DocumentCode
1775803
Title
Sparsified multilevel adaptive cross approximation
Author
Xinlei Chen ; Changqing Gu ; Zhuo Li ; Zhenyi Niu
Author_Institution
Key Lab. of Radar Imaging & Microwave Photonics, Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
fYear
2014
fDate
26-29 July 2014
Firstpage
971
Lastpage
973
Abstract
In this paper, a sparsified multilevel adaptive cross approximation (SMLACA) is proposed to improve the sparsified adaptive cross approximation (SPACA). Compared with the SPACA, the SMLACA can save the CPU time and memory requirement for large targets. Numerical results are presented to validate the SMLACA and demonstrate its merits.
Keywords
integrated memory circuits; method of moments; microprocessor chips; CPU; SMLACA; SPACA; memory; sparsified adaptive cross approximation; sparsified multilevel adaptive cross approximation; Antennas; Approximation algorithms; Approximation methods; Educational institutions; Laboratories; Method of moments; Sparse matrices; method of moments (MoM); sparsified multilevel adaptive cross approximation (SMLACA);
fLanguage
English
Publisher
ieee
Conference_Titel
Antennas and Propagation (APCAP), 2014 3rd Asia-Pacific Conference on
Conference_Location
Harbin
Print_ISBN
978-1-4799-4355-5
Type
conf
DOI
10.1109/APCAP.2014.6992665
Filename
6992665
Link To Document