On the preconditioning of the primal form of TFOV-based image deblurring model [PDF]
Scientific Reports, 2023 To address the staircasing problem in deblurred images generated by a simple total variation (TV) based model, one approach is to use the total fractional-order variation (TFOV) image deblurring model.
Junseok Kim, Shahabz Ahmad
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Deflated preconditioned conjugate gradient method for solving single-step BLUP models efficiently [PDF]
Genetics Selection Evolution, 2018 Background The single-step single nucleotide polymorphism best linear unbiased prediction (ssSNPBLUP) method, such as single-step genomic BLUP (ssGBLUP), simultaneously analyses phenotypic, pedigree, and genomic information of genotyped and non-genotyped
Jérémie Vandenplas +3 more
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Least squares reverse time migration imaging with illumination preconditioned based on improved PRP conjugate gradients [PDF]
Scientific Reports, 2023 Least squares reverse time migration (LSRTM) imaging is the one of the most accurate methods for migration imaging at present, and Polak–Ribiere–Polyak conjugate gradient (PRPCG) for LSRTM has the good numerical performance but weak convergence, so we ...
Xiaodan Zhang +5 more
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Parallel preconditioned conjugate gradient algorithm on GPU
Journal of Computational and Applied Mathematics, 2012 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Helfenstein, Rudi, Koko, Jonas
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Preconditioned conjugate gradients for solving singular systems
Journal of Computational and Applied Mathematics, 1988 Sparse singular systems have to be solved for instance with semi-definite Neumann-problems. Such systems \(Ax=b\) with a rank deficiency of one can be solved by fixing a \(x_ i\), deleting the corresponding row and column, adjusting the right hand side and solving the new system with a preconditioned conjugate gradient method.
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Preconditioned conjugate gradient methods for absolute value equations
Journal of Numerical Analysis and Approximation Theory, 2020 We investigate the NP-hard absolute value equations (AVE), \(Ax-B|x| =b\), where \(A,B\) are given symmetric matrices in \(\mathbb{R}^{n\times n}, \ b\in \mathbb{R}^{n}\).
Nassima Anane, Mohamed Achache
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A Combined Conjugate Gradient Quasi-Newton Method with Modification BFGS Formula
International Journal of Analysis and Applications, 2023 The conjugate gradient and Quasi-Newton methods have advantages and drawbacks, as although quasi-Newton algorithm has more rapid convergence than conjugate gradient, they require more storage compared to conjugate gradient algorithms.
Mardeen Sh. Taher, Salah G. Shareef
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Reproducibility strategies for parallel Preconditioned Conjugate Gradient [PDF]
Journal of Computational and Applied Mathematics, 2020 [EN] The Preconditioned Conjugate Gradient method is often used in numerical simulations. While being widely used, the solver is also known for its lack of accuracy while computing the residual. In this article, we aim at a twofold goal: enhance the accuracy of the solver but also ensure its reproducibility in a message-passing implementation.
Iakymchuk, Roman +4 more
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A New Preconditioned Inexact Line-Search Technique for Unconstrained Optimization [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2012 In this paper, we study the global convergence properties of the new class of preconditioned conjugate gradient descent algorithm, when applied to convex objective non-linear unconstrained optimization functions.
Abbas Al-Bayati, Ivan Latif
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Using the Update of Conditional BFGS in Constrained Optimization [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2009 In this paper, we have used one of the preconditioned conjugate gradient algorithm with the Quasi – Newton approximation; namely the BFGS preconditioned algorithm which was suggested by (AL-Bayati and Aref, 2001).
Abbas Al-Bayati, Ban Mitras
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