A NEW SUFFICIENT CONDITION FOR SPARSE RECOVERY WITH MULTIPLE ORTHOGONAL LEAST SQUARES

A greedy algorithm used for the recovery of sparse signals, multiple orthogonal least squares (MOLS) have recently attracted quite a big of attention. In this paper, we consider the number of iterations required for the MOLS algorithm for recovery of a K-sparse signal x is an element of R-n. We show that MOLS provides stable reconstruction of all K-sparse signals x from y = Ax + w in inverted right perpendicular6K/Minverted left perpendicular iterations when the matrix A satisfies the restricted isometry property (RIP) with isometry constant delta(7K) <= 0.094. Compared with the existing results, our sufficient condition is not related to the sparsity level K.