Recovering Sparse Signals With a Certain Family of Nonconvex Penalties and DC Programming

This paper considers the problem of recovering a sparse signal representation according to a signal dictionary. This problem could be formalized as a penalized least-squares problem in which sparsity is usually induced by a lscr1-norm penalty on the coefficients. Such an approach known as the Lasso ... View More