Minimum variance regularization in linear inverse problems
β Scribed by C. Takiya; O. Helene; E. do Nascimento; V.R. Vanin
- Publisher
- Elsevier Science
- Year
- 2004
- Tongue
- English
- Weight
- 300 KB
- Volume
- 523
- Category
- Article
- ISSN
- 0168-9002
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
A new numerical procedure is proposed for the reconstruction of the shape and volume of unknown objects from measurements of their radiation in the far field. This procedure is a variant and the linear sampling method has a very acceptable computational load and is fully automated. It is based on ex
## Abstract For the approximate solution of illβposed inverse problems, the formulation of a regularization functional involves two separate decisions: the choice of the residual minimizer and the choice of the regularizor. In this paper, the KullbackβLeibler functional is used for both. The result
Optimal state estimation from given observations of a dynamical system by data assimilation is generally an ill-posed inverse problem. In order to solve the problem, a standard Tikhonov, or L 2 , regularization is used, based on certain statistical assumptions on the errors in the data. The regulari