For linear least squares problems min x Ax -b 2 , where A is sparse except for a few dense rows, a straightforward application of Cholesky or QR factorization will lead to catastrophic fill in the factor R. We consider handling such problems by a matrix stretching technique, where the dense rows ar
β¦ LIBER β¦
Square and stretch multigrid for stochastic matrix eigenproblems
β Scribed by Eran Treister; Irad Yavneh
- Publisher
- John Wiley and Sons
- Year
- 2010
- Tongue
- English
- Weight
- 443 KB
- Volume
- 17
- Category
- Article
- ISSN
- 1070-5325
- DOI
- 10.1002/nla.708
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
Matrix stretching for sparse least squar
β
Mikael Adlers; Γ
ke BjΓΆrck
π
Article
π
2000
π
John Wiley and Sons
π
English
β 91 KB
Algebraic multigrid for stationary and t
β
E. Rosseel; T. Boonen; S. Vandewalle
π
Article
π
2008
π
John Wiley and Sons
π
English
β 373 KB
First and second derivative matrix eleme
β
Kenneth J. Miller; Robert J. Hinde; Janet Anderson
π
Article
π
1989
π
John Wiley and Sons
π
English
β 957 KB
Matrix elements for the first and second derivatives of the internal coordinates with respect to Cartesian coordinates are reported for stretching, linear, nonlinear, and out-of-plane bending and torsional motion. Derivatives of the energy with respect to the Cartesian coordinates are calculated wit
βStretchβ vs βsliceβ methods for represe
β
Richard A. Harshman; Sungjin Hong
π
Article
π
2002
π
John Wiley and Sons
π
English
β 147 KB
Nonlinear multigrid for the solution of
β
L. Grasedyck
π
Article
π
2008
π
John Wiley and Sons
π
English
β 284 KB
Least-square method for 2D FIR digital f
β
Masahiro Okuda; Masaaki Ikehara; Shin-ichi Takahashi
π
Article
π
1998
π
John Wiley and Sons
π
English
β 919 KB