DocumentCode
3311564
Title
Neural Network Approach for Solving Boundary Value Problems of Electrodynamics by the R-Functions Method
Author
Basarab, M.
Author_Institution
Bauman Moscow State Tech. Univ., Moscow
Volume
2
fYear
2007
fDate
25-30 June 2007
Firstpage
932
Lastpage
934
Abstract
Application of the RFM GSSs allows one to increase efficiency of training procedures for RBF neural networks. The technique proposed can be applied to solving a wide class of electrodynamics problems, including eigenvalue and nonlinear problems.
Keywords
computational electromagnetics; eigenvalues and eigenfunctions; electrical engineering computing; electrodynamics; neural nets; nonlinear equations; radial basis function networks; R-functions method; RBF neural networks approach; boundary value problems; eigenvalue problems; electrodynamics problems; nonlinear problems; Atomic measurements; Boundary conditions; Boundary value problems; Electrodynamics; Electronic mail; Finite difference methods; Finite volume methods; Neural networks; Partial differential equations; Physics;
fLanguage
English
Publisher
ieee
Conference_Titel
Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves and Workshop on Terahertz Technologies, 2007. MSMW '07. The Sixth International Kharkov Symposium on
Conference_Location
Kharkov
Print_ISBN
1-4244-1237-4
Type
conf
DOI
10.1109/MSMW.2007.4294865
Filename
4294865
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