On MLMDA/Butterfly Compressibility of Inverse Integral Operators

The multilevel matrix decomposition algorithm (MLMDA) is shown to permit effective compression of inverse integral operators pertinent to the analysis of scattering from electrically large structures. Observed compression ratios exceed those realized by low-rank (LR) compression methods, leading to...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:IEEE antennas and wireless propagation letters Ročník 12; s. 31 - 34
Hlavní autoři: Guo, Han, Hu, Jun, Michielssen, Eric
Médium: Journal Article
Jazyk:angličtina
Vydáno: IEEE 2013
Témata:
Approximation methods
Butterfly algorithms
direct solver
Educational institutions
Electromagnetic scattering
Integral equations
Matrix decomposition
Memory management
multilevel matrix decomposition
ISSN:1536-1225, 1548-5757
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:The multilevel matrix decomposition algorithm (MLMDA) is shown to permit effective compression of inverse integral operators pertinent to the analysis of scattering from electrically large structures. Observed compression ratios exceed those realized by low-rank (LR) compression methods, leading to substantial memory savings and a faster application of the inverse operator, and suggesting a new application for schemes traditionally used for compressing forward integral operators.
ISSN:1536-1225
1548-5757
DOI:10.1109/LAWP.2012.2234433