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Regularization methods aimed at finding stable approximate solutions are a necessary tool to tackle inverse and ill-posed problems. Inverse problems arise in a
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This specialized and authoritative book contains an overview of modern approaches to constructing approximations to solutions of ill-posed operator equations, b
Regularization in Banach Spaces - Convergence Rates Theory
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Motivated by their successful application in image restoring and sparsity reconstruction this manuscript deals with regularization theory of linear and nonlinea
New Trends in Parameter Identification for Mathematical Models
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Iterative Regularization Methods for Nonlinear Ill-Posed Problems
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Nonlinear inverse problems appear in many applications, and typically they lead to mathematical models that are ill-posed, i.e., they are unstable under data pe