TY - JOUR
T1 - Iterative regularization methods with new stepsize rules for solving variational inclusions
AU - Van Hieu, Dang
AU - Anh, Pham Ky
AU - Muu, Le Dung
AU - Strodiot, Jean Jacques
N1 - Funding Information:
The authors sincerely thank the Editor and anonymous reviewers for their constructive comments which helped to improve the quality and presentation of this paper. The research of first and third authors is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under Grant Number 101.01-2020.06. The research of last author is supported by the Namur Institute for Complex Systems, naXys, University of Namur, Belgium.
Publisher Copyright:
© 2021, Korean Society for Informatics and Computational Applied Mathematics.
PY - 2022/2
Y1 - 2022/2
N2 - The paper concerns with three iterative regularization methods for solving a variational inclusion problem of the sum of two operators, the one is maximally monotone and the another is monotone and Lipschitz continuous, in a Hilbert space. We first describe how to incorporate regularization terms in the methods of forward-backward types, and then establish the strong convergence of the resulting methods. With several new stepsize rules considered, the methods can work with or without knowing previously the Lipschitz constant of cost operator. Unlike known hybrid methods, the strong convergence of the proposed methods comes from the regularization technique. Several applications to signal recovery problems and optimal control problems together with numerical experiments are also presented in this paper. Our numerical results have illustrated the fast convergence and computational effectiveness of the new methods over known hybrid methods.
AB - The paper concerns with three iterative regularization methods for solving a variational inclusion problem of the sum of two operators, the one is maximally monotone and the another is monotone and Lipschitz continuous, in a Hilbert space. We first describe how to incorporate regularization terms in the methods of forward-backward types, and then establish the strong convergence of the resulting methods. With several new stepsize rules considered, the methods can work with or without knowing previously the Lipschitz constant of cost operator. Unlike known hybrid methods, the strong convergence of the proposed methods comes from the regularization technique. Several applications to signal recovery problems and optimal control problems together with numerical experiments are also presented in this paper. Our numerical results have illustrated the fast convergence and computational effectiveness of the new methods over known hybrid methods.
KW - Forward-backward-forward method
KW - Lipschitz continuity
KW - Monotonicity
KW - Regularization method
KW - Variational inclusion
UR - http://www.scopus.com/inward/record.url?scp=85103560996&partnerID=8YFLogxK
U2 - 10.1007/s12190-021-01534-9
DO - 10.1007/s12190-021-01534-9
M3 - Article
AN - SCOPUS:85103560996
SN - 1598-5865
VL - 68
SP - 571
EP - 599
JO - Journal of Applied Mathematics and Computing
JF - Journal of Applied Mathematics and Computing
IS - 1
ER -