Artificial neural networks for the narrow aperture dimension calculation of optimum gain pyramidal horns

Guney K., Sarikaya N.

ELECTRICAL ENGINEERING, cilt.86, sa.3, ss.157-163, 2004 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 86 Sayı: 3
  • Basım Tarihi: 2004
  • Doi Numarası: 10.1007/s00202-003-0197-z
  • Dergi Adı: ELECTRICAL ENGINEERING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.157-163
  • Erciyes Üniversitesi Adresli: Evet

Özet

A new method based on artificial neural networks for calculating the narrow aperture dimension of the pyramidal horn is presented. The Levenberg-Marquardt algorithm is used to train the networks. The narrow aperture dimension calculated using artificial neural networks is used in the optimum gain pyramidal horn design. The computed gains of the designed pyramidal horns are in very good agreement with the desired gains.