Solution of ill-posed problems by means of Truncated SVD (Singular Value Decomposition)
Technical Report
·
OSTI ID:6987431
We investigate /ital Truncated Singular Value Decomposition/ (TSVD) solutions to ill-posed least squares problems involving matrices with ill-determined as well as well-determined numerical rank. If a /ital discrete Picard condition/ is satisfied, then in /ital both cases/ the truncation parameter can be chosen such that the TSVD solution is satisfactory. The appropriate truncation parameter, giving the optimal signal-to-noise ratio in the solution, is the minimizer of the generalized cross-validation. 26 refs.
- Research Organization:
- USDOE, Washington, DC; Oak Ridge National Lab., TN (USA)
- DOE Contract Number:
- AC05-84OR21400
- OSTI ID:
- 6987431
- Report Number(s):
- ORNL/TM-10772; ON: DE88013510
- Country of Publication:
- United States
- Language:
- English
Similar Records
Iterative SVD-based methods for ill-posed problems. [Singular value decomposition]
Regularization, GSVD and Truncated GSVD (generalized singular value decomposition)
A multiprocessor scheme for the singular value decomposition
Journal Article
·
Sun May 01 00:00:00 EDT 1994
· SIAM Journal on Scientific and Statistical Computing (Society for Industrial and Applied Mathematics); (United States)
·
OSTI ID:7112108
Regularization, GSVD and Truncated GSVD (generalized singular value decomposition)
Technical Report
·
Thu Sep 01 00:00:00 EDT 1988
·
OSTI ID:6788384
A multiprocessor scheme for the singular value decomposition
Conference
·
Sat Aug 01 00:00:00 EDT 1987
·
OSTI ID:5576354