  Given an array with defective elements, failure correction (FC) aims at
finding a new set of weights for the working elements so that the properties of
the original pattern can be recovered. Unlike several FC techniques available
in the literature, which update all the working excitations, the
Minimum-Complexity Failure Correction (MCFC) problem is addressed in this
paper. By properly reformulating the FC problem, the minimum number of
corrections of the whole excitations of the array is determined by means of an
innovative Compressive Processing (CP) technique in order to afford a pattern
as close as possible to the original one (i.e., the array without failures).
Selected examples, from a wide set of numerical test cases, are discussed to
assess the effectiveness of the proposed approach as well as to compare its
performance with other competitive state-of-the-art techniques in terms of both
pattern features and number of corrections.
