# On the choice of subspace for iterative methods for linear discrete ill-posed problems

Daniela Calvetti; Bryan Lewis; Lothar Reichel

International Journal of Applied Mathematics and Computer Science (2001)

- Volume: 11, Issue: 5, page 1069-1092
- ISSN: 1641-876X

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topCalvetti, Daniela, Lewis, Bryan, and Reichel, Lothar. "On the choice of subspace for iterative methods for linear discrete ill-posed problems." International Journal of Applied Mathematics and Computer Science 11.5 (2001): 1069-1092. <http://eudml.org/doc/207546>.

@article{Calvetti2001,

abstract = {Many iterative methods for the solution of linear discrete ill-posed problems with a large matrix require the computed approximate solutions to be orthogonal to the null space of the matrix. We show that when the desired solution is not smooth, it may be possible to determine meaningful approximate solutions with less computational work by not imposing this orthogonality condition.},

author = {Calvetti, Daniela, Lewis, Bryan, Reichel, Lothar},

journal = {International Journal of Applied Mathematics and Computer Science},

keywords = {conjugate gradient method; ill-posed problems; minimal residual method},

language = {eng},

number = {5},

pages = {1069-1092},

title = {On the choice of subspace for iterative methods for linear discrete ill-posed problems},

url = {http://eudml.org/doc/207546},

volume = {11},

year = {2001},

}

TY - JOUR

AU - Calvetti, Daniela

AU - Lewis, Bryan

AU - Reichel, Lothar

TI - On the choice of subspace for iterative methods for linear discrete ill-posed problems

JO - International Journal of Applied Mathematics and Computer Science

PY - 2001

VL - 11

IS - 5

SP - 1069

EP - 1092

AB - Many iterative methods for the solution of linear discrete ill-posed problems with a large matrix require the computed approximate solutions to be orthogonal to the null space of the matrix. We show that when the desired solution is not smooth, it may be possible to determine meaningful approximate solutions with less computational work by not imposing this orthogonality condition.

LA - eng

KW - conjugate gradient method; ill-posed problems; minimal residual method

UR - http://eudml.org/doc/207546

ER -

## References

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