Abstract
The purpose of this contribution is to generalize some recent results on sparse representations of signals in redundant bases. The question that is considered is thc following : let A be a known (n, m) matrix with m > n. one observes b = AX where X is known to have p < n nonzero components. under which couditions on A and p is it possible to recover X by solving a convex optimization problem such as a linear or quadratic program? The solution is known when A is the concatination of two unitary matrices. we extend it to arbitrary matrices.
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