Two self-adaptive inertial projection algorithms for solving split variational inclusion problems
Keyword(s):
<abstract><p>This paper is to analyze the approximation solution of a split variational inclusion problem in the framework of Hilbert spaces. For this purpose, inertial hybrid and shrinking projection algorithms are proposed under the effect of a self-adaptive stepsize which does not require information of the norms of the given operators. The strong convergence properties of the proposed algorithms are obtained under mild constraints. Finally, a numerical experiment is given to illustrate the performance of proposed methods and to compare our algorithms with an existing algorithm.</p></abstract>
A modified proximal point algorithm for solving variational inclusion problem in real Hilbert spaces
2020 ◽
Vol 2020
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pp. 28-39
2017 ◽
Vol 38
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pp. 306-326
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2013 ◽
Vol 2013
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