In this article, a neural network with radial-basis functions (RBF-NN) is applied to microwave imaging of cylinders. Initially, the shape function of the target cylinder is expanded by a Fourier series. The RBF-NN is trained by some direct-scattering data sets and thus can predict the images of the target cylinders.
|Number of pages||6|
|Journal||International Journal of RF and Microwave Computer-Aided Engineering|
|Publication status||Published - 2004 Sep 1|
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Computer Graphics and Computer-Aided Design
- Electrical and Electronic Engineering