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Parametric macromodeling for S ‐parameter data based on internal nonexpansivity
Author(s) -
Ferranti Francesco,
Knockaert Luc,
Dhaene Tom,
Antonini Giulio
Publication year - 2012
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.1825
Subject(s) - parametric statistics , passivity , interpolation (computer graphics) , bounded function , stability (learning theory) , computer science , set (abstract data type) , parametric model , space (punctuation) , parametric design , algorithm , state space , parametric equation , mathematics , control theory (sociology) , mathematical analysis , engineering , geometry , artificial intelligence , electrical engineering , machine learning , motion (physics) , statistics , programming language , operating system , control (management)
SUMMARY We propose a novel parametric macromodeling method for systems described by scattering parameters, which depend on multiple design variables such as geometrical layout or substrate features. The new concept of internal nonexpansivity for bounded real systems is introduced. It is used in combination with suitable interpolation schemes to interpolate a set of state‐space matrices, and hence poles and residues indirectly, to build accurate parametric macromodels. Stability and passivity are guaranteed by construction over the design space of interest. Pertinent numerical examples validate the proposed parametric macromodeling method. Copyright © 2012 John Wiley & Sons, Ltd.