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3-D Projected L1 inversion of gravity data using truncated unbiased predictive risk estimator for regularization parameter estimation
Sparse inversion of gravity data based on $L_1$-norm regularization is discussed. An iteratively reweighted least squares algorithm is used to solve the problem. At each iteration the solution of a linear system of equations and the determination of a suitable regularization parameter are considered. The LSQR iteration is used to …