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Enhanced uniform data sampling for constrained data‐driven modeling of antenna input characteristics

Abstract

Data-driven surrogates are the most popular replacement models utilized in many fields of engineering and science, including design of microwave and antenna structures. The primary practical issue is a curse of dimensionality which limits the number of independent parameters that can be accounted for in the modelling process. Recently, a performance-driven modelling technique has been proposed where the constrained domain of the model is spanned by a set of reference designs optimized with respect to selected figures of interest. This approach allows for significant improvement of prediction power of the surrogates without the necessity of reducing the parameter ranges. Yet, uniform allocation of the training data samples in the constrained domain remains a problem. Here, a novel design of experiments technique ensuring better sample uniformity is proposed. Our approach involves uniform sampling on the domain-spanning manifold and linear transformation of the remaining sample vector components onto orthogonal directions with respect to the manifold. Two antenna examples are provided to demonstrate the advantages of the technique, including application case studies (antenna optimization).

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Category:
Articles
Type:
artykuły w czasopismach
Published in:
INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS no. 32, pages 1 - 11,
ISSN: 0894-3370
Language:
English
Publication year:
2019
Bibliographic description:
Kozieł S., Sigurdsson A., Pietrenko-Dąbrowska A., Szczepański S.: Enhanced uniform data sampling for constrained data‐driven modeling of antenna input characteristics// INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS -Vol. 32,iss. 5 (2019), s.1-11
DOI:
Digital Object Identifier (open in new tab) 10.1002/jnm.2584
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Gdańsk University of Technology

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