A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is
The Feasibility Pump is an effective heuristic method for solving mixed integer optimization programs. In this paper the algorithm is adapted for finding the sparse representation of signals affected by Laplacian noise. Two adaptations of the algorithm, regularized and nonregularized, are proposed, tested, and compared against the regularized least absolute deviation (RLAD) model. The obtained results show that the addition of the regularization factor always improves the algorithm. Thedoi:10.1155/2019/5615243 fatcat:vhabkrq5afcnxj5basyj3o3h4m