Skip to Main content Skip to Navigation
Journal articles

Determination of thickness and permeability tensor using the combination (models-neural networks)

Fatima Djerfaf 1 Didier Vincent 2 Stéphane Robert 2 Abdelaziz Merzouki 3
1 Université Amar Telidji - Laghouat
2 LHC - Laboratoire Hubert Curien [Saint Etienne]
3 UFAS1 - Université Ferhat-Abbas Sétif 1 [Sétif]
Abstract : The purpose of this paper is to describe an improved microwave method for predicting the material’s thickness and the saturation magnetization and the damping factor through the neural networks. These characteristics provide the permeability tensor components using the combination between theoretical models and neural network. Neural networks learn the relationship between the scattering parameters and the outputs. The networks’ performances result from both simulation and measurement thin ferrite samples.
Keywords : neural network Permeability tensors
Document type :
Journal articles
Complete list of metadata
https://hal-ujm.archives-ouvertes.fr/ujm-01390559
Contributor : Stéphane Robert Connect in order to contact the contributor
Submitted on : Wednesday, November 2, 2016 - 10:55:11 AM
Last modification on : Thursday, December 9, 2021 - 3:13:14 AM

Links full text

istex

Identifiers

Collections

UNIV-ST-ETIENNE | CNRS | LAHC | PARISTECH | IOGS | UDL

Citation

Fatima Djerfaf, Didier Vincent, Stéphane Robert, Abdelaziz Merzouki. Determination of thickness and permeability tensor using the combination (models-neural networks). European Physical Journal: Applied Physics, EDP Sciences, 2015, 70 (2), pp.20601. ⟨10.1051/epjap/2015140333⟩. ⟨ujm-01390559⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Les métriques sont temporairement indisponibles