On the relaxed projection method for the SFPMOS

IF 1.1 Q1 MATHEMATICS Journal of Nonlinear Functional Analysis Pub Date : 2023-01-01 DOI:10.23952/jnfa.2023.26
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Abstract

. This paper presents our investigation into the split feasibility problem with multiple output sets (SF-PMOS), under the assumption that the corresponding convex subsets are level subsets of convex functionals. To approximate the solutions of this problem, we propose a method that combines relaxed projection with a recently proposed technique. Our approach involves establishing a weak convergence theorem for the fixed stepsize, followed by constructing a variable stepsize that is independent of the norm of the linear operator involved. We also modify these methods to ensure strong convergence. As an application, we develop a new relaxed projection algorithm for solving the split feasibility problem.
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SFPMOS的松弛投影法
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2.40
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期刊介绍: Journal of Nonlinear Functional Analysis focuses on important developments in nonlinear functional analysis and its applications with a particular emphasis on topics include, but are not limited to: Approximation theory; Asymptotic behavior; Banach space geometric constant and its applications; Complementarity problems; Control theory; Dynamic systems; Fixed point theory and methods of computing fixed points; Fluid dynamics; Functional differential equations; Iteration theory, iterative and composite equations; Mathematical biology and ecology; Miscellaneous applications of nonlinear analysis; Multilinear algebra and tensor computation; Nonlinear eigenvalue problems and nonlinear spectral theory; Nonsmooth analysis, variational analysis, convex analysis and their applications; Numerical analysis; Optimal control; Optimization theory; Ordinary differential equations; Partial differential equations; Positive operator inequality and its applications in operator equation spectrum theory and so forth; Semidefinite programming polynomial optimization; Variational and other types of inequalities involving nonlinear mappings; Variational inequalities.
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