DocumentCode :
3087903
Title :
Radial Basis Function Neural Networks for Filling the MoM Impedance Matrix
Author :
Zainud-Deen, S.H. ; Ibrahim, I.I. ; Ibrahem, Sabry M M ; Hassan, A.S.
Author_Institution :
Fac. of Electron. Eng., Menoufia Univ.
Volume :
0
fYear :
2006
fDate :
14-16 March 2006
Firstpage :
1
Lastpage :
8
Abstract :
In this paper radial basis function neural network (RBF-NN) used for filling the method of moments (MoM) impedance matrix of several configuration of wire antennas. Four radial basis function neural networks (RBF-NNs) are trained to calculate the impedances of two elements consist of four monopoles. The mutual impedance between the two elements is the sum of outputs of the four RBF-NNs. The RBF-NN model is applied to the analysis of the straight dipole, two element array, circular array, wire-grid corner reflector, square loop, and square spiral antenna
Keywords :
antenna radiation patterns; electric impedance; electrical engineering computing; impedance matrix; method of moments; monopole antenna arrays; radial basis function networks; wire antennas; MoM impedance matrix; RBF-NN; method of moment; mutual impedance; radial basis function neural network; wire antenna; Antenna arrays; Dipole antennas; Equations; Filling; Frequency; Impedance; Radial basis function networks; Shape; Spirals; Transmission line matrix methods;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Radio Science Conference, 2006. NRSC 2006. Proceedings of the Twenty Third National
Conference_Location :
Menoufiya
Print_ISBN :
977-5031-84-2
Electronic_ISBN :
977-5031-84-2
Type :
conf
DOI :
10.1109/NRSC.2006.386319
Filename :
4275116
Link To Document :
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