Search results for "Condition number"

showing 6 items of 6 documents

Norm estimates for operators from Hp to ℓq

2008

Abstract We give upper and lower estimates of the norm of a bounded linear operator from the Hardy space H p to l q in terms of the norm of the rows and the columns of its associated matrix in certain vector-valued sequence spaces.

Applied MathematicsMathematical analysisMatrix normSchatten class operatorHardy spaceBounded operatorCombinatoricssymbols.namesakesymbolsSchatten normCondition numberOperator normAnalysisDual normMathematicsJournal of Mathematical Analysis and Applications
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A new solver for incompressible non-isothermal flows in natural and mixed convection over unstructured grids

2022

Abstract In the present paper we propose a new numerical methodology for the solution of 2D non-isothermal incompressible flows for natural and mixed convection in irregular geometries. The governing equations are the Incompressible Navier-Stokes Equations and the Energy Conservation Equation. Fluid velocity and temperature are coupled in the buoyancy term of the momentum equations according to the Oberbeck–Boussinesq approximation. The governing equations are discretized over unstructured triangular meshes satisfying the Delaunay property. Thanks to the Oberbeck–Boussinesq hypothesis, the flow and energy problems are solved in an uncoupled way, and two fractional time step procedures are s…

DiscretizationDelaunay triangulationApplied MathematicsEulerian pathUnstructured meshesSolverNumerical methodSettore ICAR/01 - IdraulicaPhysics::Fluid Dynamicssymbols.namesakeMatrix (mathematics)Flow (mathematics)Natural convectionModeling and SimulationPredictor-corrector schemesymbolsApplied mathematicsIncompressible fluidMixed convectionCondition numberMathematicsNumerical stability
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Combined K-Best sphere decoder based on the channel matrix condition number

2008

It is known that sphere decoding (SD) methods can provide maximum-likelihood (ML) detection over Gaussian MIMO channels with lower complexity than the exhaustive search. Channel matrix condition number represents an important influence on the performance of usual detectors. Throughout this paper, two particular cases of a SD method called K-Best carry out a combined detection in order to reduce the computational complexity with predictable performance degradation. Algorithm selection is based on channel matrix condition number thresholding. K-Best is a suboptimal SD algorithm for finding the ML solution of a detection problem. It is based on a fixed complexity tree search, set by a paramete…

Mathematical optimizationComputational complexity theoryGaussianBrute-force searchThresholdingsymbols.namesakeMatrix (mathematics)symbolsCondition numberAlgorithmDecoding methodsComputer Science::Information TheoryMathematicsCommunication channel2008 3rd International Symposium on Communications, Control and Signal Processing
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On the condition number of the antireflective transform

2010

Abstract Deconvolution problems with a finite observation window require appropriate models of the unknown signal in order to guarantee uniqueness of the solution. For this purpose it has recently been suggested to impose some kind of antireflectivity of the signal. With this constraint, the deconvolution problem can be solved with an appropriate modification of the fast sine transform, provided that the convolution kernel is symmetric. The corresponding transformation is called the antireflective transform. In this work we determine the condition number of the antireflective transform to first order, and use this to show that the so-called reblurring variant of Tikhonov regularization for …

Numerical AnalysisAlgebra and Number TheoryBoundary conditionsTikhonov regularizationMathematical analysisDeconvolutionUpper and lower boundsRegularization (mathematics)ConvolutionTikhonov regularizationTransformation (function)Discrete Mathematics and CombinatoricsApplied mathematicsFast sine transformGeometry and TopologyUniquenessDeconvolutionCondition numberAntireflective transformMathematicsLinear Algebra and its Applications
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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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The smallest singular value of a shifted $d$-regular random square matrix

2017

We derive a lower bound on the smallest singular value of a random d-regular matrix, that is, the adjacency matrix of a random d-regular directed graph. Specifically, let $$C_1<d< c n/\log ^2 n$$ and let $$\mathcal {M}_{n,d}$$ be the set of all $$n\times n$$ square matrices with 0 / 1 entries, such that each row and each column of every matrix in $$\mathcal {M}_{n,d}$$ has exactly d ones. Let M be a random matrix uniformly distributed on $$\mathcal {M}_{n,d}$$ . Then the smallest singular value $$s_{n} (M)$$ of M is greater than $$n^{-6}$$ with probability at least $$1-C_2\log ^2 d/\sqrt{d}$$ , where c, $$C_1$$ , and $$C_2$$ are absolute positive constants independent of any other parameter…

Statistics and ProbabilityIdentity matrixAdjacency matrices01 natural sciencesSquare matrixCombinatorics010104 statistics & probabilityMatrix (mathematics)Mathematics::Algebraic GeometryFOS: MathematicsMathematics - Combinatorics60B20 15B52 46B06 05C80Adjacency matrix0101 mathematicsCondition numberCondition numberMathematicsRandom graphsRandom graphLittlewood–Offord theorySingularity010102 general mathematicsProbability (math.PR)InvertibilityRegular graphsSingular valueSmallest singular valueAnti-concentrationSingular probabilitySparse matricesCombinatorics (math.CO)Statistics Probability and UncertaintyRandom matricesRandom matrixMathematics - ProbabilityAnalysis
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