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Erschienen in:
2007 | OriginalPaper | Buchkapitel
An Adaptive Neuro-Fuzzy Inference System for Calculation Resonant Frequency and Input Resistance of Microstrip Dipole Antenna
verfasst von : Siddik C. Basaran, Inayet B. Toprak, Ahmet Yardimci
Erschienen in: Artificial Neural Networks – ICANN 2007
Verlag: Springer Berlin Heidelberg
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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.