Search results for "vector space"

showing 10 items of 287 documents

Text localization from photos

2009

In this paper a new text extraction algorithm is proposed. In real scenes the text is usually overlapped or is part of the background. To identify the text regions, in complex conditions, a method exploiting a “multi-resolution feature based method” for extracting text with undefined dimension has been developed. Once identified, the multi-resolution information are merged and skimmed through a set of Support Vector Machines (SVM). The tests and the comparisons with other techniques, performed on heterogeneous images, have shown the effectiveness of the proposed.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionibusiness.industryComputer scienceFeature extractionPattern recognitionSupport vector machineSet (abstract data type)Text Localization Image UnderstandingDimension (vector space)Pattern recognition (psychology)Computer visionArtificial intelligencebusinessImage resolution2009 Digest of Technical Papers International Conference on Consumer Electronics
researchProduct

MR2684111 Kadelburg, Zoran; Radenović, Stojan; Rakočević, Vladimir Topological vector space-valued cone metric spaces and fixed point theorems. Fixed…

2011

Recently, Huang and Zhang [\emph{Cone metric spaces and fixed point theorems of contractive mappings}, J. Math. Anal. Appl., \textbf{332} (2007), 1468 -1476] defined cone metric spaces by substituing an order normed space for the real numbers and proved some fixed point theorems. Let $E$ be a real Hausdorff topological vector space and $P$ a cone in $E$ with int\,$P\neq \emptyset$, where int\,$P$ denotes the interior of $P$. Let $X$ be a nonempty set. A function $d : X \times X\to E$ is called a \emph{tvs}-cone metric and $(X, d)$ is called a \emph{tvs}-cone metric space, if the following conditions hold: (1) $\theta \leq d(x, y)$ for all $x, y \in X$ and $d(x, y)= \theta$ if and only if $x…

Settore MAT/05 - Analisi MatematicaCone metric spaces Topological vector space-valued cone metric spaces fixed points
researchProduct

Generalized dimension estimates for images of porous sets under monotone Sobolev mappings

2014

We give an essentially sharp estimate in terms of generalized Hausdorff measures for images of porous sets under monotone Sobolev mappings, satisfying suitable Orlicz-Sobolev conditions.

Sobolev spaceMathematics::Functional AnalysisMonotone polygonDimension (vector space)Applied MathematicsGeneral MathematicsMathematical analysisMathematics::Analysis of PDEsSobolev inequalityMathematicsProceedings of the American Mathematical Society
researchProduct

Analysis of multi degree of freedom systems with fractional derivative elements of rational order

2014

In this paper a novel method based on complex eigenanalysis in the state variables domain is proposed to uncouple the set of rational order fractional differential equations governing the dynamics of multi-degree-of-freedom system. The traditional complex eigenanalysis is appropriately modified to be applicable to the coupled fractional differential equations. This is done by expanding the dimension of the problem and solving the system in the state variable domain. Examples of applications are given pertaining to multi-degree-of-freedom systems under both deterministic and stochastic loads.

State variableMathematical optimizationDifferential equationcomplex eigenvalue analysiRational functionfrequency domain analysisDomain (mathematical analysis)Fractional calculusfractional state variablesymbols.namesakeFourier transformDimension (vector space)Multi-degree-of-freedom systems; complex eigenvalue analysis; fractional state variables; frequency domain analysisFrequency domainsymbolsMulti-degree-of-freedom systemSettore ICAR/08 - Scienza Delle CostruzioniMathematics
researchProduct

Ornstein-Zernike equation and Percus-Yevick theory for molecular crystals

2004

We derive the Ornstein-Zernike equation for molecular crystals of axially symmetric particles and apply the Percus-Yevick approximation to this system. The one-particle orientational distribution function has a nontrivial dependence on the orientation and is needed as an input. Despite some differences, the Ornstein-Zernike equation for molecular crystals has a similar structure as for liquids. We solve both equations for hard ellipsoids on a sc lattice. Compared to molecular liquids, the tensorial orientational correlators exhibit less structure. However, depending on the lengths a and b of the rotation axis and the perpendicular axes of the ellipsoids, different behavior is found. For obl…

Statistical Mechanics (cond-mat.stat-mech)Plane (geometry)Center (category theory)FOS: Physical sciencesOrnstein–Zernike equationCondensed Matter - Soft Condensed MatterSpace (mathematics)Brillouin zoneOrientation (vector space)symbols.namesakeReciprocal latticeQuantum mechanicssymbolsSoft Condensed Matter (cond-mat.soft)MaximaCondensed Matter - Statistical MechanicsMathematics
researchProduct

On the geometry of the characteristic class of a star product on a symplectic manifold

2001

The characteristic class of a star product on a symplectic manifold appears as the class of a deformation of a given symplectic connection, as described by Fedosov. In contrast, one usually thinks of the characteristic class of a star product as the class of a deformation of the Poisson structure (as in Kontsevich's work). In this paper, we present, in the symplectic framework, a natural procedure for constructing a star product by directly quantizing a deformation of the symplectic structure. Basically, in Fedosov's recursive formula for the star product with zero characteristic class, we replace the symplectic structure by one of its formal deformations in the parameter $\hbar$. We then s…

Statistical and Nonlinear PhysicsGeometrySymplectic representationSymplectic matrixSymplectic vector spaceMathematics - Quantum AlgebraFOS: MathematicsQuantum Algebra (math.QA)SymplectomorphismMoment mapMathematics::Symplectic GeometryMathematical PhysicsSymplectic geometryQuantum cohomologySymplectic manifoldMathematics
researchProduct

The asymptotic covariance matrix of the Oja median

2003

The Oja median, based on a sample of multivariate data, is an affine equivariant estimate of the centre of the distribution. It reduces to the sample median in one dimension and has several nice robustness and efficiency properties. We develop different representations of its asymptotic variance and discuss ways to estimate this quantity. We consider symmetric multivariate models and also the more narrow elliptical models. A small simulation study is included to compare finite sample results to the asymptotic formulas.

Statistics and ProbabilityCombinatoricsDelta methodMultivariate statisticsMatrix (mathematics)Multivariate analysis of varianceDimension (vector space)Matrix t-distributionApplied mathematicsEquivariant mapAffine transformationStatistics Probability and UncertaintyMathematicsStatistics & Probability Letters
researchProduct

Fast Estimation of the Median Covariation Matrix with Application to Online Robust Principal Components Analysis

2017

International audience; The geometric median covariation matrix is a robust multivariate indicator of dispersion which can be extended without any difficulty to functional data. We define estimators, based on recursive algorithms, that can be simply updated at each new observation and are able to deal rapidly with large samples of high dimensional data without being obliged to store all the data in memory. Asymptotic convergence properties of the recursive algorithms are studied under weak conditions. The computation of the principal components can also be performed online and this approach can be useful for online outlier detection. A simulation study clearly shows that this robust indicat…

Statistics and ProbabilityComputer scienceMathematics - Statistics TheoryStatistics Theory (math.ST)01 natural sciences010104 statistics & probabilityMatrix (mathematics)Dimension (vector space)Geometric medianStochastic gradientFOS: Mathematics0101 mathematicsL1-median010102 general mathematicsEstimator[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]Geometric medianCovariance[ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH]Functional dataMSC: 62G05 62L20Principal component analysisProjection pursuitAnomaly detectionRecursive robust estimationStatistics Probability and UncertaintyAlgorithm
researchProduct

Intensity estimation for inhomogeneous Gibbs point process with covariates-dependent chemical activity

2014

Recent development of intensity estimation for inhomogeneous spatial point processes with covariates suggests that kerneling in the covariate space is a competitive intensity estimation method for inhomogeneous Poisson processes. It is not known whether this advantageous performance is still valid when the points interact. In the simplest common case, this happens, for example, when the objects presented as points have a spatial dimension. In this paper, kerneling in the covariate space is extended to Gibbs processes with covariates-dependent chemical activity and inhibitive interactions, and the performance of the approach is studied through extensive simulation experiments. It is demonstr…

Statistics and ProbabilityDimensionality reductionNonparametric statisticsPoisson distributionPoint processsymbols.namesakeDimension (vector space)CovariatesymbolsEconometricsStatistics::MethodologyStatistical physicsStatistics Probability and UncertaintySmoothingMathematicsParametric statisticsStatistica Neerlandica
researchProduct

Sharp dimension free quantitative estimates for the Gaussian isoperimetric inequality

2017

We provide a full quantitative version of the Gaussian isoperimetric inequality: the difference between the Gaussian perimeter of a given set and a half-space with the same mass controls the gap between the norms of the corresponding barycenters. In particular, it controls the Gaussian measure of the symmetric difference between the set and the half-space oriented so to have the barycenter in the same direction of the set. Our estimate is independent of the dimension, sharp on the decay rate with respect to the gap and with optimal dependence on the mass.

Statistics and ProbabilityGaussianGaussian isoperimetric inequality01 natural sciencesPerimeterSet (abstract data type)symbols.namesakeMathematics - Analysis of PDEsDimension (vector space)quantitative isoperimetric inequalityFOS: MathematicsMathematics::Metric Geometry0101 mathematicsSymmetric differenceGaussian isoperimetric inequalityQuantitative estimatesMathematics010102 general mathematicsMathematical analysisProbability (math.PR)49Q20Gaussian measure010101 applied mathematicssymbolsHigh Energy Physics::Experiment60E15Statistics Probability and UncertaintyMathematics - ProbabilityAnalysis of PDEs (math.AP)
researchProduct