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This paper describes a new MATLAB software package of iterativeregularization methods and test problems for large-scale linear inverseproblems. The software package, called IR Tools, serves two related purposes:we provide implementations of a range of iterative solvers, including severalrecently proposed methods that are not available elsewhere, and we provide aset of large-scale test problems in the form of discretizations of 2D linearinverse problems. The solvers include iterative regularization methods wherethe regularization is due to the semi-convergence of the iterations,Tikhonov-type formulations where the regularization is explicitly formulated inthe form of a regularization term, and methods that can impose boundconstraints on the computed solutions. All the iterative methods areimplemented in a very flexible fashion that allows the problem's coefficientmatrix to be available as a (sparse) matrix, a function handle, or an object.The most basic call to all of the various iterative methods requires only thismatrix and the right hand side vector; if the method uses any special stoppingcriteria, regularization parameters, etc., then default values are setautomatically by the code. Moreover, through the use of an optional inputstructure, the user can also have full control of any of the algorithmparameters. The test problems represent realistic large-scale problems found inimage reconstruction and several other applications. Numerical examplesillustrate the various algorithms and test problems available in this package.

IR Tools: A MATLAB Package of Iterative Regularization Methods and Large-Scale Test Problems