A NEW RELAXED CQ ALGORITHM FOR SOLVING SPLIT FEASIBILITY PROBLEMS IN HILBERT SPACES AND ITS APPLICATIONS

摘要

Inspired by the works of Lopez et al. [21] and the recent paper of Dang et al. [15], we devise a new inertial relaxation of the CQ algorithm for solving Split Feasibility Problems (SFP) in real Hilbert spaces. Under mild and standard conditions we establish weak convergence of the proposed algorithm . We also propose a Mann-type variant which converges strongly. The performances and comparisons with some existing methods are presented through numerical examples in Compressed Sensing and Sparse Binary Tomography by solving the LASSO problem.