Non-linear interpolation and adaptive sampling of scattering parameters

The accurate and efficient sampling of scattering parameters is addressed. A popular sampling technique is the uniform sampling combined with a straight-line interpolation for representing the continuous variation of the observable. However, this sampling becomes rapidly inefficient if the observable varies strongly since a high-oversampling is necessary due to Nyquist’s theorem. An alternative is nonlinear sampling and non-linear interpolation of the sampling points. Another reason why more efficient sampling techniques are needed is the optimization of devices using full-wave simulation tools where the reduction of sampling points is essential to accelerate the design of a component. This paper presents an algorithm that is based on ideas coming from the model-based parameter estimation (MBPE) and the competition and selection of interpolating models similar as in the Genetic Algorithm (GA).


Published in:
Proceedings of the 26th International Review of Progress in Applied Computational Electromagnetics (ACES)
Presented at:
26th International Review of Progress in Applied Computational Electromagnetics (ACES), Tampere, Finland, April 25-29, 2010
Year:
2010
Keywords:
Laboratories:




 Record created 2010-03-16, last modified 2018-03-17


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