[PDF] Top 20 A preconditioning method of the CQ algorithm for solving an extended split feasibility problem
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A preconditioning method of the CQ algorithm for solving an extended split feasibility problem
... the CQ algorithm so that it can easily be implemented and converge faster is the hot ...relaxed CQ algorithm for solving the SFP, then the orthogonal projections onto halfspaces C k and ... See full document
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Preconditioning methods for solving a general split feasibility problem
... modulus method and relaxed method, two modified projection algo- rithms for solving the GSFP and some approximate methods for algorithm executing have been ...by preconditioning ... See full document
11
An improved method for solving multiple-sets split feasibility problem
... basic CQ algorithm was proposed by Byrne [], then it was generalized to MSSFP by Censor ...relaxed CQ algorithm was proposed by Yang [], the half-space relaxation projection method ... See full document
12
Simultaneous iterative algorithms for the split common fixed-point problem of generalized asymptotically quasi-nonexpansive mappings without prior knowledge of operator norms
... alternating algorithm (.) and the simultaneous algorithm (.) for solving SCFP ...helpful method for estimating the stepsizes which do not need prior knowledge of the operator norms for ... See full document
12
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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Iterative approximation of solutions for proximal split feasibility problems
... popular algorithm that solves the SFP (.) is due to Byrne’s CQ algorithm [] which is found to be a gradient-projection method (GPM) in convex ...the CQ algorithm, and Zhao and ... See full document
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An algorithm for the split feasibility problems with application to the split equality problem
... the CQ algorithm in the setting of finite dimensional spaces by adopting the Armijo-like searches, which need not compute the matrix inverses and the largest eigenvalue of the matrix A ...multiple-sets ... See full document
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Iterative methods for solving the multiple-sets split feasibility problem with splitting self-adaptive step size
... The CQ algorithm used a fixed step size, which relies on the spectral norm of the linear operator ...search method to solve the SFP, for which there is no need to know the prior norm of ...relaxed ... See full document
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Hybrid CQ projection algorithm with line search process for the split feasibility problem
... selfadaptive method for solving variational ...for solving variational inequality ...the split feasibility problem [, ...projection method was developed by Nakajo and ... See full document
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Iterative process for solving a multiple set split feasibility problem
... relaxed CQ algorithm by using a new searching direction, which is not the gradient of a corresponding ...relaxed CQ algorithm converges more quickly than the existing ... See full document
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Relaxed alternating CQ algorithms for the split equality problem in Hilbert spaces
... new algorithm for solving the ...projection algorithm, we propose two new relaxed alternating algorithms for the SEP governed by level sets, which present an affirmative answer to Moudafi’s ...the ... See full document
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Strong convergence of a self-adaptive method for the split feasibility problem
... for solving the SFP. Their proposal is an iterative algorithm, which involves the computation of the inverse of a matrix, which is known to be a difficult ...so-called CQ algorithm, which ... See full document
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Adaptively relaxed algorithms for solving the split feasibility problem with a new step size
... By means of new analysis techniques, we have proved several kinds of weak and strong convergence theorems of the proposed algorithms for solving SFP (.), which improved, extended, and complemented those ... See full document
22
Strong convergence of a relaxed CQ algorithm for the split feasibility problem
... The split feasibility problem (SFP) is finding a point in a given closed convex subset of a Hilbert space such that its image under a bounded linear operator belongs to a given closed convex subset of ... See full document
11
New generalized variable stepsizes of the CQ algorithm for solving the split feasibility problem
... Variable stepsize methods are effective for various modified CQ algorithms to solve the split feasibility problem (SFP). The purpose of this paper is first to introduce two new simpler variable ... See full document
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Iterative algorithm for solving the multiple sets split equality problem with split self adaptive step size in Hilbert spaces
... For solving it, Byrne [, ] presented the well-known CQ-algorithm, inspired by the idea of iterative scheme of fixed point ...the CQ- algorithm is fixed, depending upon the norm of the ... See full document
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The regularized CQ algorithm without a priori knowledge of operator norm for solving the split feasibility problem
... Recently, the SFP has been studied extensively by many authors. However, some algo- rithms need to compute A , and this is not an easy thing to work out. Others do not need to compute A, but the algorithms always have ... See full document
10
The common solutions of the split feasibility problems and fixed point problems
... The SCFP is a natural extension of the SFP and of the convex feasibility problem. The SCFP was firstly considered by Censor and Segal in [] where S and T are directed op- erators which include the ... See full document
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Preconditioned ADMM with nonlinear operator constraint
... generic problem formulation, then address its numerical minimisation via a generalised ADMM method with linearised operator ...NL-PDHGM method (indicating a local conver- gence result of the proposed ... See full document
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Split feasibility problems for total quasi-asymptotically nonexpansive mappings
... The split feasibility problem (SFP) in finite-dimensional 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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