An adaptive neuro-fuzzy inference system for calculation resonant frequency and input resistance of microstrip dipole antenna

BAŞARAN S. C., TOPRAK İ. B., YARDIMCI A.

17th International Conference on Artificial Neural Networks (ICANN 2007), Oporto, Portekiz, 9 - 13 Eylül 2007, cilt.4669, ss.709-710 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 4669
  • Doi Numarası: 10.1007/978-3-540-74695-9_73
  • Basıldığı Şehir: Oporto
  • Basıldığı Ülke: Portekiz
  • Sayfa Sayıları: ss.709-710
  • Anahtar Kelimeler: microstrip dipole antenna, ANFIS, resonance frequency, input resistance
  • Akdeniz Üniversitesi Adresli: Evet

Özet

The accurate calculation of the resonance frequency and input resistance of microstrip antennas is a key factor to guarantee their correct behavior. In this paper we presented an adaptive neuro-fuzzy inference system (ANFIS) that calculates resonant frequency and input impedance of the microstrip dipole antenna's (MSDAs). Although the MSDAs' resonant frequency greatly depends on the dipole's length, it also depends on the dipole's width, the antenna substrate's permittivity value, and its size (which affects resonant frequency). Input impedance, like resonant frequency, changes with these parameters. According to test results accuracy of ANFIS is calculated 98.91 % for resonant frequency while 95.81 % for input resistance calculation.