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
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;
Conference_Titel :
Electromagnetic Compatibility (APEMC), 2010 Asia-Pacific Symposium on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-5621-5
DOI :
10.1109/APEMC.2010.5475720
