Polyak’s gradient method for solving the split convex feasibility problem and its applications

Abstract

In this paper, we are concerned with the problem of finding minimum-norm solutions of a split convex feasibility problem in real Hilbert spaces. We study and analyze the convergence of a new self-adaptive CQ algorithm. The main advantage of the algorithm is that there is no need to calculate the norm of the involved operator.