Abstract
In this paper, we propose double inertial forward-backward algorithms for solving unconstrained minimization problems and projected double inertial forward-backward algorithms for solving constrained minimization problems. We then prove convergence theorems under mild conditions. Finally, we provide numerical experiments on image restoration problem and image inpainting problem. The numerical results show that the proposed algorithms have more efficient than known algorithms introduced in the literature.
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This work was supported by National Research Council of Thailand (NRCT) under grant no. N41A640094 and the Thailand Science Research and Innovation Fund and the University of Phayao under the pro ject FF66-UoE.
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Kankam, K., Cholamjiak, P. Double Inertial Proximal Gradient Algorithms for Convex Optimization Problems and Applications. Acta Math Sci 43, 1462–1476 (2023). https://doi.org/10.1007/s10473-023-0326-x
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DOI: https://doi.org/10.1007/s10473-023-0326-x