DocumentCode
1157535
Title
New iterative inverse scattering algorithms based on neural networks
Author
Lee, Hyuek-Jae ; Ahn, Chang-Hoi ; Park, Cheon-Seok ; Jeong, Bong-Sik ; Lee, Soo-Young
Author_Institution
GoldStar Central Res. Lab., Seoul, South Korea
Volume
30
Issue
5
fYear
1994
fDate
9/1/1994 12:00:00 AM
Firstpage
3641
Lastpage
3643
Abstract
By introducing analogy between electromagnetic field problems and neural network models, new iterative numerical methods are developed for inverse scattering problems. Both recurrent and feedforward neural network architectures are developed, and the validity of the proposed algorithms is demonstrated by computer simulation for small dielectric cylinders
Keywords
digital simulation; electrical engineering computing; electromagnetic fields; electromagnetic wave scattering; feedforward neural nets; inverse problems; iterative methods; recurrent neural nets; electromagnetic field problems; feedforward neural network; inverse scattering algorithms; iterative numerical methods; neural networks; recurrent neural network; small dielectric cylinders; Computer architecture; Electromagnetic fields; Electromagnetic modeling; Feedforward neural networks; Inverse problems; Iterative algorithms; Iterative methods; Neural networks; Numerical models; Recurrent neural networks;
fLanguage
English
Journal_Title
Magnetics, IEEE Transactions on
Publisher
ieee
ISSN
0018-9464
Type
jour
DOI
10.1109/20.312729
Filename
312729
Link To Document