A truncated approximate difference algorithm for sparse signal recovery

In this paper, we study the regularization lp-norm minimization problem to recover the sparse signals. We first prove that every global optimal solution to the regularization lp-norm minimization problem also solves the l0-norm minimization problem if the certain conditions are satisfied, and then generate a truncated approximated difference algorithm to recover the sparse signals. At last, we provide some numerical simulations to test the performance of the truncated approximated difference algorithm, and the numerical results show that the proposed algorithm performs effectively in recovering the sparse signals compared with some state-of-art methods.