TY - JOUR A1 - Pornsawad, Pornsarp A1 - Sungcharoen, Parada A1 - Böckmann, Christine T1 - Convergence rate of the modified Landweber method for solving inverse potential problems JF - Mathematics : open access journal N2 - In this paper, we present the convergence rate analysis of the modified Landweber method under logarithmic source condition for nonlinear ill-posed problems. The regularization parameter is chosen according to the discrepancy principle. The reconstructions of the shape of an unknown domain for an inverse potential problem by using the modified Landweber method are exhibited. KW - nonlinear operator KW - regularization KW - modified Landweber method KW - discrepancy principle KW - logarithmic source condition Y1 - 2020 U6 - https://doi.org/10.3390/math8040608 SN - 2227-7390 VL - 8 IS - 4 PB - MDPI CY - Basel ER - TY - JOUR A1 - Pornsawad, Pornsarp A1 - Sapsakul, Nantawan A1 - Böckmann, Christine T1 - A modified asymptotical regularization of nonlinear ill-posed problems JF - Mathematics N2 - In this paper, we investigate the continuous version of modified iterative Runge–Kutta-type methods for nonlinear inverse ill-posed problems proposed in a previous work. The convergence analysis is proved under the tangential cone condition, a modified discrepancy principle, i.e., the stopping time T is a solution of ∥𝐹(𝑥𝛿(𝑇))−𝑦𝛿∥=𝜏𝛿+ for some 𝛿+>𝛿, and an appropriate source condition. We yield the optimal rate of convergence. KW - nonlinear operator KW - regularization KW - discrepancy principle KW - asymptotic method KW - optimal rate Y1 - 2019 U6 - https://doi.org/10.3390/math7050419 SN - 2227-7390 VL - 7 PB - MDPI CY - Basel, Schweiz ET - 5 ER - TY - JOUR A1 - Blanchard, Gilles A1 - Hoffmann, Marc A1 - Reiss, Markus T1 - Optimal adaptation for early stopping in statistical inverse problems JF - SIAM/ASA Journal on Uncertainty Quantification N2 - For linear inverse problems Y = A mu + zeta, it is classical to recover the unknown signal mu by iterative regularization methods ((mu) over cap,(m) = 0,1, . . .) and halt at a data-dependent iteration tau using some stopping rule, typically based on a discrepancy principle, so that the weak (or prediction) squared-error parallel to A((mu) over cap (()(tau)) - mu)parallel to(2) is controlled. In the context of statistical estimation with stochastic noise zeta, we study oracle adaptation (that is, compared to the best possible stopping iteration) in strong squared- error E[parallel to((mu) over cap (()(tau)) - mu)parallel to(2)]. For a residual-based stopping rule oracle adaptation bounds are established for general spectral regularization methods. The proofs use bias and variance transfer techniques from weak prediction error to strong L-2-error, as well as convexity arguments and concentration bounds for the stochastic part. Adaptive early stopping for the Landweber method is studied in further detail and illustrated numerically. KW - linear inverse problems KW - early stopping KW - discrepancy principle KW - adaptive estimation KW - oracle inequality KW - Landweber iteration Y1 - 2018 U6 - https://doi.org/10.1137/17M1154096 SN - 2166-2525 VL - 6 IS - 3 SP - 1043 EP - 1075 PB - Society for Industrial and Applied Mathematics CY - Philadelphia ER - TY - JOUR A1 - Blanchard, Gilles A1 - Hoffmann, Marc A1 - Reiss, Markus T1 - Early stopping for statistical inverse problems via truncated SVD estimation JF - Electronic journal of statistics N2 - We consider truncated SVD (or spectral cut-off, projection) estimators for a prototypical statistical inverse problem in dimension D. Since calculating the singular value decomposition (SVD) only for the largest singular values is much less costly than the full SVD, our aim is to select a data-driven truncation level (m) over cap is an element of {1, . . . , D} only based on the knowledge of the first (m) over cap singular values and vectors. We analyse in detail whether sequential early stopping rules of this type can preserve statistical optimality. Information-constrained lower bounds and matching upper bounds for a residual based stopping rule are provided, which give a clear picture in which situation optimal sequential adaptation is feasible. Finally, a hybrid two-step approach is proposed which allows for classical oracle inequalities while considerably reducing numerical complexity. KW - Linear inverse problems KW - truncated SVD KW - spectral cut-off KW - early stopping KW - discrepancy principle KW - adaptive estimation KW - oracle inequalities Y1 - 2018 U6 - https://doi.org/10.1214/18-EJS1482 SN - 1935-7524 VL - 12 IS - 2 SP - 3204 EP - 3231 PB - Institute of Mathematical Statistics CY - Cleveland ER - TY - JOUR A1 - Böckmann, Christine A1 - Kammanee, Athassawat A1 - Braunss, Andreas T1 - Logarithmic convergence rate of Levenberg-Marquardt method with application to an inverse potential problem JF - Journal of inverse and ill-posed problems N2 - We prove logarithmic convergence rate of the Levenberg-Marquardt method in a Hilbert space if a logarithmic source condition is satisfied. This method is applied to an inverse potential problem. Numerical implementations demonstrate the convergence rate. KW - Levenberg-Marquardt method KW - inverse potential problems KW - logarithmic convergence rate KW - discrepancy principle KW - logarithmic source condition Y1 - 2011 U6 - https://doi.org/10.1515/JIIP.2011.034 SN - 0928-0219 VL - 19 IS - 3 SP - 345 EP - 367 PB - De Gruyter CY - Berlin ER -