Optimally Tuned Iterative Reconstruction Algorithms for Compressed Sensing

@article{Maleki2010OptimallyTI,
title={Optimally Tuned Iterative Reconstruction Algorithms for Compressed Sensing},
author={Arian Maleki and David L. Donoho},
journal={IEEE Journal of Selected Topics in Signal Processing},
year={2010},
volume={4},
pages={330-341}
}

We conducted an extensive computational experiment, lasting multiple CPU-years, to optimally select parameters for two important classes of algorithms for finding sparse solutions of underdetermined systems of linear equations. We make the optimally tuned implementations available at sparselab.stanford.edu; they run ¿out of the box¿ with no user tuning: it is not necessary to select thresholds or know the likely degree of sparsity. Our class of algorithms includes iterative hard and soft… CONTINUE READING