An Efficient Algorithm for EM Scattering from Anatomically Realistic Human Head Model Using Parallel CG-FFT Method
An efficient algorithm is proposed to analyze the electromagnetic scattering problem from a high resolution head model with pixel data format. The algorithm is based on parallel technique and the conjugate gradient (CG) method combined with the fast Fourier transform (FFT). Using the parallel CG-FFT...
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Format: | Article |
Language: | English |
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Wiley
2014-01-01
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Series: | International Journal of Antennas and Propagation |
Online Access: | http://dx.doi.org/10.1155/2014/495057 |
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author | Lei Zhao Gen Chen |
author_facet | Lei Zhao Gen Chen |
author_sort | Lei Zhao |
collection | DOAJ |
description | An efficient algorithm is proposed to analyze the electromagnetic scattering problem from a high resolution head model with pixel data format. The algorithm is based on parallel technique and the conjugate gradient (CG) method combined with the fast Fourier transform (FFT). Using the parallel CG-FFT method, the proposed algorithm is very efficient and can solve very electrically large-scale problems which cannot be solved using the conventional CG-FFT method in a personal computer. The accuracy of the proposed algorithm is verified by comparing numerical results with analytical Mie-series solutions for dielectric spheres. Numerical experiments have demonstrated that the proposed method has good performance on parallel efficiency. |
format | Article |
id | doaj-art-622951f5a2c047748893c612439315a6 |
institution | Kabale University |
issn | 1687-5869 1687-5877 |
language | English |
publishDate | 2014-01-01 |
publisher | Wiley |
record_format | Article |
series | International Journal of Antennas and Propagation |
spelling | doaj-art-622951f5a2c047748893c612439315a62025-02-03T06:00:15ZengWileyInternational Journal of Antennas and Propagation1687-58691687-58772014-01-01201410.1155/2014/495057495057An Efficient Algorithm for EM Scattering from Anatomically Realistic Human Head Model Using Parallel CG-FFT MethodLei Zhao0Gen Chen1Center for Computational Science and Engineering, School of Mathematics and Statistics, Jiangsu Normal University, Xuzhou 221116, ChinaCenter for Computational Science and Engineering, School of Mathematics and Statistics, Jiangsu Normal University, Xuzhou 221116, ChinaAn efficient algorithm is proposed to analyze the electromagnetic scattering problem from a high resolution head model with pixel data format. The algorithm is based on parallel technique and the conjugate gradient (CG) method combined with the fast Fourier transform (FFT). Using the parallel CG-FFT method, the proposed algorithm is very efficient and can solve very electrically large-scale problems which cannot be solved using the conventional CG-FFT method in a personal computer. The accuracy of the proposed algorithm is verified by comparing numerical results with analytical Mie-series solutions for dielectric spheres. Numerical experiments have demonstrated that the proposed method has good performance on parallel efficiency.http://dx.doi.org/10.1155/2014/495057 |
spellingShingle | Lei Zhao Gen Chen An Efficient Algorithm for EM Scattering from Anatomically Realistic Human Head Model Using Parallel CG-FFT Method International Journal of Antennas and Propagation |
title | An Efficient Algorithm for EM Scattering from Anatomically Realistic Human Head Model Using Parallel CG-FFT Method |
title_full | An Efficient Algorithm for EM Scattering from Anatomically Realistic Human Head Model Using Parallel CG-FFT Method |
title_fullStr | An Efficient Algorithm for EM Scattering from Anatomically Realistic Human Head Model Using Parallel CG-FFT Method |
title_full_unstemmed | An Efficient Algorithm for EM Scattering from Anatomically Realistic Human Head Model Using Parallel CG-FFT Method |
title_short | An Efficient Algorithm for EM Scattering from Anatomically Realistic Human Head Model Using Parallel CG-FFT Method |
title_sort | efficient algorithm for em scattering from anatomically realistic human head model using parallel cg fft method |
url | http://dx.doi.org/10.1155/2014/495057 |
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