Adaptive multivariate rational data fitting with applications in electromagnetics

The behavior of certain electromagnetic devices or components can be simulated with great detail in software. A drawback of these simulation models is that they are very time consuming. Since the accuracy required for the computational electromagnetic analysis is usually only 2-3 significant digits,...

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Bibliographic Details
Published in:IEEE transactions on microwave theory and techniques 2006-05, Vol.54 (5), p.2265-2274
Main Authors: Cuyt, A., Lenin, R.B., Becuwe, S., Verdonk, B.
Format: Article
Language:English
Subjects:
Application software
Applied sciences
Approximation
Computational electromagnetics
Computational modeling
Computer simulation
Digits
Electric, optical and optoelectronic circuits
Electromagnetic analysis
Electromagnetic devices
Electromagnetic modeling
Electromagnetics
Electronics
Exact sciences and technology
Finite wordlength effects
Interpolation
Linear systems
Magnetoelectric, magnetostrictive, magnetoacoustic, magnetooptic and magnetothermal devices. Spintronics
Mathematical analysis
Mathematical models
meta-modeling
Microwaves
multivariate
Polynomials
rational function
Rational functions
Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices
Theoretical study. Circuits analysis and design
Truncation errors
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Description
Summary:The behavior of certain electromagnetic devices or components can be simulated with great detail in software. A drawback of these simulation models is that they are very time consuming. Since the accuracy required for the computational electromagnetic analysis is usually only 2-3 significant digits, an approximate analytic model is sometimes used instead, as noted by Lehmensiek and Meyer in 2001. The most complex model we consider here is a multivariate rational function, which interpolates a number of simulation data. The interpolating rational function is constructed in such a way that it minimizes both the truncation error and the number of simulation data since each evaluation of the simulation model is computationally costly.
ISSN:0018-9480
1557-9670
DOI:10.1109/TMTT.2006.873637