𝔖 Bobbio Scriptorium
✦   LIBER   ✦

A neural network approach to the microwave inverse scattering problem with edge-preserving regularization

✍ Scribed by Gong, Xing; Wang, Yuanmei

Book ID
118662522
Publisher
American Geophysical Union
Year
2001
Tongue
English
Weight
772 KB
Volume
36
Category
Article
ISSN
0048-6604

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Optimization approach with edge-preservi
Optimization approach with edge-preserving regularization to time domain 1D inverse scattering
✍ Hiromi Yoshida; Toshiyuki Tanaka; Takashi Takenaka 📂 Article 📅 2001 🏛 John Wiley and Sons 🌐 English ⚖ 203 KB

## Abstract The electromagnetic inverse scattering problems are in general ill‐conditioned, so that image reconstruction becomes unstable when noise exists or when the number of unknown parameters is increased. Usually, regularization is required. However, when regularization is applied, the high‐f

A neural-network approach to the inverse
A neural-network approach to the inverse-scattering problem from a circular conducting cylindrical scatterer
✍ A-K. Hamid 📂 Article 📅 1996 🏛 John Wiley and Sons 🌐 English ⚖ 208 KB 👁 2 views

A nertral-neh~orh approucli is riei.ekiped to itiwstigate tl7e irii,erse ~caftt'rrti,y from a perfectlv coridrrcring circular d i n d e r due to a normal field incidence. The neural network, is itsed to predict the electrical radius ka of ( I circular cylinder h\ rewi enng the coinp1e.u coefficients

A wavelet-based radial-basis function ne
A wavelet-based radial-basis function neural network approach to the inverse scattering of conducting cylinders
✍ 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