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...

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Bibliographic Details
Published in:IEEE antennas and wireless propagation letters Vol. 12; pp. 31 - 34
Main Authors: Guo, Han, Hu, Jun, Michielssen, Eric
Format: Journal Article
Language:English
Published: IEEE 2013
Subjects:
Approximation methods
Butterfly algorithms
direct solver
Educational institutions
Electromagnetic scattering
Integral equations
Matrix decomposition
Memory management
multilevel matrix decomposition
ISSN:1536-1225, 1548-5757
Online Access:Get full text
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Summary: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