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The L1 linear estimator which is used to solve the linear problem by minimizing the L1 norm in the data-fitting term does better than traditional least square (LS) methods in applications where the residual vector is super-Gaussian or contains outliers. We propose a fast L1 linear estimation algorithm by first translating the L1 norm data-fitting problem into a L1 norm regularized L2 norm data-fitting...
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