DocumentCode
329122
Title
An inverse-problem analysis of magnetopneumography with RBFN
Author
Sued, Yoshiko ; Kotani, A. Makoto ; Aihara, Kazuyuki
Author_Institution
Dept. of Electron. Eng., Tokyo Denki Univ., Japan
Volume
2
fYear
1993
fDate
25-29 Oct. 1993
Firstpage
2005
Abstract
In this paper, we analyze the inverse problem of magnetopneumography (the magnetic field pattern produced from the lung) by radial basis function networks (RBFN) with smoothing ability. We show that radial basis function is naturally derived by calculation of the magnetic fields and RBFN composes of elements with such output function that is useful for the inverse problem of magnetopneumography.
Keywords
feedforward neural nets; inverse problems; lung; magnetic fields; medical computing; pattern recognition; pneumodynamics; inverse-problem analysis; lung; magnetic field pattern; magnetopneumography; pneumodynamics; radial basis function networks; Humans; Inverse problems; Lungs; Magnetic analysis; Magnetic field measurement; Particle measurements; Radial basis function networks; Smoothing methods; X-ray detection; X-ray detectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
Print_ISBN
0-7803-1421-2
Type
conf
DOI
10.1109/IJCNN.1993.717051
Filename
717051
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