-Up Design
International Standard Book Number (ISBN)
978-153869199-1
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2019 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jul 2019
Comments
This paper is based upon work supported partially by the National Science Foundation under Grant No. IIP-1440110.