Input impedance of rectangular microstrip patch antenna using artificial neural networks

2002 ◽  
Vol 32 (5) ◽  
pp. 381-383 ◽  
Author(s):  
Shyam S. Pattnaik ◽  
Dhruba C. Panda ◽  
S. Devi
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Patch Antenna ◽  
Input Impedance ◽  
Microstrip Patch Antenna ◽  
Microstrip Patch ◽  
Rectangular Microstrip Patch Antenna ◽  
Artificial Neural

scholarly journals Comparison of the Resonant Frequency Determination of a Microstrip Patch Antenna using ANN and Analytical Methods

2017 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Lahcen Aguni ◽  
Samira Chabaa ◽  
Saida Ibnyaich ◽  
Abdelouhab Zeroual
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Dielectric Permittivity ◽  
Resonant Frequency ◽  
Analytical Methods ◽  
Patch Antenna ◽  
Good Argument ◽  
Microstrip Patch ◽  
Rectangular Patch ◽  
Artificial Neural

In this paper we are interested to calculate the resonant frequency of rectangular patch antenna using artificial neural networks based on the multilayered perceptrons. The artificial neural networks built, transforms the inputs which are, the width of the patch W, the length of the patch L, the thickness of the substrate h and the dielectric permittivity to the resonant frequency fr which is an important parameter to design a microstrip patch antenna.The proposed method based on artificial neural networks is compared to some analytical methods using some statistical criteria. The obtained results demonstrate that artificial neural networks are more adequate to achieve the purpose than the other methods and present a good argument with the experimental results available in the literature. Hence, the artificial neural networks can be used by researchers to predict the resonant frequency of a rectangular patch antenna knowing length (L), width (W), thickness (h) and dielectric permittivity with a good accuracy.

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