Creating accurate multivariate rational interpolation models of microwave circuits by using efficient adaptive sampling to minimize the number of computational electromagnetic analyses

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dc.contributor.authorLehmensiek R.
dc.contributor.authorMeyer P.
dc.date.accessioned2011-05-15T16:01:46Z
dc.date.available2011-05-15T16:01:46Z
dc.date.issued2001
dc.description.abstractA fast and efficient adaptive sampling algorithm for multivariate rational interpolation models based on convergents of Thiele-type branched continued fractions (BCFs) is presented in this paper. We propose a variation of the standard BCF that uses approximation to establish a nonrectangular grid of support points. Starting with a low-order interpolant, the technique systematically increases the order by optimally choosing new support points in the areas of highest error until the required accuracy is achieved. In this way, accurate surrogate models are established by a small number of support points without any a priori knowledge of the data. The technique is evaluated on several passive microwave structures.
dc.description.versionConference Paper
dc.identifier.citationIEEE Transactions on Microwave Theory and Techniques
dc.identifier.citation49
dc.identifier.citation8
dc.identifier.issn189480
dc.identifier.other10.1109/22.939922
dc.identifier.urihttp://hdl.handle.net/10019.1/12140
dc.subjectBranched continued fractions (BCF)
dc.subjectComputational electromagnetic (CEM) amalysis
dc.subjectAdaptive algorithms
dc.subjectApproximation theory
dc.subjectComputer aided design
dc.subjectElectromagnetism
dc.subjectError analysis
dc.subjectInterpolation
dc.subjectMathematical models
dc.subjectParameter estimation
dc.subjectSampling
dc.subjectMicrowave circuits
dc.titleCreating accurate multivariate rational interpolation models of microwave circuits by using efficient adaptive sampling to minimize the number of computational electromagnetic analyses
dc.typeConference Paper
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