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Sophisticated Electromagnetic Forward Scattering Solver via Deep Learning

Af: Yinpeng Wang, Qiang Ren, Yongzhong Li, Shutong Qi Engelsk Paperback

Sophisticated Electromagnetic Forward Scattering Solver via Deep Learning

Af: Yinpeng Wang, Qiang Ren, Yongzhong Li, Shutong Qi Engelsk Paperback
Tjek vores konkurrenters priser
This book investigates in detail the deep learning (DL) techniques in electromagnetic (EM) near-field scattering problems, assessing its potential to replace traditional numerical solvers in real-time forecast scenarios. Studies on EM scattering problems have attracted researchers in various fields, such as antenna design, geophysical exploration and remote sensing. Pursuing a holistic perspective, the book introduces the whole workflow in utilizing the DL framework to solve the scattering problems. To achieve precise approximation, medium-scale data sets are sufficient in training the proposed model. As a result, the fully trained framework can realize three orders of magnitude faster than the conventional FDFD solver. It is worth noting that the 2D and 3D scatterers in the scheme can be either lossless medium or metal, allowing the model to be more applicable. This book is intended for graduate students who are interested in deep learning with computational electromagnetics, professional practitioners working on EM scattering, or other corresponding researchers.
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This book investigates in detail the deep learning (DL) techniques in electromagnetic (EM) near-field scattering problems, assessing its potential to replace traditional numerical solvers in real-time forecast scenarios. Studies on EM scattering problems have attracted researchers in various fields, such as antenna design, geophysical exploration and remote sensing. Pursuing a holistic perspective, the book introduces the whole workflow in utilizing the DL framework to solve the scattering problems. To achieve precise approximation, medium-scale data sets are sufficient in training the proposed model. As a result, the fully trained framework can realize three orders of magnitude faster than the conventional FDFD solver. It is worth noting that the 2D and 3D scatterers in the scheme can be either lossless medium or metal, allowing the model to be more applicable. This book is intended for graduate students who are interested in deep learning with computational electromagnetics, professional practitioners working on EM scattering, or other corresponding researchers.
Produktdetaljer
Sprog: Engelsk
Sider: 125
ISBN-13: 9789811662638
Indbinding: Paperback
Udgave:
ISBN-10: 9811662630
Udg. Dato: 21 okt 2022
Længde: 0mm
Bredde: 155mm
Højde: 235mm
Forlag: Springer Verlag, Singapore
Oplagsdato: 21 okt 2022
Forfatter(e) Yinpeng Wang, Qiang Ren, Yongzhong Li, Shutong Qi


Kategori Mikrobølgeteknologi


ISBN-13 9789811662638


Sprog Engelsk


Indbinding Paperback


Sider 125


Udgave


Længde 0mm


Bredde 155mm


Højde 235mm


Udg. Dato 21 okt 2022


Oplagsdato 21 okt 2022


Forlag Springer Verlag, Singapore

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