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 language | English |
|---|---|
| Pages (from-to) | 667-686 |
| Number of pages | 20 |
| Journal | SIAM Journal on Scientific Computing |
| Volume | 27 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 1 Jan 2005 |
Keywords
- linear system
- preconditioning
- sparse approximate inverse
- wavelet
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