An implicit wavelet sparse approximate inverse preconditioner

Stuart C. Hawkins*, Ke Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)667-686
Number of pages20
JournalSIAM Journal on Scientific Computing
Volume27
Issue number2
DOIs
Publication statusPublished - 1 Jan 2005

Keywords

  • linear system
  • preconditioning
  • sparse approximate inverse
  • wavelet

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