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Journal of Applied Mathematics and Computing

Erschienen in:

10.10.2021 | Original Research

Weak and strong convergence results for solving inclusion problems and its applications

verfasst von: Jun Yang, Huali Zhao, Min An

Erschienen in: Journal of Applied Mathematics and Computing | Ausgabe 4/2022

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Abstract

In this work, we study splitting methods for inclusion problems in real Hilbert space. The algorithms are inspired by forward-backward splitting method, projection and contraction method, inertial method and a self-adaptive step size. Under standard assumptions, such as Lipschitz continuity and monotonicity (also maximal monotonicity), we establish convergence results of the proposed algorithms. Finally, we present the application of the proposed algorithms for solving convex minimization problems and variational inequalities.

Vorheriger Artikel An adaptation of the modified decomposition method in solving nonlinear initial-boundary value problems for ODEs

Nächster Artikel Effective numerical technique for solving variable order integro-differential equations

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Titel: Weak and strong convergence results for solving inclusion problems and its applications
verfasst von: Jun Yang
Huali Zhao
Min An
Publikationsdatum: 10.10.2021
Verlag: Springer Berlin Heidelberg
Erschienen in: Journal of Applied Mathematics and Computing / Ausgabe 4/2022
Print ISSN: 1598-5865
Elektronische ISSN: 1865-2085
DOI: https://doi.org/10.1007/s12190-021-01644-4

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