Abstract
In this study, an artificial neural network (ANN) model has been implemented to predict the notch band frequency of an Ultra Wide Band (UWB) antenna. The structure of the proposed ANN model is obtained by varying the ANN parameters such as number of layers, number of neurons, and training algorithm and also by observing the statistical criteria Root Mean Squared Error (RMSE). In term of the regression coefficient R, the obtained value is about 0.98, which indicates that the predicted notch band frequency is good either in the training phase or in the test phase. The reflection coefficient result of the proposed UWB antenna indicates a notch band from 5.1 GHz to 6 GHz with a simulated notch frequency similar to the predicted one.
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Aguni, L., Chabaa, S., Ibnyaich, S., Zeroual, A. (2020). Implementing an ANN Model to Predict the Notch Band Frequency of an UWB Antenna. In: Hamlich, M., Bellatreche, L., Mondal, A., Ordonez, C. (eds) Smart Applications and Data Analysis. SADASC 2020. Communications in Computer and Information Science, vol 1207. Springer, Cham. https://doi.org/10.1007/978-3-030-45183-7_18
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DOI: https://doi.org/10.1007/978-3-030-45183-7_18
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