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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) Perfecting a Video Game with Game Metrics
Samira Chabaa
Ibn Zohr University
Computer Science & IT

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Comparison of the Resonant Frequency Determination of a Microstrip Patch Antenna using ANN and Analytical Methods Lahcen Aguni; Samira Chabaa; Saida Ibnyaich; Abdelouhab Zeroual
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 6, No 1: April 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (765.67 KB) | DOI: 10.11591/ijict.v6i1.pp1-9

Abstract

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.
Predicting the notch band frequency of an ultra-wideband antenna using artificial neural networks Lahcen Aguni; Samira Chabaa; Saida Ibnyaich; Abdelouhab Zeroual
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i1.15912

Abstract

In this paper we propose to predict the notch frequency of an ultra-wideband (UWB) antenna which operates in the frequency band from 3.85 GHz to 12.38 GHz. The prediction of the notch frequency in order to avoid interferences between (WLAN) IEEE802.11a and HIPERLAN/2 WLAN applications and UWB technology is achieved using the artificial neural networks (ANN) technique. The developed ANN is optimized with the help of K-fold cross validation method which allows us to divide the datasets into 10 subsets in the training phase. The simulated datasets are generated by controlling high frequency structural simulator (HFSS) from MATLAB using a VB script. The performance of the ANN technique is assessed using some statistical criteria. During the training process, the mean absolute percentage error (MAPE) between the simulated and the predicted ANN notch frequencies is 0,125. A comparison between simulated, theoretical, and ANN results has been achieved during the test and validation process, good accuracy is obtained between the simulated and the ANN predictions. The proposed UWB antenna exhibits a notch band from 5.1 GHz to 6.0 GHz with a notch frequency of approximately 5.51 GHz.
Co-Authors Abdelouhab Zeroual Abdelouhab Zeroual Lahcen Aguni Saida Ibnyaich