Minimum norm
Iterative algorithms for minimum-norm fixed point of non-expansive mapping in hilbert space
... Motivated and inspired by the above studies, the purpose of this article is to consider another way to ensure the well defined of the iterative sequence. That is, we replace the closed convex subset C by a closed convex ...
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Augmented Lagrangian Method for Finding Minimum Norm Solution to the Absolute Value Equation
... follows. Minimum norm solution of AVE is described in Section ...compute minimum norm solution for some randomly generated AVE to demonstrate the effectiveness of our ...
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Approximation of the common minimum-norm fixed point of a finite family of asymptotically nonexpansive mappings
... Recall that a point x ¯ ∈ K is said to be a fixed point of T if T(¯ x) = x. We denote the set of ¯ fixed points of T by F(T ), i.e., F(T ) := {¯ x ∈ K : T x ¯ = x}. Therefore, finding a solution to ¯ the split feasibility ...
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An algorithm for a common minimum norm zero of a finite family of monotone mappings in Banach spaces
... Remark . Theorem . provides convergence scheme to the common minimum-norm zero of a finite family of monotone mappings which improves the results of Bauschke et al. [] to Banach spaces more general than ...
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Construction of minimum norm fixed points of pseudocontractions in Hilbert spaces
... the minimum-norm solution of a given fixed point ...the minimum-norm fixed point of the ...finding minimum-norm solutions of nonlinear fixed point and variational inequality ...
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Regularized gradient projection methods for finding the minimum norm solution of the constrained convex minimization problem
... In a real Hilbert space, there are many methods to solve the constrained convex mini- mization problem. However, most of them cannot find the minimum-norm solution. In this article, we use the regularized ...
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On Real Matrices to Least Squares g Inverse and Minimum Norm g Inverse of Quaternion Matrices
... Through the real representations of quaternion matrices and matrix rank method, we give the expression of the real ma- trices in least-squares g-inverse and minimum norm g-inverse. From these formulas, we ...
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Boundary point algorithms for minimum norm fixed points of nonexpansive mappings
... The purpose of this paper is to propose three new algorithms for finding the minimum norm fixed point of T . The strong convergence theorems are proved under some assump- tions. The main advantage of the ...
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A comparison of minimum norm and MUSIC for a combined MEG/EEG sensor array
... the minimum norm and MUSIC, respec- ...the minimum norm solution is ...the minimum norm and the MUSIC solution for a cortical gyrus activation is smaller than for a cortical ...
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Iterative methods for finding the minimum norm solution of the standard monotone variational inequality problems with applications in Hilbert spaces
... The purpose of this paper is to solve the questions above. We introduce implicit and explicit iterative methods for construction of the solution of the monotone variational in- equality problem and prove that our ...
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Iterative algorithms for finding the zeroes of sums of operators
... The paper is organized as follows. In Section , we define the concept of the minimal norm solution of the problem P (.). Using Tychonov regularization, we obtain a net of solutions for some minimization problem ...
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A scheme for a solution of a variational inequality for a monotone mapping and a fixed point of a pseudocontractive mapping
... 13. Yamada, I: The hybrid steepest-descent method for variational inequality problems over the intersection of the fixed point sets of nonexpansive mappings. In: Butnariu, D, Censor, Y, Reich, S (eds.) Inherently Parallel ...
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Approximating a common point of fixed points of a pseudocontractive mapping and zeros of sum of monotone mappings
... It is our purpose in this paper to introduce an iterative scheme which converges strongly to a common minimum-norm point of fixed points of a Lipschitzian pseudocontractive mapping and zeros of sum of two ...
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Approximating Curve and Strong Convergence of the CQ Algorithm for the Split Feasibility Problem
... that F / ∅; that is, the solution set of SFP 1.1 is nonempty. The fact that F is nonempty closed convex set thus allows us to introduce the concept of minimum-norm solution of SFP 1.1. Definition 3.3. An ...
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Time Optimal and Minimum Effort Control of Time-invariant Systems.
... Two critical aspects of the semi-smooth algorithm are the initialization of the unknown parameters and obtaining solutions efficiently for varying known parameters. Initialization based on solutions of the L 2 ...
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Ordinary and generalized Green’s functions for the second order discrete nonlocal problems
... In this paper, we investigate the properties of a generalized Green’s function describing the minimum norm least squares solution for a second order discrete problem with two nonlocal conditions. The ...
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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 ...
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A Generalization of Cramer’s Rule
... It is known and simple proven that there is a solution for all b ∈ IR n if, and only if, the rows of A are linearly independent, and the minimum norm solution is given by the Moore-Penro[r] ...
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Constructed nets with perturbations for equilibrium and fixed point problems
... In this paper, an implicit net with perturbations for solving the mixed equilibrium problems and fixed point problems has been constructed and it is shown that the proposed net converges strongly to a common solution of ...
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Krasnoselskii-Mann method for non-self mappings
... He, S, Zhu, W: A modified Mann iteration by boundary point method for finding minimum-norm fixed point of nonexpansive mappings. He, S, Yang, C: Boundary point algorithms for minimum norm fi[r] ...
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