Free space material characterization using genetic algorithms

R. Fenner, S. Keilson
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引用次数: 11

Abstract

This work demonstrates the use of genetic algorithms (GA) to transform the traditional free space characterization process into an optimization process. The basis of the process is to compare the measured reflection coefficient to the reflection coefficient computed by the GA. The GA computes the reflection coefficient using candidate solutions of the permittivity and permeability and the Fresnel reflection coefficient equations. The permittivity and permeability that yield the reflection coefficient closest to the measured reflection coefficient is determined to be the best solution. Results using synthetic reflection coefficient data using a Plexiglas sample show accurate extraction of the permittivity with both transverse electric and transverse magnetic polarized plane waves.
利用遗传算法表征自由空间材料
这项工作展示了使用遗传算法(GA)将传统的自由空间表征过程转化为优化过程。该过程的基础是将测量的反射系数与遗传算法计算的反射系数进行比较。遗传算法利用介电常数、磁导率和菲涅耳反射系数方程的候选解计算反射系数。产生的反射系数与实测反射系数最接近的介电常数和渗透率被确定为最佳解决方案。利用有机玻璃样品的合成反射系数数据,可以准确地提取出横向极化平面波和横向极化平面波的介电常数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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