Compressed representation of matrix decomposition algorithm-singular value decomposition for full-wave analysis microstrip problems

	Compressed representation of matrix decomposition algorithm-singular value decomposition for full-wave analysis microstrip problems
	Xiaoqing Hu; Rushan Chen; Xiao Chen; Xin Liu; Hairong Zheng; Ye Li
刊名	Journal of Electromagnetic Waves and Applications
	2015
英文摘要	In order to efficiently solve large dense complex linear systems arising from electric field integral equations (EFIE) of electromagnetic problems, matrix decomposition algorithm-singular value decomposition (MDA-SVD) is used to accelerate the matrix-vector product (MVP) operations and decrease memory usage. Based on the symmetry of the impedance matrix resulting from the discretization of the EFIE, we introduce a compressed representation of MDA-SVD in this paper. We obtain a sparse representation of the far-field interaction parts of impedance matrix and perform a fast MVP operation. Numerical experiments demonstrate that the compressed representation of MDA-SVD can reduce both the MVP time and memory usage by around 50% with similar accuracy.
收录类别	SCI
原文出处	http://dx.doi.org/10.1080/09205071.2015.1017013
语种	英语
内容类型	期刊论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/7129]
专题	深圳先进技术研究院_医工所
作者单位	Journal of Electromagnetic Waves and Applications
推荐引用方式 GB/T 7714	Xiaoqing Hu,Rushan Chen,Xiao Chen,et al. Compressed representation of matrix decomposition algorithm-singular value decomposition for full-wave analysis microstrip problems[J]. Journal of Electromagnetic Waves and Applications,2015.
APA	Xiaoqing Hu,Rushan Chen,Xiao Chen,Xin Liu,Hairong Zheng,&Ye Li.(2015).Compressed representation of matrix decomposition algorithm-singular value decomposition for full-wave analysis microstrip problems.Journal of Electromagnetic Waves and Applications.
MLA	Xiaoqing Hu,et al."Compressed representation of matrix decomposition algorithm-singular value decomposition for full-wave analysis microstrip problems".Journal of Electromagnetic Waves and Applications (2015).