Results 61 to 70 of about 12,511,953 (289)
On Robust Incomplete Choleski-Conjugate Gradient Method And Its Modification [PDF]
, 1989 This paper includes a solver for a large sparse set of linear algebraic equations which are obtained by the application of the finite element method to static structural problems.
Fujiwara, Kohji, Taniguchi, Takeo
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Leucine‐rich glioma inactivated 1 (LGI1) is a ganglioside‐binding protein
FEBS Letters, EarlyView.Neuronal hyperexcitability associated with a decrease/absence of the extracellular protein LGI1 has been suggested to be primarily due to the downregulation of Kv1 channel expression. The molecular mechanisms underlying this decrease have not yet been elucidated.
Kévin Debreux +7 more
wiley +1 more source
An Accelerated Riemannian Conjugate Gradient Method Based on the Barzilai–Borwein Technique
MathematicsThis paper proposes an accelerated Riemannian conjugate gradient method based on the Barzilai-Borwein (BB) technique, termed ABBSRCG, for unconstrained optimization on Riemannian manifolds. Building upon classical Riemannian conjugate gradient frameworks,
Ziyin Ma, Tao Yan, Shimin Zhao
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A New sufficient descent Conjugate Gradient Method for Nonlinear Optimization [PDF]
المجلة العراقية للعلوم الاحصائية, 2014 In this paper, a new conjugate gradient method based on exact step size which produces sufficient descent search direction at every iteration is introduced. We prove its global convergence, and give some results to illustrate its efficiency by comparing
Dr. Basim A. Hassan, Omer M. Esmaeel
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Going viral − Virus‐targeting nanobodies for research, diagnostics and therapy
FEBS Letters, EarlyView.The increasing prevalence of viral diseases represents a major threat for global human health. Nanobodies, small binding fragments derived from camelid heavy‐chain antibodies, offer versatile tools for viral research, diagnostics, and antiviral therapy.
Domenic Ebert, Ulrich Rothbauer
wiley +1 more source
A Modified Conjugate Gradient Method for Unconstrained Optimization [PDF]
, 2013 Conjugate gradient methods are an important class of methods for solving unconstrained optimization problems, especially for large-scale problems. Recently, they have been much studied.
Li, Can
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A New Smoothing Conjugate Gradient Method for Solving Nonlinear Nonsmooth Complementarity Problems
Algorithms, 2015 In this paper, by using the smoothing Fischer-Burmeister function, we present a new smoothing conjugate gradient method for solving the nonlinear nonsmooth complementarity problems.
Ajie Chu, Shouqiang Du, Yixiao Su
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FEBS Letters, EarlyView.Vacuolar H+‐ATPase (V‐ATPase) is a multisubunit rotary proton pump that acidifies intracellular compartments. Using elastic network models, we identified conserved hinge residues that govern its large‐scale functional motions. We show that intrinsically encoded ‘soft modes’ drive critical functional transitions, including rotary catalysis and ...
Diksha Parwana +3 more
wiley +1 more source
A Novel hybridization of CG-techniques for Solving Unconstrained Optimization Problems
Wasit Journal for Pure SciencesConjugate gradient methods are an extremely helpful way for handling large scale non-linear optimization issues. In this paper, based on the three famous Dai-yuan (DY), Liu–Storey (LS)and Conjugate-Descent (CD) conjugate gradient methods, a new hybrid ...
Hawraz Jabbar
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Dai-Kou type conjugate gradient methods with a line search only using gradient
Journal of Inequalities and Applications, 2017 In this paper, the Dai-Kou type conjugate gradient methods are developed to solve the optimality condition of an unconstrained optimization, they only utilize gradient information and have broader application scope.
Yuanyuan Huang, Changhe Liu
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