Global Golub–Kahan bidiagonalization applied to large discrete ill-posed problems

Research paper by A.H. Bentbib, M. El Guide, K. Jbilou, L. Reichel

Indexed on: 17 Apr '17Published on: 27 Mar '17Published in: Journal of Computational and Applied Mathematics


We consider the solution of large linear systems of equations that arise from the discretization of ill-posed problems. The matrix has a Kronecker product structure and the right-hand side is contaminated by measurement error. Problems of this kind arise, for instance, from the discretization of Fredholm integral equations of the first kind in two space-dimensions with a separable kernel and in image restoration problems. Regularization methods, such as Tikhonov regularization, have to be employed to reduce the propagation of the error in the right-hand side into the computed solution. We investigate the use of the global Golub–Kahan bidiagonalization method to reduce the given large problem to a small one. The small problem is solved by employing Tikhonov regularization. A regularization parameter determines the amount of regularization. The connection between global Golub–Kahan bidiagonalization and Gauss-type quadrature rules is exploited to inexpensively compute bounds that are useful for determining the regularization parameter by the discrepancy principle.

Figure 10.1016/j.cam.2017.03.016.0.jpg
Figure 10.1016/j.cam.2017.03.016.1.jpg
Figure 10.1016/j.cam.2017.03.016.2.jpg