TY - JOUR
T1 - Inheritance of the discrete Picard condition in Krylov subspace methods
AU - Gazzola, Silvia
AU - Novati, Paolo
PY - 2016/9
Y1 - 2016/9
N2 - When projection methods are employed to regularize linear discrete ill-posed problems, one implicitly assumes that the discrete Picard condition (DPC) is somehow inherited by the projected problems. In this paper we show that, under some assumptions, the DPC holds for the projected uncorrupted systems computed by various Krylov subspace methods. By exploiting the inheritance of the DPC, some estimates on the behavior of the projected problems are also derived. Numerical examples are provided in order to illustrate the accuracy of the derived estimates.
AB - When projection methods are employed to regularize linear discrete ill-posed problems, one implicitly assumes that the discrete Picard condition (DPC) is somehow inherited by the projected problems. In this paper we show that, under some assumptions, the DPC holds for the projected uncorrupted systems computed by various Krylov subspace methods. By exploiting the inheritance of the DPC, some estimates on the behavior of the projected problems are also derived. Numerical examples are provided in order to illustrate the accuracy of the derived estimates.
KW - Arnoldi algorithm
KW - Discrete Picard condition
KW - GMRES residual
KW - Iterative regularization
KW - Lanczos bidiagonalization algorithm
UR - http://www.scopus.com/inward/record.url?scp=84938635325&partnerID=8YFLogxK
UR - http://dx.doi.org/10.1007/s10543-015-0578-5
U2 - 10.1007/s10543-015-0578-5
DO - 10.1007/s10543-015-0578-5
M3 - Article
AN - SCOPUS:84938635325
SN - 0006-3835
VL - 56
SP - 893
EP - 918
JO - BIT Numerical Mathematics
JF - BIT Numerical Mathematics
IS - 3
ER -