Signal recovery by best feasible approximation

The objective of set theoretic signal recovery is to find a feasible signal in the form of a point in the intersection S of sets modeling the information available about the problem. For problems in which the true signal is known to lie near a reference signal r, the solution should not be any feasible point but one which best approximates r, i.e., a projection of r onto S. Such a solution cannot be obtained by the feasibility algorithms currently in use, e.g., the method of projections onto convex sets (POCS) and its offsprings. In this work, methods to project a point onto the intersection of closed and convex sets in a Hilbert space are introduced and applied to signal recovery by best feasible approximation of a reference signal. These recent algorithms are closely related to the above projection methods, to which they add little computational complexity.