Convergence rates of the continuous regularized Gauss—Newton method
نویسندگان
چکیده
In this paper a convergence proof is given for the continuous analog of the Gauss—Newton method for nonlinear ill-posed operator equations and convergence rates are obtained. Convergence for exact data is proved for nonmonotone operators under weaker source conditions than before. Moreover, nonlinear ill-posed problems with noisy data are considered and a priori and a posteriori stopping rules are proposed. These rules yield convergence of the regularized approximations to the exact solution as the noise level tends to zero. The convergence rates are optimal rates under the source conditions considered.
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Continuous regularized Gauss-Newton-type algorithm for nonlinear ill-posed equations with simultaneous updates of inverse derivative
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