[PDF] Top 20 The constrained multiple sets split feasibility problem and its projection algorithms
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The constrained multiple sets split feasibility problem and its projection algorithms
... The split feasibility problem in finite-dimensional Hilbert spaces was first introduced by Censor and Elfving [] for modeling inverse problems which arise from phase retrievals and in medical image ... See full document
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Iterative methods for solving the multiple-sets split feasibility problem with splitting self-adaptive step size
... the multiple-sets split feasibility problem, which was motivated by the in- verse problem of intensity modulated radiation therapy ...The multiple-sets split ... See full document
15
Solutions for a variational inclusion problem with applications to multiple sets split feasibility problems
... problems: multiple sets split feasibility problems, system of convex constrained linear inverse problems, convex constrained linear inverse problems, split ... See full document
21
Gradient projection method with a new step size for the split feasibility problem
... In all these CQ-like algorithms for the SFP (1.1), in order to get the step size, one has to compute the largest eigenvalue of the related matrix or use some line search scheme which usually requires many inner ... See full document
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Alternating proximal penalization algorithm for the modified multiple sets split feasibility problems
... the projection method more efficient when the projection is difficult to compute, Yang [25] established a relaxed CQ algorithm by modifying the projection ...the split feasibility ... See full document
8
Some Krasnonsel'skiĭ-Mann Algorithms and the Multiple-Set Split Feasibility Problem
... new projection algorithms which solve the MSSFP ...of algorithms 1.13, 1.14, and 1.15 for solving the MSSFP. These projection algorithms can also reduce to the algorithm ... See full document
12
Split equality problem and multiple sets split equality problem for quasi nonexpansive multi valued mappings
... the split equality problem ...well-known multiple-sets split feasibility problem (MSSFP) and split feasibility problem (SFP), ...many ... See full document
8
Strong convergence of an extragradient type algorithm for the multiple sets split equality problem
... various algorithms proposed to solve the SFP, see [–] and the references ...convex sets instead of the convex set C, which is the original of the multiple-sets split ... See full document
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Hybrid CQ projection algorithm with line search process for the split feasibility problem
... CQ projection algorithm with two projection steps and one Armijo-type line-search step for the split feasibility ...the projection of the initial point on a regress region (the ... See full document
11
An improved method for solving multiple-sets split feasibility problem
... relaxation projection method was proposed by Qu and Xiu [], and the variable Krasnosel’skii-Mann algorithm was proposed by Xu ...These algorithms first converted the problem to an equivalent ... See full document
12
An algorithm for the split feasibility problems with application to the split equality problem
... the multiple-sets split-feasibility problem that requires one to find a point closest to a family of closed convex sets in one space such that its image under a linear ... See full document
12
Iterative algorithm for solving the multiple sets split equality problem with split self adaptive step size in Hilbert spaces
... regards algorithms for solving the SFP, see [, ...convex sets, which is the original multiple-sets split feasibility problem (MSSFP), and introduced its ... See full document
9
Hierarchical problems with applications to mathematical programming with multiple sets split feasibility constraints
... a multiple sets split feasibility problem and a fixed point prob- ...and multiple sets split feasibility constraints, mathematical programming with fixed point ... See full document
31
Simultaneous extragradient iterative method to a split equality variational inequality problem and a multiple-sets split equality fixed point problem for multi-valued demicontractive mappings
... a split equality variational inequality problem and a multiple-sets split equality fixed point problem for two countable families of multi-valued demicontractive mappings in real ... See full document
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Algorithms with strong convergence for the split common solution of the feasibility problem and fixed point problem
... The above equivalence relation (.) reminds us to use fixed point method to solve (.). Many authors have given a continuation of the study on the CQ algorithm and its variant form. For related work, please refer ... See full document
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Iterative process for solving a multiple set split feasibility problem
... Starting Projection of the University of Shanghai for Science and Technology under Grant ID-10-303-002, and Young Teacher Training Projection Program of Shanghai for Science and ... See full document
10
Weak convergence theorems for split feasibility problems on zeros of the sum of monotone operators and fixed point sets in Hilbert spaces
... the split feasibility problem (SFP), which was first introduced by Censor and Elfving [], have appeared in various fields of science and technology, such as in signal processing, medical image ... See full document
17
Simultaneous and semi alternating projection algorithms for solving split equality problems
... The structure of the paper is as follows. In the next section, we present some concepts and lemmas which will be used in the main results. In Section 3, two classes of projection algorithms are provided and ... See full document
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Convergence rate analysis of an iterative algorithm for solving the multiple sets split equality problem
... The rest of this paper is organized as follows. In Sect. 2, we recall some definitions and lemmas which are useful for our convergence analysis later. We also introduce a concept of bounded Hölder regularity property for ... See full document
13
Adaptively relaxed algorithms for solving the split feasibility problem with a new step size
... bounded linear observation operator. A is sparse and the range of it is not closed in most inverse problems, thus A is often ill-condition and the problem is also ill-posed. When x is a sparse expansion, finding ... See full document
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