In numericalexamples, Scattered fields are applied trained NN, outputs of NN are compared the exact profiles andgood reconstructions are observed.
📌 3 Key Takeaways
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Objective & Hypothesis:In this paper, Neural Network (NN) is used for profile reconstruction of dielectric constant of thecylinder.
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Key Findings & Data:The region is assumed to be filled with dielectric medium of which dielectric constantchanges along the radial direction.
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Conclusion & Impact:In numericalexamples, Scattered fields are applied trained NN, outputs of NN are compared the exact profiles andgood reconstructions are observed.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters
Abstract
In this paper, Neural Network (NN) is used for profile reconstruction of dielectric constant of thecylinder. The region is assumed to be filled with dielectric medium of which dielectric constantchanges along the radial direction. Radial variation of dielectric constant is represented by Fourierseries. Scattered fields, which are obtained by numerically Method of Moments (MoM) technique, andFourier coefficients are used for training the NN as inputs and outputs respectively. In numericalexamples, Scattered fields are applied trained NN, outputs of NN are compared the exact profiles andgood reconstructions are observed.
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Cite This Article
TEZEL, N. S. (2022). One dimensional profile reconstruction of dielectric cylinder by using neural network. Istanbul University Journal of Electrical and Electronics Engineering, Cilt: 9 - Sayı: 1, 797–800. https://ajindex.com/articles/543739
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