Abstract
The feasible solution to the signal restoration problem is defined as the one which satisfies all constraints which can be imposed on the true solution. A very important set of constraints can be obtained by examining the statistics of the noise. These and other constraints can be described as closed convex sets. Thus, projection onto closed convex sets is the numerical method used to obtain a feasible solution. Examples of this method demonstrate its usefulness in one-and two-dimensional signal restoration. The limitations of the method are discussed.
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