MICROWAVE CHARACTERIZATION OF DIELECTRIC MATERIALS USING BAYESIAN NEURAL NETWORKS | Zendy

Hulusi Açikgöz | Zendy; Yann Le Bihan | Zendy; O. Meyer | Zendy; Lionel Pichon | Zendy

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MICROWAVE CHARACTERIZATION OF DIELECTRIC MATERIALS USING BAYESIAN NEURAL NETWORKS

Author(s) -

Hulusi Açikgöz,

Yann Le Bihan,

O. Meyer,

Lionel Pichon

Publication year - 2008

Publication title -

progress in electromagnetics research c

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.341

H-Index - 34

ISSN - 1937-8718

DOI - 10.2528/pierc08030603

Subject(s) - characterization (materials science) , artificial neural network , bayesian probability , microwave , dielectric , materials science , bayesian network , computer science , biological system , artificial intelligence , optoelectronics , nanotechnology , biology , telecommunications

This paper shows the efficiency of neural networks (NN), coupled with the finite element method (FEM), to evaluate the broad- band 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.

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