Perturbation resilience and superiorization methodology of averaged mappings. (1st March 2017) - He, Hongjin; Xu, Hong-Kun
Abstract: We first prove the bounded perturbation resilience for the successive fixed point algorithm of averaged mappings, which extends the string-averaging projection and block-iterative projection methods. We then apply the superiorization methodology to a constrained convex minimization problem where the constraint set is the intersection of fixed point sets of a finite family of averaged mappings.