Dergiler / Turkish Journal of Electrical Engineering and Computer Science / 2012 / Cilt: 20 - Sayı: Sup.2

A neural-based electromagnetic inverse scattering approach to the detection of a conducting cylinder coated with a dielectric material

Sayfa
1249–1258
Yayın Tarihi
2011-12-01
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

This is an application of the electromagnetic inverse scattering of the objects embedded in a material based on the use of a neural network.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:In this study, a radial basis function neural network approach is applied for the estimation of the localization and the radius of a conducting cylinder with a circular cross-section coated with a dielectric material.
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Temel Bulgular & Veri:RCS values are obtained using 10 different scattering angles that are fed into the network.
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Sonuç & Katkı:This is an application of the electromagnetic inverse scattering of the objects embedded in a material based on the use of a neural network.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Electromagnetic scattering · the method of moment · neural network

Özet

In this study, a radial basis function neural network approach is applied for the estimation of the localization and the radius of a conducting cylinder with a circular cross-section coated with a dielectric material. A set of features, the radar cross-section (RCS) values, are derived from scattered fields, which are calculated using the surface equivalence principle and the method of moment. RCS values are obtained using 10 different scattering angles that are fed into the network. The outputs of the network are the location (x0, y0) and the radius (rp) of the conducting cylinder. This is an application of the electromagnetic inverse scattering of the objects embedded in a material based on the use of a neural network.

Abstract

In this study, a radial basis function neural network approach is applied for the estimation of the localization and the radius of a conducting cylinder with a circular cross-section coated with a dielectric material. A set of features, the radar cross-section (RCS) values, are derived from scattered fields, which are calculated using the surface equivalence principle and the method of moment. RCS values are obtained using 10 different scattering angles that are fed into the network. The outputs of the network are the location (x0, y0) and the radius (rp) of the conducting cylinder. This is an application of the electromagnetic inverse scattering of the objects embedded in a material based on the use of a neural network.

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Bu Makaleye Atıf Yap

MAKAL, S., KIZILAY, A. (2011). A neural-based electromagnetic inverse scattering approach to the detection of a conducting cylinder coated with a dielectric material. Turkish Journal of Electrical Engineering and Computer Science, Cilt: 20 - Sayı: Sup.2, 1249–1258. https://ajindex.com/articles/188973

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