The Regularizing Efect of the Golub-Kahan Iterative Bidiagonalization and Revealing the Noise in the Data
Abstract
Regularization techniques based on the Golub-Kahan iterative bidiagonalization belong among popular approaches for solving large ill-posed problems. In this paper we consider an ill-posed problem with a noisy right-hand side, where the noise level is unknown.
We show how the information from the Golub-Kahan iterative bidiagonalization can be used for estimating the noise level.