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Two relaxed inertial forward-backward-forward algorithms for solving monotone inclusions and an application to compressed sensing
Published online by Cambridge University Press: 13 January 2025
Abstract
Two novel algorithms, which incorporate inertial terms and relaxation effects, are introduced to tackle a monotone inclusion problem. The weak and strong convergence of the algorithms are obtained under certain conditions, and the R-linear convergence for the first algorithm is demonstrated if the set-valued operator involved is strongly monotone in real Hilbert spaces. The proposed algorithms are applied to signal recovery problems and demonstrate improved performance compared to existing algorithms in the literature.
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- © The Author(s), 2025. Published by Cambridge University Press on behalf of Canadian Mathematical Society
Footnotes
B. Tan thanks the support of the Natural Science Foundation of Chongqing (No. CSTB2024NSCQ-MSX0354), the National Natural Science Foundation of China (No. 12471473), and the Fundamental Research Funds for the Central Universities (No. SWU-KQ24052).