Results 31 to 40 of about 654,439 (198)
Preconditioned nonlinear conjugate gradient method for micromagnetic energy minimization [PDF]
Fast computation of demagnetization curves is essential for the computational design of soft magnetic sensors or permanent magnet materials. We show that a sparse preconditioner for a nonlinear conjugate gradient energy minimizer can lead to a speed up ...
L. Exl +5 more
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A new conjugate gradient method for acceleration of gradient descent algorithms
An accelerated of the steepest descent method for solving unconstrained optimization problems is presented. which propose a fundamentally different conjugate gradient method, in which the well-known parameter βk is computed by an new formula.
Rahali Noureddine +2 more
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A New Modified Conjugate Gradient for Nonlinear Minimization Problems
The conjugate gradient is a highly effective technique to solve the unconstrained nonlinear minimization problems and it is one of the most well-known methods. It has a lot of applications.
Hussein Ageel Khatab, Salah G. Sharef
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Two Versions of the Spectral Nonlinear Conjugate Gradient Method
The nonlinear conjugate gradient method is widely used to solve unconstrained optimization problems. In this paper the development of different versions of nonlinear conjugate gradient methods with global convergence properties proved.
Basim A. Hassan, Haneen A. Alashoor
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The conjugate gradient (CG) method has played a special role in solving large-scale nonlinear optimization problems due to the simplicity of their very low memory requirements.
Shengwei Yao, Xiwen Lu, Zengxin Wei
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Two efficient modifications of AZPRP conjugate gradient method with sufficient descent property
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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A Bayesian Conjugate Gradient Method [PDF]
A fundamental task in numerical computation is the solution of large linear systems. The conjugate gradient method is an iterative method which offers rapid convergence to the solution, particularly when an effective preconditioner is employed.
J. Cockayne, C. Oates, M. Girolami
semanticscholar +1 more source
Algorithm for Scaling Variables in Minimization Methods
Eliminating 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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Reducing Impulse Noise in Images Using an Improved Formula Conjugate Gradient Method
The 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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Combining the projection method of Solodov and Svaiter with the Liu-Storey and Fletcher Reeves conjugate gradient algorithm of Djordjević for unconstrained minimization problems, a hybrid conjugate gradient algorithm is proposed and extended to solve ...
Abdulkarim Hassan Ibrahim +4 more
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