Machine-Learning Classification of Closed and Open Radiating Wires from Near Magnetic or Electric Field Scan Images

Amir Geranmayeh

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arXiv · 2104.09277

Machine-Learning Classification of Closed and Open Radiating Wires from Near Magnetic or Electric Field Scan Images

Amir Geranmayeh

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Abstract

Sets of intelligent classifiers are applied to the near-field scan-data in order to automatically classify the shape of radiating wirings. The support vector machine, k-nearest neighbors algorithm, and Gaussian process classifications are trained using the near-field radiation pattern of diverse radiating wire configurations. Leave-one-out cross-validation is used for estimating the performance of the predictive models. The output of this research is a software package well-suited to be retrained based on any measured near-field databank to automate the identification of magnetic-type or electric-type of the radiating coupling sources.

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Amir Geranmayeh. 2021-03-16. Machine-Learning Classification of Closed and Open Radiating Wires from Near Magnetic or Electric Field Scan Images. https://arxiv.org/abs/2104.09277

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