NEURAL NETWORK BASED ESTIMATION OF RESONANT FREQUENCY OF AN EQUILATERAL TRIANGULAR MICROSTRIP PATCH ANTENNA

Kapusuz K. Y., TORA H., CAN S.

TEHNICKI VJESNIK-TECHNICAL GAZETTE, cilt.20, sa.6, ss.955-960, 2013 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 20 Sayı: 6
  • Basım Tarihi: 2013
  • Dergi Adı: TEHNICKI VJESNIK-TECHNICAL GAZETTE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.955-960
  • Anahtar Kelimeler: microstrip antenna, neural network, resonant frequency, IMPROVED FORMULA, COMPUTATION
  • Ankara Üniversitesi Adresli: Evet

Özet

This study proposes an artificial neural network (ANN) model in order to approximate the resonant frequencies of equilateral triangular patch antennas. The neural network structure applied here is trained and tested for both single-layer and double-layer antennas. It is shown upon experiment that the resonant frequencies obtained from the neural network are both more accurate than the calculated frequencies by formula and satisfactorily close to the measured frequencies. Results appear to be promising as per the available literature. This paper also may offer more efficient approach to developing antennas of such nature. While the total absolute error of 7 MHz and the average error of 0,09 % are achieved for single-layer antenna, the total absolute and average errors are 49 MHz and 0,07 % for the double-layered antenna, respectively.