Implicit iteration methods in Hilbert scales under general smoothness conditions
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For solving linear ill-posed problems, regularization methods are required when the right-hand side is with some noise. In this paper regularized solutions are obtained by implicit iteration methods in Hilbert scales. By exploiting operator monotonicity of certain functions and interpolation techniques in variable Hilbert scales, we study these methods under general smoothness conditions. Order optimal error bounds are given in case the regularization parameter is chosen either a priori or a posteriori by the discrepancy principle. For realizing the discrepancy principle, some fast algorithm is proposed which is based on Newton's method applied to some properly transformed equations.
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Inverse Problems