A neural-network-based model for 2D microwave imaging of cylinders

International Journal of RF and Microwave Computer-Aided Engineering

Volumn 14, Issue 5, 2004, Pages 398-403

  Lee, Kun Chou ^a  

^a NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

Author keywords

Microwave imaging; Neural network; Radial basis function

Indexed keywords

COMPUTER SIMULATION; DATA REDUCTION; DIELECTRIC MATERIALS; FOURIER TRANSFORMS; IMAGING SYSTEMS; MATHEMATICAL MODELS; NONLINEAR SYSTEMS; RADIAL BASIS FUNCTION NETWORKS; REGRESSION ANALYSIS;

DIELECTRIC CYLINDERS; FOURIER SERIES COEFFICIENTS; MICROWAVE IMAGING; NONLINEAR MAPPING;

MICROWAVE DEVICES;

EID: 4444235768     PISSN: 10964290     EISSN: None     Source Type: Journal    
DOI: 10.1002/mmce.20026     Document Type: Article

References (19)

1. Simon Haykin, Neural networks: Comprehensive foundation, Prentice-Hall, New Jersey, 1999.
2. C. Christodoulous and M. Georgiopoulos, Applications of neural networks in electromagnetics, Artech House, Boston, 2001.
3. Q.J. Zhang and K.C. Gupta, Neural networks for RF and microwave design, Artech House, Boston, 2000.
4. S.R.H. Hoole, Artificial neural networks in the solution of inverse electromagnetic field problems, IEEE Trans Magnetics 29 (1992), 1931-1934.
5. E. Coccorese, R. Martone, and F.C. Morabito, A neural network approach for the solution of electric and magnetic inverse problems, IEEE Trans Magnetics 30 (1993), 2829-2839.
6. I. Elshafiey, L. Udpa, and S.S. Udpa, Application of neural networks to inverse problems in electromagnetics, IEEE Trans Magnetics 31 (1993), 3629-3632.
7. B.S. Jeong, C.H. Ahn, C.S. Park, H.J. Lee, and S.Y. Lee, New iterative inverse scattering algorithms based on neural networks, IEEE Trans Magnetics 31 (1993), 3641-3643.
8. I. Elshafiey, L. Udpa, S.S. Udpa, Solution of inverse problems in electromagnetics using Hopfield neural networks, IEEE Trans Magnetics 31 (1994), 852-861.
9. S. Caorsi and P. Gamba, Electromagnetic detection of dielectric cylinders by a neural network approach, IEEE Trans Geosci Remote Sensing 37 (1999), 820-827.
10. I.T. Rekanos, On-line inverse scattering of conducting cylinders using radial basis-function neural networks, Microwave Opt Technol Lett 28 (2001), 378-380.
11. I.T. Rekanos, Inverse scattering of dielectric cylinders by using radial basis function neural networks, Radio Sci 36 (2001), 841-849.
12. I.T. Rekanos, Neural-network-based inverse-scattering technique for online microwave medical imaging, IEEE Trans Magnetics 38 (2002), 1061-1064.
13. R.F. Harrington, Field computation by moment methods, Macmillan, New York, 1968.
14. D.F. Specht, A general regression neural network, IEEE Trans Neural Networks 2 (1991), 568-576.
15. J.H. Richmond, Scattering by a dielectric cylinder of arbitrary cross section shape, IEEE Trans Antenna Propagat 13 (1965), 334-341.
16. R.M. Lewis, Physicalal optics inverse diffraction, IEEE Trans Antenna Propagat 17 (1969), 308-314.
17. N.N. Bojarski, A survey of the physical optics inverse scattering identity, IEEE Trans Antenna Propagat 30 (1982), 980-989.
18. R.M. Lewis, Physical optics inverse diffraction, IEEE Trans Antenna Propagat 17 (1969), 308-314.
19. K.C. Lee, Mutual coupling analyses of antenna arrays by neural network models with radial basis functions, J Electromagn Waves Applic 17 (2003), 1217-1223.