1,788 research outputs found
Local Analysis of Inverse Problems: H\"{o}lder Stability and Iterative Reconstruction
We consider a class of inverse problems defined by a nonlinear map from
parameter or model functions to the data. We assume that solutions exist. The
space of model functions is a Banach space which is smooth and uniformly
convex; however, the data space can be an arbitrary Banach space. We study
sequences of parameter functions generated by a nonlinear Landweber iteration
and conditions under which these strongly converge, locally, to the solutions
within an appropriate distance. We express the conditions for convergence in
terms of H\"{o}lder stability of the inverse maps, which ties naturally to the
analysis of inverse problems
Convergence analysis of a proximal Gauss-Newton method
An extension of the Gauss-Newton algorithm is proposed to find local
minimizers of penalized nonlinear least squares problems, under generalized
Lipschitz assumptions. Convergence results of local type are obtained, as well
as an estimate of the radius of the convergence ball. Some applications for
solving constrained nonlinear equations are discussed and the numerical
performance of the method is assessed on some significant test problems
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