Bayesian Optimization for Stack-Up Design
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.
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
2019 IEEE International Symposium on Electromagnetic Compatibility, Signal and Power Integrity, EMC+SIPI 2019 (2019: Jul. 22-26, New Orleans, LA)
Electrical and Computer Engineering
Electromagnetic Compatibility (EMC) Laboratory
Keywords and Phrases
Bayesian Optimization; Gaussian Process; PCB Stack-Up Design
International Standard Book Number (ISBN)
Article - Conference proceedings
© 2019 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
01 Jul 2019