An iterative algorithm for solving equilibrium problems, variational inequalities and fixed point problems of multivalued quasi-nonexpansive mappings

<abstract>In this paper, we establish a modified proximal point algorithm for solving the common problem between convex constrained minimization and modified variational inclusion problems. The proposed algorithm base on the proximal point algorithm in [<xref ref-type="bibr" rid="b19">19</xref>] and the method of Khuangsatung and Kangtunyakarn in [<xref ref-type="bibr" rid="b21">21</xref>] by using suitable conditions in Hilbert spaces. The proposed algorithm is not only presented in this article; however has also been demonstrated to generate a robust convergence theorem. The proposed algorithm could be used to solve image restoration problems where the images have suffered a variety of blurring operations. Additionally, we contrast the signal-to-noise ratio (SNR) of the proposed algorithm against that of Khuangsatung and Kangtunyakarn's method in [<xref ref-type="bibr" rid="b21">21</xref>] in order to compare image quality.</abstract>

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An iterative algorithm for solving equilibrium problems, variational inequalities and fixed point problems of multivalued quasi-nonexpansive mappings

Cited by 2 publications

References 18 publications

A modified proximal point algorithm for solving variational inclusion problem in real Hilbert spaces

A modified proximal point algorithm for solving variational inclusion problem in real Hilbert spaces

Image restoration by using a modified proximal point algorithm

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