Journal article
A novel adaptive sampling algorithm based on the survival-of-the-fittest principle of genetic algorithms
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.
Language: | English |
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Publisher: | IEEE |
Year: | 2004 |
Pages: | 265,266,267,268,269,270,271,272,273,274,275 |
ISSN: | 15579670 and 00189480 |
Types: | Journal article |
DOI: | 10.1109/TMTT.2003.820894 |
Acceleration Approximation algorithms Approximation error Convergence Electromagnetic devices Frequency response Genetic algorithms Microwave devices Microwave filters Sampling methods adaptive sampling algorithm circuit CAD computational electromagnetics computer-aided design denominator polynomial electromagnetic responses frequency response frequency-domain analysis frequency-domain calculations generic scattering parameter genetic algorithms interpolation microwave circuits microwave filters numerator polynomial rational functions reduced order systems reduced-order models survival-of-the-fittest principle