TY - JOUR
T1 - Further Convergence Results on the General Iteratively Regularized Gauss-Newton Methods Under the Discrepancy Principle
AU - Jin, Qinian
PY - 2013
Y1 - 2013
N2 - We consider the general iteratively regularized Gauss-Newton methods for solving nonlinear inverse problems F(x) = y using the only available noise yδ satisfying||y δ -y|| ≤ δ with a given small noise level δ > 0. In order to produce reasonable approximation to the sought solution, we terminate the iteration by the discrepancy principle. Under much weaker conditions we derive some further convergence results which improve the existing ones and thus expand the applied range.
AB - We consider the general iteratively regularized Gauss-Newton methods for solving nonlinear inverse problems F(x) = y using the only available noise yδ satisfying||y δ -y|| ≤ δ with a given small noise level δ > 0. In order to produce reasonable approximation to the sought solution, we terminate the iteration by the discrepancy principle. Under much weaker conditions we derive some further convergence results which improve the existing ones and thus expand the applied range.
KW - Convergence
KW - Nonlinear inverse problems
KW - Order optimality.
KW - The discrepancy principle
KW - The general iteratively regularized Gauss-Newton methods
UR - http://www.scopus.com/inward/record.url?scp=84878317202&partnerID=8YFLogxK
U2 - 10.1090/S0025-5718-2012-02665-2
DO - 10.1090/S0025-5718-2012-02665-2
M3 - Article
SN - 0025-5718
VL - 82
SP - 1647
EP - 1665
JO - Mathematics of Computation
JF - Mathematics of Computation
IS - 283
ER -