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
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);
Conference_Titel :
Antennas and Propagation (APCAP), 2014 3rd Asia-Pacific Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4799-4355-5
DOI :
10.1109/APCAP.2014.6992665
