Modeling frequency reconfigurable antenna array using neural networks

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


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
Issue number4
Publication statusPublished - 20 Feb 2005


  • 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


Dive into the research topics of 'Modeling frequency reconfigurable antenna array using neural networks'. Together they form a unique fingerprint.

Cite this