IEEE Transactions on Antennas and Propagation最新文献

Novel Numerical Basis Sets for Electromagnetic Field Expansion in Arbitrary Inhomogeneous Objects 任意非均匀物体电磁场展开的新的数值基集

IF 5.7 1区计算机科学

IEEE Transactions on Antennas and Propagation Pub Date : 2022-03-30 DOI: 10.1109/TAP.2022.3177566

Ioannis P. Georgakis;Jorge Fernández Villena;Athanasios G. Polimeridis;Riccardo Lattanzi

{"title":"Novel Numerical Basis Sets for Electromagnetic Field Expansion in Arbitrary Inhomogeneous Objects","authors":"Ioannis P. Georgakis;Jorge Fernández Villena;Athanasios G. Polimeridis;Riccardo Lattanzi","doi":"10.1109/TAP.2022.3177566","DOIUrl":"10.1109/TAP.2022.3177566","url":null,"abstract":"We investigated how to construct low-order subspace basis sets to accurately represent electromagnetic (EM) fields generated within inhomogeneous arbitrary objects by radio frequency sources external to Huygen’s surface. The basis generation relies on the singular value decomposition of Green’s functions integrodifferential operators, which makes it feasible to derive a reduced-order yet stable model. We present a detailed study of the theoretical and numerical requisites for generating such basis and show how it can be used to calculate performance limits in magnetic resonance imaging applications. Finally, we propose a novel numerical framework for the computation of characteristic modes of arbitrary inhomogeneous objects. We validated accuracy and convergence properties of the numerical basis against a complete analytical basis in the case of a uniform spherical object. We showed that the discretization of Huygens’s surface has a minimal effect on the accuracy of the calculations, which mainly depends on the EM solver resolution and order of approximation.","PeriodicalId":13102,"journal":{"name":"IEEE Transactions on Antennas and Propagation","volume":"70 9","pages":"8227-8241"},"PeriodicalIF":5.7,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10147338/pdf/nihms-1841694.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10125449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A Butterfly-Accelerated Volume Integral Equation Solver for Broad Permittivity and Large-Scale Electromagnetic Analysis 用于宽介电常数和大规模电磁分析的蝶形加速体积积分方程求解器

IF 5.7 1区计算机科学

IEEE Transactions on Antennas and Propagation Pub Date : 2021-12-28 DOI: 10.1109/TAP.2021.3137193

Sadeed Bin Sayed;Yang Liu;Luis J. Gomez;Abdulkadir C. Yucel

{"title":"A Butterfly-Accelerated Volume Integral Equation Solver for Broad Permittivity and Large-Scale Electromagnetic Analysis","authors":"Sadeed Bin Sayed;Yang Liu;Luis J. Gomez;Abdulkadir C. Yucel","doi":"10.1109/TAP.2021.3137193","DOIUrl":"10.1109/TAP.2021.3137193","url":null,"abstract":"A butterfly-accelerated volume integral equation (VIE) solver is proposed for fast and accurate electromagnetic (EM) analysis of scattering from heterogeneous objects. The proposed solver leverages the hierarchical off-diagonal butterfly (HOD-BF) scheme to construct the system matrix and obtain its approximate inverse, used as a preconditioner. Complexity analysis and numerical experiments validate the \u0000<inline-formula> <tex-math>$O(Nlog ^{2}N)$ </tex-math></inline-formula>\u0000 construction cost of the HOD-BF-compressed system matrix and \u0000<inline-formula> <tex-math>$O(N^{1.5}log N)$ </tex-math></inline-formula>\u0000 inversion cost for the preconditioner, where \u0000<inline-formula> <tex-math>$N$ </tex-math></inline-formula>\u0000 is the number of unknowns in the high-frequency EM scattering problem. For many practical scenarios, the proposed VIE solver requires less memory and computational time to construct the system matrix and obtain its approximate inverse compared to a \u0000<inline-formula> <tex-math>$mathcal {H}$ </tex-math></inline-formula>\u0000 matrix-accelerated VIE solver. The accuracy and efficiency of the proposed solver have been demonstrated via its application to the EM analysis of large-scale canonical and real-world structures comprising of broad permittivity values and involving millions of unknowns.","PeriodicalId":13102,"journal":{"name":"IEEE Transactions on Antennas and Propagation","volume":"70 5","pages":"3549-3559"},"PeriodicalIF":5.7,"publicationDate":"2021-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9205442/pdf/nihms-1804470.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9436678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Dielectric Breast Phantoms by Generative Adversarial Network 利用世代对抗网络研究介电性乳腺癌

IF 5.7 1区计算机科学

IEEE Transactions on Antennas and Propagation Pub Date : 2021-10-26 DOI: 10.1109/TAP.2021.3121149

Wenyi Shao;Beibei Zhou

{"title":"Dielectric Breast Phantoms by Generative Adversarial Network","authors":"Wenyi Shao;Beibei Zhou","doi":"10.1109/TAP.2021.3121149","DOIUrl":"10.1109/TAP.2021.3121149","url":null,"abstract":"In order to conduct the research of machine learning (ML)-based microwave breast imaging (MBI), a large number of digital dielectric breast phantoms that can be used as training data (ground truth) are required but are difficult to be achieved from practice. Although a few dielectric breast phantoms have been developed for research purpose, the number and the diversity are limited and are far inadequate to develop a robust ML algorithm for MBI. This article presents a neural network method to generate 2-D virtual breast phantoms that are similar to the real ones, which can be used to develop ML-based MBI in the future. The generated phantoms are similar but are different from those used in training. Each phantom consists of several images with each representing the distribution of a dielectric parameter in the breast map. A statistical analysis was performed over 10 000 generated phantoms to investigate the performance of the generative network. With the generative network, one may generate an unlimited number of breast images with more variations, so the ML-based MBI will be more ready to deploy.","PeriodicalId":13102,"journal":{"name":"IEEE Transactions on Antennas and Propagation","volume":"70 8","pages":"6256-6264"},"PeriodicalIF":5.7,"publicationDate":"2021-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10038476/pdf/nihms-1835327.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10292120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Compression of Volume-Surface Integral Equation Matrices via Tucker Decomposition for Magnetic Resonance Applications 磁共振应用中体表面积分方程矩阵的Tucker分解压缩

IF 5.7 1区计算机科学

IEEE Transactions on Antennas and Propagation Pub Date : 2021-06-25 DOI: 10.1109/TAP.2021.3090835

Ilias I. Giannakopoulos;Georgy D. Guryev;José E. C. Serrallés;Ioannis P. Georgakis;Luca Daniel;Jacob K. White;Riccardo Lattanzi

{"title":"Compression of Volume-Surface Integral Equation Matrices via Tucker Decomposition for Magnetic Resonance Applications","authors":"Ilias I. Giannakopoulos;Georgy D. Guryev;José E. C. Serrallés;Ioannis P. Georgakis;Luca Daniel;Jacob K. White;Riccardo Lattanzi","doi":"10.1109/TAP.2021.3090835","DOIUrl":"10.1109/TAP.2021.3090835","url":null,"abstract":"In this work, we propose a method for the compression of the coupling matrix in volume-surface integral equation (VSIE) formulations. VSIE methods are used for electromagnetic (EM) analysis in magnetic resonance imaging (MRI) applications, for which the coupling matrix models the interactions between the coil and the body. We showed that these effects can be represented as independent interactions between remote elements in 3-D tensor formats, and subsequently decomposed with the Tucker model. Our method can work in tandem with the adaptive cross approximation (ACA) technique to provide fast solutions of VSIE problems. We demonstrated that our compression approaches can enable the use of VSIE matrices of prohibitive memory requirements, by allowing the effective use of modern graphical processing units (GPUs) to accelerate the arising matrix-vector products. This is critical to enable numerical MRI simulations at clinical voxel resolutions in a feasible computation time. In this article, we demonstrate that the VSIE matrix-vector products needed to calculate the EM field produced by an MRI coil inside a numerical body model with 1 mm\u0000<sup>3</sup>\u0000 voxel resolution, could be performed in ~33 s in a GPU, after compressing the associated coupling matrix from ~80 TB to ~43 MB.","PeriodicalId":13102,"journal":{"name":"IEEE Transactions on Antennas and Propagation","volume":"70 1","pages":"459-471"},"PeriodicalIF":5.7,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8803273/pdf/nihms-1770887.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10459012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Millimeter-Wave Channel-Sounder Performance Verification Using Vector Network Analyzer in a Controlled RF Channel 用矢量网络分析仪在受控射频信道中验证毫米波信道测深仪的性能

IF 5.7 1区计算机科学

IEEE Transactions on Antennas and Propagation Pub Date : 2021-06-02 DOI: 10.1109/TAP.2021.3083737

Jeanne T. Quimby;Dylan F. Williams;Kate A. Remley;Diogo Ribeiro;Ruoyu Sun;Jelena Senic

引用次数: 3