上海大学学报（英文版）
上海大學學報（英文版）
상해대학학보（영문판）
JOURNAL OF SHANGHAI UNIVERSITY (ENGLISH EDITION)
2007年
5期
457-463
,共7页
nonlinear ill-posed problems%A-smooth regularization%a posteriori stopping rule%convergence and convergence rates.
In this paper we present a regularized Newton-type method for ill-posed problems, by using the A-smooth regularization to solve the linearized ill-posed equations. For noisy data a proper a posteriori stopping rule is used that yields convergence of the Newton iteration to a solution, as the noise level goes to zero, under certain smoothness conditions on the nonlinear operator. Some appropriate assumptions on the closedness and smoothness of the starting value and the solution are shown to lead to optimal convergence rates.
