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An implicit wavelet sparse approximate inverse preconditioner

delete2005-01-01
delete6
PRE
AI
S
Stuart C. Hawkins
陈珂 (Ke Chen)
DOI:10.1137/S1064827503423500delete
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Abstract

Abstract

En 中文
Wavelet-based sparse approximate inverse preconditioners are considered for the linear system Ax = b. The preconditioners are good sparse approximations to the inverse of A computed by taking advantage of the compression obtained by working in a wavelet basis. When the representation of A in a single scale basis ( for example, a finite element basis) is available, the formulation presented obviates computation of the representation of A in the wavelet basis and removes the associated costs. Efficient application for both sparse and dense A is considered.
Keywords:
linear system
preconditioning
sparse approximate inverse
wavelet

Journal

SIAM Journal on Scientific Computing cover
SIAM Journal on Scientific Computing
IF:
2.6
Papers:
5.1K
Citations:
1.8W

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