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

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15 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)398-403
Number of pages6
JournalInternational Journal of RF and Microwave Computer-Aided Engineering
Issue number5
Publication statusPublished - 2004 Sept

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering


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