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Title: Convergence rate of the relaxed CQ algorithm under Hölderian type error bound property
Authors: Zhang, L
Wang, J
Li, C
Yang, X 
Issue Date: 2024
Source: Optimization, 2024, v. 73, no. 4, p. 1285-1301
Abstract: The relaxed CQ algorithm is one of the most important algorithms for solving the split feasibility problem. We study the issue of strong convergence of the relaxed CQ algorithm in Hilbert spaces together with estimates on the convergence rate. Under a kind of Hölderian type bounded error bound property, strong convergence of the relaxed CQ algorithm is established. Furthermore, qualitative estimates on the convergence rate is presented. In particular, for the case when the involved exponent is equal to 1, the linear convergence of the relaxed CQ algorithm is established. Finally, numerical experiments are performed to show the convergence property of the relaxed CQ algorithm for the compressed sensing problem.
Keywords: Convergence rete analysis
Hölderian type error bound
Relaxed CQ algorithm
Split feasibility problem
Publisher: Taylor & Francis
Journal: Optimization 
ISSN: 0233-1934
EISSN: 1029-4945
DOI: 10.1080/02331934.2022.2154606
Rights: © 2022 Informa UK Limited, trading as Taylor & Francis Group
This is an Accepted Manuscript of an article published by Taylor & Francis in Optimization on 12 Dec 2022 (Published online), available online: http://www.tandfonline.com/10.1080/02331934.2022.2154606.
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