Back to Search
Start Over
Inverse subspace problems with applications.
- Source :
-
Numerical Linear Algebra with Applications . Oct2014, Vol. 21 Issue 5, p589-603. 15p. - Publication Year :
- 2014
-
Abstract
- SUMMARY Given a square matrix A, the inverse subspace problem is concerned with determining a closest matrix to A with a prescribed invariant subspace. When A is Hermitian, the closest matrix may be required to be Hermitian. We measure distance in the Frobenius norm and discuss applications to Krylov subspace methods for the solution of large-scale linear systems of equations and eigenvalue problems as well as to the construction of blurring matrices. Extensions that allow the matrix A to be rectangular and applications to Lanczos bidiagonalization, as well as to the recently proposed subspace-restricted SVD method for the solution of linear discrete ill-posed problems, also are considered.Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10705325
- Volume :
- 21
- Issue :
- 5
- Database :
- Academic Search Index
- Journal :
- Numerical Linear Algebra with Applications
- Publication Type :
- Academic Journal
- Accession number :
- 98508739
- Full Text :
- https://doi.org/10.1002/nla.1914