Search results for "Conjugate gradient method"

showing 10 items of 23 documents

Covariant approximation averaging

2015

We present a new class of statistical error reduction techniques for Monte-Carlo simulations. Using covariant symmetries, we show that correlation functions can be constructed from inexpensive approximations without introducing any systematic bias in the final result. We introduce a new class of covariant approximation averaging techniques, known as all-mode averaging (AMA), in which the approximation takes account of contributions of all eigenmodes through the inverse of the Dirac operator computed from the conjugate gradient method with a relaxed stopping condition. In this paper we compare the performance and computational cost of our new method with traditional methods using correlation…

PhysicsNuclear and High Energy PhysicsHigh Energy Physics::LatticeMonte Carlo methodLattice field theoryHigh Energy Physics - Lattice (hep-lat)FOS: Physical sciencesLattice QCDDirac operatorsymbols.namesakeHigh Energy Physics - LatticeConjugate gradient methodLattice gauge theoryQuantum mechanicssymbolsCovariant transformationVector mesonMathematical physics
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A Lagrange Multiplier Based Domain Decomposition Method for the Solution of a Wave Problem with Discontinuous Coefficients

2008

In this paper we consider the numerical solution of a linear wave equation with discontinuous coefficients. We divide the computational domain into two subdomains and use explicit time difference scheme along with piecewise linear finite element approximations on semimatching grids. We apply boundary supported Lagrange multiplier method to match the solution on the interface between subdomains. The resulting system of linear equations of the “saddle-point” type is solved efficiently by a conjugate gradient method.

Piecewise linear functionsymbols.namesakeConstraint algorithmLagrange multiplierConjugate gradient methodMathematical analysisMathematicsofComputing_NUMERICALANALYSISsymbolsBoundary (topology)Domain decomposition methodsSystem of linear equationsDomain (mathematical analysis)Mathematics
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Iterative Regularization Techniques in Image Reconstruction

2000

In this survey we review recent developments concerning the efficient iterative regularization of image reconstruction problems in atmospheric imaging. We present a number of preconditioners for the minimization of the corresponding Tikhonov functional, and discuss the alternative of terminating the iteration early, rather than adding a stabilizing term in the Tikhonov functional. The methods are examplified for a (synthetic) model problem.

Point spread functionTikhonov regularizationMathematical optimizationConjugate gradient methodMinificationIterative reconstructionRegularization (mathematics)AlgorithmSignal subspaceMathematics
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Tridiagonal preconditioning for Poisson-like difference equations with flat grids: Application to incompressible atmospheric flow

2011

AbstractThe convergence of many iterative procedures, in particular that of the conjugate gradient method, strongly depends on the condition number of the linear system to be solved. In cases with a large condition number, therefore, preconditioning is often used to transform the system into an equivalent one, with a smaller condition number and therefore faster convergence. For Poisson-like difference equations with flat grids, the vertical part of the difference operator is dominant and tridiagonal and can be used for preconditioning. Such a procedure has been applied to incompressible atmospheric flows to preserve incompressibility, where a system of Poisson-like difference equations is …

Poisson-like equationBiconjugate gradient method010504 meteorology & atmospheric sciencesTridiagonal matrixOperator (physics)Applied MathematicsLinear systemGeometryPreconditioning010103 numerical & computational mathematics01 natural sciencesComputational MathematicsConjugate gradient methodConvergence (routing)Convergence accelerationApplied mathematicsDynamic pressure0101 mathematicsCondition numberCondition numberAtmospheric model0105 earth and related environmental sciencesMathematicsFlat gridsJournal of Computational and Applied Mathematics
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QR-Factorization Algorithm for Computed Tomography (CT): Comparison With FDK and Conjugate Gradient (CG) Algorithms

2018

[EN] Even though QR-factorization of the system matrix for tomographic devices has been already used for medical imaging, to date, no satisfactory solution has been found for solving large linear systems, such as those used in computed tomography (CT) (in the order of 106 equations). In CT, the Feldkamp, Davis, and Kress back projection algorithm (FDK) and iterative methods like conjugate gradient (CG) are the standard methods used for image reconstruction. As the image reconstruction problem can be modeled by a large linear system of equations, QR-factorization of the system matrix could be used to solve this system. Current advances in computer science enable the use of direct methods for…

QR-factorization algorithmComputer scienceIterative methodImage qualityLinear systemDavis and Kress (FDK)Iterative reconstruction3-D images reconstructionSystem of linear equationsAtomic and Molecular Physics and OpticsConjugate gradient (CG)FeldkampQR decompositionMatrix (mathematics)Conjugate gradient methodRadiology Nuclear Medicine and imagingMedical imagingMATEMATICA APLICADAInstrumentationAlgorithmComputed tomography (CT)Reconstruction algorithmsReconstruction toolkit (RTK)
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A Mlp-Based Digit And Uppercase Characters Recognition System

1997

A simple software solution for digit and uppercase handwritten characters recognition is presented. The proposed solution is based on a two-layer Multi Layer Perceptron (MLP) trained by a conjugate gradient descent (CGD) optimization algorithm. This neural network is embedded in a software tool for automatic processing of forms achieved using a scanner. The chosen solutions allow us to obtain good results both in terms of recognition rate and speed. In the paper are fully described design details and experimental results.

ScannerArtificial neural networkComputer sciencebusiness.industrySpeech recognitionNumerical digitComputingMethodologies_PATTERNRECOGNITIONSoftwareSimple (abstract algebra)Computer Science::Computer Vision and Pattern RecognitionMultilayer perceptronConjugate gradient methodLogical matrixbusiness
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Iterative moment method for electromagnetic transients in grounding systems on CRAY T3D

1996

In this paper the parallel aspects of an electromagnetic model for transients in grounding systems based on an iterative scheme are investigated in a multiprocessor environment. A coarse and fine grain parallel solutions have been developed on the CRAY T3D, housed at CINECA, equipped with 64 processors working in space sharing modality. The performances of the two parallel approaches implemented according to the work sharing parallel paradigm have been evaluated for different problem sizes employing variable number of processors.

Scheme (programming language)Moment (mathematics)Fine grainComputer scienceGroundConjugate gradient methodMultiprocessingParallel computingcomputercomputer.programming_languageComputational science
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Multilayer neural networks: an experimental evaluation of on-line training methods

2004

Artificial neural networks (ANN) are inspired by the structure of biological neural networks and their ability to integrate knowledge and learning. In ANN training, the objective is to minimize the error over the training set. The most popular method for training these networks is back propagation, a gradient descent technique. Other non-linear optimization methods such as conjugate directions set or conjugate gradient have also been used for this purpose. Recently, metaheuristics such as simulated annealing, genetic algorithms or tabu search have been also adapted to this context.There are situations in which the necessary training data are being generated in real time and, an extensive tr…

Training setGeneral Computer ScienceArtificial neural networkbusiness.industryComputer scienceComputer Science::Neural and Evolutionary ComputationMathematicsofComputing_NUMERICALANALYSISContext (language use)Management Science and Operations ResearchMachine learningcomputer.software_genreBackpropagationTabu searchModeling and SimulationConjugate gradient methodGenetic algorithmSimulated annealingArtificial intelligencebusinessGradient descentcomputerMetaheuristicComputers & Operations Research
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Fast nonstationary preconditioned iterative methods for ill-posed problems, with application to image deblurring

2013

We introduce a new iterative scheme for solving linear ill-posed problems, similar to nonstationary iterated Tikhonov regularization, but with an approximation of the underlying operator to be used for the Tikhonov equations. For image deblurring problems, such an approximation can be a discrete deconvolution that operates entirely in the Fourier domain. We provide a theoretical analysis of the new scheme, using regularization parameters that are chosen by a certain adaptive strategy. The numerical performance of this method turns out to be superior to state-of-the-art iterative methods, including the conjugate gradient iteration for the normal equation, with and without additional precondi…

Well-posed problemDeblurringMathematical optimizationIterative methodApplied MathematicsRegularization (mathematics)Computer Science ApplicationsTheoretical Computer ScienceTikhonov regularizationConjugate gradient methodSignal ProcessingApplied mathematicsDeconvolutionMathematical PhysicsLinear least squaresMathematics
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An optimization-based approach for solving a time-harmonic multiphysical wave problem with higher-order schemes

2013

This study considers developing numerical solution techniques for the computer simulations of time-harmonic fluid-structure interaction between acoustic and elastic waves. The focus is on the efficiency of an iterative solution method based on a controllability approach and spectral elements. We concentrate on the model, in which the acoustic waves in the fluid domain are modeled by using the velocity potential and the elastic waves in the structure domain are modeled by using displacement.Traditionally, the complex-valued time-harmonic equations are used for solving the time-harmonic problems. Instead of that, we focus on finding periodic solutions without solving the time-harmonic problem…

fourth-order Runge–Kuttata113Numerical AnalysisOptimization problemfluid–structure interactionta114Physics and Astronomy (miscellaneous)DiscretizationApplied Mathematicsta111Mathematical analysisSpectral element methodspectral element methodAcoustic wavecoupled problemcontrollabilityComputer Science ApplicationsControllabilityComputational MathematicsMultigrid methodRate of convergenceModeling and SimulationConjugate gradient methodMathematicsJournal of Computational Physics
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