A novel adaptive sampling algorithm based on the survival-of-the-fittest principle of genetic algorithms

Michael Mattes*, Juan R. Mosig

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

A new adaptive sampling is proposed to accelerate frequency-domain calculations. The algorithm is based on the survival-of-the-fittest principle of genetic algorithms and uses rational functions to approximate the frequency response. The sampling algorithm is derivative free and well-adapted to devices with rapidly varying frequency responses like microwave filters. The criteria for convergence checking and to determine the location of additional sampling points are easy and fast to evaluate because they are based on the rational functions. Moreover, they provide an estimation of the approximation error and can be used to determine whether the algorithm has problems to reach convergence. The adaptive sampling algorithm leads to a significant reduction of simulation points, as demonstrated by parameter studies. This allows an efficient simulation of electromagnetic responses, as application examples show, which is of great importance when optimizing devices.

Original languageEnglish
JournalIEEE Transactions on Microwave Theory and Techniques
Volume52
Issue number1 II
Pages (from-to)265-275
Number of pages11
ISSN0018-9480
DOIs
Publication statusPublished - Jan 2004
Externally publishedYes

Keywords

  • Adaptive sampling
  • Computer-aided design (CAD)
  • Genetic algorithm (GA)
  • Rational interpolation/approximation
  • Reduced-order models

Fingerprint Dive into the research topics of 'A novel adaptive sampling algorithm based on the survival-of-the-fittest principle of genetic algorithms'. Together they form a unique fingerprint.

Cite this