Results 31 to 40 of about 888,833 (294)
Differentiating the Method of Conjugate Gradients [PDF]
SIAM Journal on Matrix Analysis and Applications, 2014 The method of conjugate gradients (CG) is widely used for the iterative solution of large sparse systems of equations $Ax=b$, where $A\in\Re^{n\times n}$ is symmetric positive definite. Let $x_k$ denote the $k$th iterate of CG. This is a nonlinear differentiable function of $b$. In this paper we obtain expressions for $J_k$, the Jacobian matrix of $x_k$
Serge Gratton +3 more
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Reducing Impulse Noise in Images Using an Improved Formula Conjugate Gradient Method
Zanco Journal of Pure and Applied SciencesThe conjugate formula's significance is frequently emphasised by conjugate gradient approaches. In this paper, a novel conjugate coefficient for the conjugate gradient technique is introduced using a quadratic model and conjugacy condition.
Basim A. Hassan, Yousif Ali Mohammed
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Two modified hybrid conjugate gradient methods based on a hybrid secant equation
Mathematical Modelling and Analysis, 2013 Taking advantage of the attractive features of Hestenes–Stiefel and Dai–Yuan conjugate gradient methods, we suggest two globally convergent hybridizations of these methods following Andrei's approach of hybridizing the conjugate gradient parameters ...
Saman Babaie-Kafaki, Nezam Mahdavi-Amiri
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SIAM Journal on Scientific Computing, 2000 The author discusses the conjugate gradient method for the numerical solution of a linear large sparse system, using preconditioning technique. To maintain the optimal convergence properties of the method, the author considers a variant of the conjugate gradient method (called flexible conjugate gradient) that performs an explicit orthogonalization of ...
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Nonlinear conjugate gradient methods [PDF]
, 2014 summary:Modifications of nonlinear conjugate gradient method are described and ...
Lukšan, Ladislav, Vlček, Jan
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Two efficient modifications of AZPRP conjugate gradient method with sufficient descent property
Journal of Inequalities and Applications, 2022 The conjugate gradient method can be applied in many fields, such as neural networks, image restoration, machine learning, deep learning, and many others.
Zabidin Salleh +2 more
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Computing several eigenpairs of Hermitian problems by conjugate gradient iterations
, 2008 The paper is concerned with algorithms for computing several extreme eigenpairs of Hermitian problems based on the conjugate gradient method. We analyse computational strategies employed by various algorithms of this kind reported in the literature and ...
Ovtchinnikov, E.
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Algorithm for Scaling Variables in Minimization Methods
AlgorithmsEliminating poor scaling of variables of minimized functions is a pressing issue in solving high-dimensional minimization problems where it is impossible to use methods that change the metric of the space with full-scale metric matrices.
Elena Tovbis +2 more
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Two New Conjugate Gradient Methods for Unconstrained Optimization
Complexity, 2020 The conjugate gradient method is very effective in solving large-scale unconstrained optimal problems. In this paper, on the basis of the conjugate parameter of the conjugate descent (CD) method and the second inequality in the strong Wolfe line search ...
Meixing Liu, Guodong Ma, Jianghua Yin
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Nonlinear Conjugate Gradient Methods with Wolfe Type Line Search
Abstract and Applied Analysis, 2013 Nonlinear conjugate gradient method is one of the useful methods for unconstrained optimization problems. In this paper, we consider three kinds of nonlinear conjugate gradient methods with Wolfe type line search for unstrained optimization problems ...
Yuan-Yuan Chen, Shou-Qiang Du
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