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Bayesian trained rational functions for electromagnetic design optimization

Authors: Yasser El Kahlout; Gullu Kiziltas;

Bayesian trained rational functions for electromagnetic design optimization

Abstract

This paper presented an interpolation scheme based on Bayesian trained quadratic rational functions for approximating frequency based electromagnetic return loss responses. Initial results indicate that this scheme is an efficient tool in catching nulls and characterizing resonance behavior. With the implementation of the adjoint variable method for effective gradient evaluations, this may be an alternative tool to predict the nulls and corresponding BW values for practical heuristic design optimization studies. Future work includes elaborating on coef and adaptive selection of sample points and finally applying it to a global design optimization example.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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