Data Mining Techniques in Artificial Neural Network for UWB Antenna Design
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With data mining techniques for the preprocessing of training patterns, an artificial neural network (ANN) model is proposed for parametric modeling of electromagnetic behavior of ultrawide band (UWB) antennas in this paper. In this ANN method, two data mining techniques, including correlation analysis and data classification based on support vector machine (SVM), are employed to determine geometrical variable inputs and classify the inputs during the training and testing processes. Compared with the traditional ANN, the proposed model with data mining can achieve the trained model with small training datasets and accurate results. The validity and efficiency of this proposed method are confirmed with two band-notched UWB antenna examples.
KeywordsArtificial neural network (ANN), data mining, pole-residue-based transfer function (TF), support vector machine (SVM), ultrawide band (UWB) antenna
Document typePeer reviewed
Document versionFinal PDF
SourceRadioengineering. 2018 vol. 27, č. 1, s. 70-78. ISSN 1210-2512
- 2018/1