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An improved multilevel simple sparse method with adaptive cross approximation for scattering from target above lossy half space
Author(s) -
Hu Xiaoqing,
Zhang Chi,
Xu Yuan,
Ding Dazhi,
Chen Rushan
Publication year - 2012
Publication title -
microwave and optical technology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.304
H-Index - 76
eISSN - 1098-2760
pISSN - 0895-2477
DOI - 10.1002/mop.26606
Subject(s) - sparse approximation , matrix (chemical analysis) , simple (philosophy) , impedance parameters , sparse matrix , representation (politics) , lossy compression , computer science , algorithm , multiplication (music) , field (mathematics) , matrix multiplication , mathematics , electrical impedance , artificial intelligence , engineering , physics , electrical engineering , materials science , law , composite material , quantum , epistemology , quantum mechanics , political science , gaussian , politics , pure mathematics , philosophy , combinatorics
The adaptive cross approximation (ACA) algorithm has been used to reduce memory requirements and matrix‐vector product (MVP) time since it was proposed to solve electric field integral equation of electromagnetic problems. In this letter, we firstly introduce an improved multilevel simple sparse method (MLSSM). Based on the improved MLSSM, the impedance matrix resulting from ACA algorithm can be represented very sparsely. In the sparse representation, the far‐field interaction parts of impedance matrix can be represented by multiplication of three sparse matrices in recursive manner. Moreover, an efficient MVP operation is implemented by using the sparse representation. Numerical experiments demonstrate that our improved MLSSM with ACA algorithm outperforms original ACA algorithm in terms of memory requirement of far‐field interactions and the time per MVP operation. © 2012 Wiley Periodicals, Inc. Microwave Opt Technol Lett 54:573–577, 2012; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26606