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Inverse scattering of dielectric cylinders by using radial basis function neural networks

✍ Scribed by Rekanos, Ioannis T.

Book ID
118662536
Publisher
American Geophysical Union
Year
2001
Tongue
English
Weight
710 KB
Volume
36
Category
Article
ISSN
0048-6604

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📜 SIMILAR VOLUMES

On-line inverse scattering of conducting
On-line inverse scattering of conducting cylinders using radial basis-function neural networks
✍ Ioannis T. Rekanos 📂 Article 📅 2001 🏛 John Wiley and Sons 🌐 English ⚖ 134 KB 👁 1 views

A no¨el on-line in¨erse-scattering method for the geometric characterization of conducting cylindrical scatterers from scatteredfield measurements is presented. The method is based on the application of radial basis-function neural networks that are constructed by use of the orthogonal least squares

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✍ Ulaş Aşık; Tayfun Günel; Işın Erer 📂 Article 📅 2004 🏛 John Wiley and Sons 🌐 English ⚖ 149 KB

## Abstract A new approach, based on the radial‐bias function neural network (RBF‐NN) combined with wavelet transform, is presented for the estimation of the locations and radii of conducting cylindrical scatterers. The discrete wavelet transform coefficients of the electric‐field values scattered