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Scalable models of microwave system responses using sequential sampling on unstructured grids
Author(s) -
Chemmangat Krishnan,
Ferranti Francesco,
Dhaene Tom,
Knockaert Luc
Publication year - 2013
Publication title -
international journal of numerical modelling: electronic networks, devices and fields
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.249
H-Index - 30
eISSN - 1099-1204
pISSN - 0894-3370
DOI - 10.1002/jnm.1903
Subject(s) - scalability , computer science , parameterized complexity , sampling (signal processing) , selection (genetic algorithm) , domain (mathematical analysis) , algorithm , frequency domain , computer engineering , artificial intelligence , mathematics , mathematical analysis , filter (signal processing) , database , computer vision
SUMMARY This paper presents two sequential sampling algorithms for the macromodeling of parameterized system responses in model‐dependent sampling frameworks. The construction of efficient algorithms for the automatic selection of samples for building scalable macromodels of frequency‐domain responses is addressed in this paper. The sequential sampling algorithms proposed here are tailored toward the application of local scalable macromodeling schemes on unstructured design space grids. Two pertinent examples are considered. For the first one, different algorithms are applied, and a comparison is made in terms of the number of samples generated, accuracy and CPU time. As a second example, four design variables are taken into account with one of the proposed algorithms, and the generated model is used in a frequency‐domain optimization. Copyright © 2013 John Wiley & Sons, Ltd.