Search results for "convexity"

showing 10 items of 57 documents

On the exhaustive generation of k-convex polyominoes

2017

The degree of convexity of a convex polyomino P is the smallest integer k such that any two cells of P can be joined by a monotone path inside P with at most k changes of direction. In this paper we present a simple algorithm for computing the degree of convexity of a convex polyomino and we show how it can be used to design an algorithm that generates, given an integer k, all k-convex polyominoes of area n in constant amortized time, using space O(n). Furthermore, by applying few changes, we are able to generate all convex polyominoes whose degree of convexity is exactly k.

General Computer SciencePolyomino0102 computer and information sciences02 engineering and technologyComputer Science::Computational Geometry01 natural sciencesConvexityTheoretical Computer ScienceCombinatoricsCAT algorithmIntegerExhaustive generation0202 electrical engineering electronic engineering information engineeringConvex polyominoeConvexity K-convex polyominoes.Convex polyominoesComputer Science::DatabasesMathematicsDiscrete mathematicsAmortized analysisMathematics::CombinatoricsDegree (graph theory)Settore INF/01 - InformaticaComputer Science (all)Regular polygonMonotone polygon010201 computation theory & mathematicsPath (graph theory)020201 artificial intelligence & image processingCAT algorithms; Convex polyominoes; Exhaustive generation;CAT algorithms
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Vector-valued Hardy inequalities and B-convexity

2000

Inequalities of the form $$\sum\nolimits_{k = 0}^\infty {|\hat f(m_k )|/(k + 1) \leqslant C||f||_1 } $$ for allf∈H 1, where {m k } are special subsequences of natural numbers, are investigated in the vector-valued setting. It is proved that Hardy's inequality and the generalized Hardy inequality are equivalent for vector valued Hardy spaces defined in terms ff atoms and that they actually characterizeB-convexity. It is also shown that for 1<q<∞ and 0<α<∞ the spaceX=H(1,q,γa) consisting of analytic functions on the unit disc such that $$\int_0^1 {(1 - r)^{q\alpha - 1} M_1^q (f,r) dr< \infty } $$ satisfies the previous inequality for vector valued functions inH 1 (X), defined as the space ofX…

General MathematicsMathematical analysisNatural numberHardy spaceSpace (mathematics)ConvexityCombinatoricssymbols.namesakesymbolsLocally integrable functionUnit (ring theory)Vector-valued functionMathematicsAnalytic function
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A general framework for a class of non-linear approximations with applications to image restoration

2018

Este artículo se encuentra disponible en la página web de la revista en la siguiente URL: https://www.sciencedirect.com/science/article/abs/pii/S0377042717301188 Este es el pre-print del siguiente artículo: Candela, V., Falcó, A. & Romero, PD. (2018). A general framework for a class of non-linear approximations with applications to image restoration. Journal of Computational and Applied Mathematics, vol. 330 (mar.), pp. 982-994, que se ha publicado de forma definitiva en https://doi.org/10.1016/j.cam.2017.03.008 This is the pre-peer reviewed version of the following article: Candela, V., Falcó, A. & Romero, PD. (2018). A general framework for a class of non-linear approximations with applic…

Mathematical optimization010103 numerical & computational mathematics01 natural sciencesProjection (linear algebra)ConvexityImage (mathematics)symbols.namesakeProgramming (Mathematics) in Works of art.Convergence (routing)Applied mathematics0101 mathematicsProgramación (Matemáticas) - Aplicaciones en Obras de arte.Art - Conservation and restoration.Image restorationMathematicsApplied MathematicsHilbert space.Hilbert spaceAlgoritmos computacionales.Hilbert Espacio de.Linear subspaceComputer algorithms.010101 applied mathematicsComputational MathematicsObras de arte - Restauración.symbolsDeconvolutionObras de arte - Conservación.Journal of Computational and Applied Mathematics
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Tangent and Normal Cones in Nonconvex Multiobjective Optimization

2000

Trade-off information is important in multiobjective optimization. It describes the relationships of changes in objective function values. For example, in interactive methods we need information about the local behavior of solutions when looking for improved search directions.

Mathematical optimizationNon-convexityTangentMulti-objective optimizationMathematics
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Error bounds for a convexity-preserving interpolation and its limit function

2008

AbstractError bounds between a nonlinear interpolation and the limit function of its associated subdivision scheme are estimated. The bounds can be evaluated without recursive subdivision. We show that this interpolation is convexity preserving, as its associated subdivision scheme. Finally, some numerical experiments are presented.

Mathematical optimizationNonlinear subdivision schemesbusiness.industryApplied MathematicsNumerical analysisMathematicsofComputing_NUMERICALANALYSISStairstep interpolationComputer Science::Computational GeometryConvexityMultivariate interpolationComputational MathematicsError boundsComputer Science::GraphicsNearest-neighbor interpolationTheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITYComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATIONApplied mathematicsComputer Science::Symbolic ComputationConvexity preservingbusinessSpline interpolationSubdivisionInterpolationMathematicsComputingMethodologies_COMPUTERGRAPHICSJournal of Computational and Applied Mathematics
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ε-Regularized two-level optimization problems: Approximation and existence results

2006

The purpose of this work is to improve some results given in [12], relating to approximate solutions for two-level optimization problems. By considering an e-regularized problem, we get new properties, under convexity assumptions in the lower level problems. In particular, we prove existence results for the solutions to the e-regularized problem, whereas the initial two-level optimization problem may fail to have a solution. Finally, as an example, we consider an approximation method with interior penalty functions.

Mathematical optimizationVector optimizationWork (thermodynamics)Optimization problemL-reductionApproximation algorithmHardness of approximationConvexityPolynomial-time approximation schemeMathematics
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Counting common perpendicular arcs in negative curvature

2013

Let $D^-$ and $D^+$ be properly immersed closed locally convex subsets of a Riemannian manifold with pinched negative sectional curvature. Using mixing properties of the geodesic flow, we give an asymptotic formula as $t\to+\infty$ for the number of common perpendiculars of length at most $t$ from $D^-$ to $D^+$, counted with multiplicities, and we prove the equidistribution in the outer and inner unit normal bundles of $D^-$ and $D^+$ of the tangent vectors at the endpoints of the common perpendiculars. When the manifold is compact with exponential decay of correlations or arithmetic with finite volume, we give an error term for the asymptotic. As an application, we give an asymptotic form…

Mathematics - Differential GeometryGeneral Mathematics[MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS]37D40 37A25 53C22 30F4001 natural sciencesDomain (mathematical analysis)Bowen-Margulis measurecommon perpendicularequidistributiondecay of correlation0502 economics and businessortholength spectrummixingAsymptotic formulaSectional curvatureTangent vectorMathematics - Dynamical Systems0101 mathematicsExponential decayskinning measurelaskeminenMathematicsconvexityApplied Mathematicsta111010102 general mathematics05 social sciencesMathematical analysisRegular polygonnegative curvatureRiemannian manifoldGibbs measureManifoldKleinian groups[MATH.MATH-DG]Mathematics [math]/Differential Geometry [math.DG]countingMathematics::Differential Geometrygeodesic arc050203 business & management
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Non-preserved curvature conditions under constrained mean curvature flows

2014

We provide explicit examples which show that mean convexity (i.e. positivity of the mean curvature) and positivity of the scalar curvature are non-preserved curvature conditions for hypersurfaces of the Euclidean space evolving under either the volume- or the area preserving mean curvature flow. The relevance of our examples is that they disprove some statements of the previous literature, overshadow a widespread folklore conjecture about the behaviour of these flows and bring out the discouraging news that a traditional singularity analysis is not possible for constrained versions of the mean curvature flow.

Mathematics - Differential GeometryMean curvature flowMean curvatureConjectureEuclidean spaceSingularity analysis010102 general mathematicsMathematical analysisCurvature53C4401 natural sciencesConvexity010101 applied mathematicsMathematics - Analysis of PDEsDifferential Geometry (math.DG)Computational Theory and MathematicsFOS: MathematicsMathematics::Differential GeometryGeometry and Topology0101 mathematicsAnalysisAnalysis of PDEs (math.AP)Scalar curvatureMathematicsDifferential Geometry and its Applications
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Interpolated measures with bounded density in metric spaces satisfying the curvature-dimension conditions of Sturm

2011

We construct geodesics in the Wasserstein space of probability measure along which all the measures have an upper bound on their density that is determined by the densities of the endpoints of the geodesic. Using these geodesics we show that a local Poincar\'e inequality and the measure contraction property follow from the Ricci curvature bounds defined by Sturm. We also show for a large class of convex functionals that a local Poincar\'e inequality is implied by the weak displacement convexity of the functional.

Mathematics - Differential GeometryPure mathematicsGeodesicPoincaré inequalityMetric measure spaceCurvature01 natural sciencesConvexitysymbols.namesakeMathematics - Analysis of PDEsMathematics - Metric GeometryFOS: MathematicsMathematics::Metric Geometry0101 mathematicsRicci curvatureMathematicsProbability measure010102 general mathematicsta111Measure contraction propertyMetric Geometry (math.MG)53C23 (Primary) 28A33 49Q20 (Secondary)Functional Analysis (math.FA)010101 applied mathematicsMathematics - Functional AnalysisMetric spaceRicci curvatureDifferential Geometry (math.DG)Poincaré inequalityBounded functionsymbolsMathematics::Differential GeometryAnalysisAnalysis of PDEs (math.AP)
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Noncoincidence of Approximate and Limiting Subdifferentials of Integral Functionals

2011

For a locally Lipschitz integral functional $I_f$ on $L^1(T,\mathbf{R}^n)$ associated with a measurable integrand f, the limiting subdifferential and the approximate subdifferential never coincide at a point $x_0$ where $f(t,\cdot)$ is not subdifferentially regular at $x_0(t)$ for a.e. $t\in T$. The coincidence of both subdifferentials occurs on a dense set of $L^1(T,\mathbf{R}^n)$ if and only if $f(t,\cdot)$ is convex for a.e. $t\in T$. Our results allow us to characterize Aubin's Lipschitz-like property as well as the convexity of multivalued mappings between $L^1$-spaces. New necessary optimality conditions for some Bolza problems are also obtained.

Mathematics::Functional AnalysisPure mathematicsControl and OptimizationDense setApplied MathematicsMathematical analysisMathematics::Analysis of PDEsMathematics::Optimization and ControlRegular polygonLimitingSubderivativeLipschitz continuityConvexityCoincidenceMathematicsSIAM Journal on Control and Optimization
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