FURTHER CONVERGENCE RESULTS ON THE GENERAL ITERATIVELY REGULARIZED GAUSS-NEWTON METHODS UNDER THE DISCREPANCY PRINCIPLE

被引:0
作者
Jin, Qinian [1 ]
机构
[1] Virginia Tech, Dept Math, Blacksburg, VA 24061 USA
关键词
Nonlinear inverse problems; the general iteratively regularized Gauss-Newton methods; the discrepancy principle; convergence; order optimality; ILL-POSED PROBLEMS;
D O I
暂无
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
We consider the general iteratively regularized Gauss-Newton methods x(k+1)(delta)=x0-g(alpha k)(F'(x(k)(delta))*F'(x(k)(delta)))F'(x(k)(delta))*(F(x(k)(delta))-y(delta)-F'(x(k)(delta))(-x(0))) for solving nonlinear inverse problems F(x) = y using the only available noise y(delta) of y satisfying ||y(delta)-y|| <= delta with a given small noise level delta > 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.
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页码:1647 / 1665
页数:19
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