The Modified Iterative Reweighted ℓ 1 Minimization Algorithm
Iterative Reweighted Algorithms for Matrix Rank Minimization
... norm) minimization, which is guaranteed to find the minimum rank matrix under suitable ...of Iterative Reweighted Least Squares algorithms IRLS-p (with 0 ≤ p ≤ 1), as a computationally ...
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Fast ℓ 1-minimization algorithm for robust background subtraction
... approximative 1 -min algorithm This section will introduce the proposed approximative 1 -min ...Fig. 1 to express the core intuition of the ...The iterative process in conventional ...
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A new reweighted l1 minimization algorithm for image deblurring
... An iterative technique for absolute deviations curve ...D: Reweighted 1 -minimization for sparse solutions to underdetermined linear ...
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ISAR Imaging Based on Iterative Reweighted Lp Block Sparse Reconstruction Algorithm
... on Iterative Reweighted L p Block Sparse Reconstruction Algorithm Junjie Feng * and Gong Zhang Abstract—Sparse signal recovery algorithms can be used to improve radar imaging quality by using the ...
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An Iterative Algorithm of Solution for Quadratic Minimization Problem in Hilbert Spaces
... an iterative algorithm for finding a solution of quadratic minimization problem in the set of fixed points of a nonexpansive mapping and to prove a strong convergence theorem of the solution for ...
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An iterative algorithm for fixed point problem and convex minimization problem with applications
... an iterative sequence for finding a common element of the fixed points set of a strictly pseudocontractive mapping and the solution set of the constrained convex minimization problem for a convex and ...
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Modified Maximum A Posteriori Algorithm For Iterative Decoding of Turbo codes
... so-called iterative decoding or turbo decoding. An iterative decoding process is an iterative learning process for a complex system where the objective is to provide a good suboptimal estimate of a ...
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Iteratively Reweighted Least Squares Minimization With Prior Information A New Approach
... IRLS algorithm that makes use of this information to further reduce the number of measurements required to recover the solution with specified ...the algorithm of Daubechies et ...
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A modified ant colony optimization algorithm for network coding resource minimization
... a modified ant colony optimiza- tion approach for the network coding resource minimization ...problem: 1) a multi-dimensional pheromone maintenance mechanism is put forward to address the issue of ...
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A modified ant colony optimization algorithm for network coding resource minimization
... Hence, less computational time is consumed. For relatively small instances, such as Rnd-3 and Rnd-8, NCRM-ACO is 20 times faster compared to pEA, the second fastest algorithm. For large instances, e.g., Fix-4, ...
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Iterative Reweighted l1 Penalty Regression Approach for Line Spectral Estimation
... l 1 penalty ...the iterative reweighted l 1 ...the iterative reweighted l 1 method is better than other state-of-the-art algorithms in many ...
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Strong convergence of modified iterative algorithm for family of asymptotically nonexpansive mappings
... new modified implicit and explicit algorithms and prove strong convergence of the two algorithms to a common fixed point of a family of uniformly asymptotically regular asymptotically nonexpansive mappings in a ...
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An Analysis of a Recursive and an Iterative Algorithm for Generating Permutations Modified for Travelling Salesman Problem
... The graphs provide opportunities to formulate and solve complex practical problems effectively in a natural way and in an accessible language. Numerous problems in different fields, both in science and in practice (for ...
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An Analysis of a Recursive and an Iterative Algorithm for Generating Permutations Modified for Travelling Salesman Problem
... The graphs provide opportunities to formulate and solve complex practical problems effectively in a natural way and in an accessible language. Numerous problems in different fields, both in science and in practice (for ...
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Strong Convergence of a Modified Iterative Algorithm for Mixed Equilibrium Problems in Hilbert Spaces
... hybrid iterative scheme for finding a common element of the set of solutions of MEP and the set of common fixed points of finite many nonexpansive ...hybrid iterative scheme converge strongly to a common ...
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Modified Block Iterative Algorithm for Solving Convex Feasibility Problems in Banach Spaces
... the modified block iterative method to propose an iterative algorithm for solving the convex feasibility problems for an infinite family of quasi-φ-asymptotically ...
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Accelerating ℓ 1 − ℓ 2 deblurring using wavelet expansions of operators
... • Use more sophisticated minimization algorithms to accelerate convergence. 2 Main ideas The method proposed in this paper relies on three ideas. First, function F in equation (3) can be approximated by another ...
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Proximal iteratively reweighted algorithm for low rank matrix recovery
... quasi-norm minimization to 1 minimiza- tion in compressive sampling ...quasi-norm minimization [11–13] was introduced instead of the nuclear norm minimization in order to give a better approx- ...
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The iterative reweighted Mixed-Norm Estimate for spatio-temporal MEG/EEG source reconstruction
... new algorithm for solving the MxNE surrogate problems combining BCD and a forward active set strategy, which significantly decreases the computation time compared to the original MxNE algorithm ...new ...
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Performance Analysis of Iterative Closest Point (ICP) Algorithm using Modified Hausdorff Distance
... The Iterative Closest Point Algorithm of Besl and Mckay is one of the most popular method used for rigid transformation of roughly aligned data ...ICP algorithm has become the dominant method for ...
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