We propose a hybrid inertial self-adaptive algorithm for solving the split feasibility problem and fixed point problem in the class of demicontractive mappings. Our results are very general and extend several related ...
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We propose a hybrid inertial self-adaptive algorithm for solving the split feasibility problem and fixed point problem in the class of demicontractive mappings. Our results are very general and extend several related results existing in the literature from the class of nonexpansive or quasi-nonexpansive mappings to the larger class of demicontractive mappings. Examples to illustrate numerically the effectiveness of the new analytical results are presented.
In this work, we study the split common fixed point problem with multiple output sets for two finite families of generalized demimetric mappings in Hilbert space. In order to solve this problem, we suggest a new inert...
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In this work, we study the split common fixed point problem with multiple output sets for two finite families of generalized demimetric mappings in Hilbert space. In order to solve this problem, we suggest a new inertial self-adaptive algorithm and establish a strong convergence theorem for it under relevant conditions. We also provide a numerical example to support our main result.
In the field of convex optimization, numerous problems can be modeled as the split variational inclusion problem. In this paper, we want to give self-adaptivealgorithms and inertial self-adaptive algorithms to study ...
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In the field of convex optimization, numerous problems can be modeled as the split variational inclusion problem. In this paper, we want to give self-adaptivealgorithms and inertial self-adaptive algorithms to study the split variational inclusion problems. Next, we propose related convergence theorems under suitable conditions.
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