Modeling frequency reconfigurable antenna array using neural networks

Amalendu Patnaik, Dimitrios Anagnostou, Christos G. Christodoulou, James C. Lyke

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

In order to avoid the computational complexities involved in analyzing reconfigurable antennas, neural networks are used as an alternate approach. The neural network finds the location of the operational frequency hands for any combination of switches connecting different radiating elements. The network outputs are compared with the experimentally measured results.

Original languageEnglish
Pages (from-to)351-354
Number of pages4
JournalMicrowave and Optical Technology Letters
Volume44
Issue number4
DOIs
Publication statusPublished - 20 Feb 2005

Keywords

  • Antenna array
  • MEMS
  • Neural networks
  • Reconfigurable antennas

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Condensed Matter Physics
  • Electrical and Electronic Engineering

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