Microwave characterization of dielectric materials using Bayesian neural networks

被引：9

作者：

Acikgoz, H. ^{[1
]}

Bihan, Y.L. ^{[1
]}

Meyer, O. ^{[1
]}

Pichon, L. ^{[1
]}

机构：

[1] Laboratoire de Génie Electrique de Paris, CNRS UMR8507, SUPELEC UPMC Univ. Paris 06, Univ. Paris-Sud, 11 rue Joliot-Curie, Plateau de Moulon, Gif-sur-Yvette Cedex,91192, France

来源：

Progress In Electromagnetics Research C | 2008年 / 3卷

关键词：

Finite element method - Permittivity - Dielectric materials - Bayesian networks;

D O I：

10.2528/PIERC08030603

中图分类号：

学科分类号：

摘要：

This paper shows the efficiency of neural networks (NN), coupled with the finite element method (FEM), to evaluate the broadband properties of dielectric materials. A characterization protocol is built to characterize dielectric materials and NN are used in order to provide the estimated permittivity. The FEM is used to create the data set required to train the NN. A method based on Bayesian regularization ensures a good generalization capability of the NN. It is shown that NN can determine the permittivity of materials with a high accuracy and that the Bayesian regularization greatly simplifies their implementation. © 2008, Electromagnetics Academy. All rights reserved.

引用

页码：169 / 182

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