DocumentCode
2514578
Title
Permeability extracting using GRNN method
Author
Zhang, Li ; Lu, Guizhen ; Qi, Yong
Author_Institution
Dept. of Commun. Eng., Commun. Univ. of China, Beijing, China
fYear
2010
fDate
12-16 April 2010
Firstpage
1657
Lastpage
1659
Abstract
A new method for measuring complex permeability (μ) is presented in this paper, which uses generalized regression neural network (GRNN) method. The GRNN is used to solve the problem of parameters extraction. The GRNN is trained by a large number of permeability values of the material which is obtained by using transmission line theory. Finally, the obtained neural network is used to predict the permeability of the material. The predicted results demonstrate the efficiency of the proposed approach.
Keywords
electrical engineering computing; magnetic permeability measurement; neural nets; regression analysis; transmission line theory; GRNN method; complex permeability measurement; generalized regression neural network; permeability extraction; transmission line theory; Artificial neural networks; Electromagnetic devices; Frequency; Inverse problems; Neural networks; Neurons; Permeability; Scattering parameters; Transmission line measurements; Transmission line theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Electromagnetic Compatibility (APEMC), 2010 Asia-Pacific Symposium on
Conference_Location
Beijing
Print_ISBN
978-1-4244-5621-5
Type
conf
DOI
10.1109/APEMC.2010.5475720
Filename
5475720
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