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Volume 1, Issue 2, 31 August 2019, Pages 145-156
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.
How to Cite this Article:
Aviv Gibali, Nguyen H. Ha, Ngo T. Thuong, Trinh H. Trang, Nguyen T. Vinh, Polyak’s gradient method for solving the split convex feasibility problem and its applications, J. Appl. Numer. Optim. 1 (2019), 145-156.