An implicit wavelet sparse approximate inverse preconditioner

Stuart C. Hawkins*, K. Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
23 Downloads (Pure)


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
Issue number2
Publication statusPublished - 2005
Externally publishedYes

Bibliographical note

Copyright SIAM Publications. Article archived for private and non-commercial use with the permission of the author and according to publisher conditions. For further information see


  • Linear system
  • Preconditioning
  • Sparse approximate inverse
  • Wavelet


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