Abstract
A neural network approach is presented to estimate the backscattering cross section for the scattering by a spherical shell with a circular aperture due to a normal incidence field using the radial basis function (RBF) network. The main idea of the proposed approach is to train the RBF network to model the nonlinear relationship between the electrical radius, half aperture angle, and the back scattering cross section using experimental data. Once the network is trained, it can be used to predict the backscattering cross section of a spherical shell with electrical radius and half aperture angle different from those used for training.
| Original language | English |
|---|---|
| Pages (from-to) | 1840-1843 |
| Number of pages | 4 |
| Journal | IEEE Antennas and Propagation Society, AP-S International Symposium (Digest) |
| Volume | 3 |
| State | Published - 1996 |
ASJC Scopus subject areas
- Electrical and Electronic Engineering