Search results for "Kullback-Leibler divergence"

showing 6 items of 6 documents

Genetic Algorithm Optimized Grid-based RF Fingerprint Positioning in Heterogeneous Small Cell Networks

2015

In this paper we propose a novel optimization algorithm for grid-based RF fingerprinting to improve user equipment (UE) positioning accuracy. For this purpose we have used Multi-objective Genetic Algorithm (MOGA) which enables autonomous calibration of gridcell layout (GCL) for better UE positioning as compared to that of the conventional fingerprinting approach. Performance evaluations were carried out using two different training data-sets consisting of Minimization of Drive Testing measurements obtained from a dynamic system simulation in a heterogeneous LTE small cell environment. The robustness of the proposed method has been tested analyzing positioning results from two different area…

EngineeringKullback-Leibler divergencebusiness.industryReal-time computingFingerprint recognitionGridmulti-objective genetic algorithmminimization of drive testsUser equipmentRobustness (computer science)Genetic algorithmElectronic engineeringgrid-based RF fingerprintingMinificationSmall cellRadio frequencybusiness
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Reduced reference 3D mesh quality assessment based on statistical models

2015

International audience; During their geometry processing and transmission 3D meshes are subject to various visual processing operations like compression, watermarking, remeshing, noise addition and so forth. In this context it is indispensable to evaluate the quality of the distorted mesh, we talk here about the mesh visual quality (MVQ) assessment. Several works have tried to evaluate the MVQ using simple geometric measures, However this metrics do not correlate well with the subjective score since they fail to reflect the perceived quality. In this paper we propose a new objective metric to evaluate the visual quality between a mesh with a perfect quality called reference mesh and its dis…

Gamma distribution[ INFO ] Computer Science [cs]Kullback–Leibler divergenceKullback-Leibler divergencestatistical modelingContext (language use)02 engineering and technologyhuman visual systemDatabases[SPI]Engineering Sciences [physics][ SPI ] Engineering Sciences [physics]0202 electrical engineering electronic engineering information engineeringcomputational geometryPolygon mesh[INFO]Computer Science [cs]Divergence (statistics)MathematicsComputingMethodologies_COMPUTERGRAPHICSVisualizationbusiness.industry020207 software engineeringStatistical modelPattern recognitionstatistical distributionsDistortionGeometry processing3D triangle mesh[ SPI.TRON ] Engineering Sciences [physics]/Electronicsimage processing[SPI.TRON]Engineering Sciences [physics]/ElectronicsHuman visual system modelMetric (mathematics)Solid modelingThree-dimensional displays020201 artificial intelligence & image processingDistortion measurementWeibull distributionArtificial intelligencebusinessobjective metricQuality assessment
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Variance estimation and asymptotic confidence bands for the mean estimator of sampled functional data with high entropy unequal probability sampling …

2013

For fixed size sampling designs with high entropy it is well known that the variance of the Horvitz-Thompson estimator can be approximated by the H\'ajek formula. The interest of this asymptotic variance approximation is that it only involves the first order inclusion probabilities of the statistical units. We extend this variance formula when the variable under study is functional and we prove, under general conditions on the regularity of the individual trajectories and the sampling design, that we can get a uniformly convergent estimator of the variance function of the Horvitz-Thompson estimator of the mean function. Rates of convergence to the true variance function are given for the re…

Kullback-Leibler divergence[STAT.TH] Statistics [stat]/Statistics Theory [stat.TH]FOS: Mathematicscovariance functionrejective samplingMathematics - Statistics TheoryStatistics Theory (math.ST)finite populationHorvitz-Thompson estimator[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]Hájek approximationunequal probability sampling without replacement[ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH]
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Selecting the tuning parameter in penalized Gaussian graphical models

2019

Penalized inference of Gaussian graphical models is a way to assess the conditional independence structure in multivariate problems. In this setting, the conditional independence structure, corresponding to a graph, is related to the choice of the tuning parameter, which determines the model complexity or degrees of freedom. There has been little research on the degrees of freedom for penalized Gaussian graphical models. In this paper, we propose an estimator of the degrees of freedom in $$\ell _1$$ -penalized Gaussian graphical models. Specifically, we derive an estimator inspired by the generalized information criterion and propose to use this estimator as the bias term for two informatio…

Statistics and ProbabilityStatistics::TheoryKullback–Leibler divergenceKullback-Leibler divergenceComputer scienceGaussianInformation Criteria010103 numerical & computational mathematicsModel complexityModel selection01 natural sciencesTheoretical Computer Science010104 statistics & probabilitysymbols.namesakeStatistics::Machine LearningGeneralized information criterionEntropy (information theory)Statistics::MethodologyGraphical model0101 mathematicsPenalized Likelihood Kullback-Leibler Divergence Model Complexity Model Selection Generalized Information Criterion.Model selectionEstimatorStatistics::ComputationComputational Theory and MathematicsConditional independencesymbolsPenalized likelihoodStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaAlgorithmStatistics and Computing
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An efficient grid-based RF fingerprint positioning algorithm for user location estimation in heterogeneous small cell networks

2014

This paper proposes a novel technique to enhance the performance of grid-based Radio Frequency (RF) fingerprint position estimation framework. First enhancement is an introduction of two overlapping grids of training signatures. As the second enhancement, the location of the testing signature is estimated to be a weighted geometric center of a set of nearest grid units whereas in a traditional grid-based RF fingerprinting only the center point of the nearest grid unit is used for determining the user location. By using the weighting-based location estimation, the accuracy of the location estimation can be improved. The performance evaluation of the enhanced RF fingerprinting algorithm was c…

grid-based RF fingerprintKullback-Leibler divergencePosition (vector)Computer scienceFingerprint (computing)Point (geometry)Small cellRadio frequencyGridAlgorithmWeightingInterpolationminimization of drive tests
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Radio frequency fingerprinting for outdoor user equipment localization

2017

The recent advancements in cellular mobile technology and smart phone usage have opened opportunities for researchers and commercial companies to develop ubiquitous low cost localization systems. Radio frequency (RF) fingerprinting is a popular positioning technique which uses radio signal strength (RSS) values from already existing infrastructures to provide satisfactory user positioning accuracy in indoor and densely built outdoor urban areas where Global Navigation Satellite System (GNSS) signal is poor and hard to reach. However a major requirement for the RF fingerprinting to maintain good localization accuracy is the collection and updating of large training database. The Minimization…

langattomat lähiverkotKullback-Leibler divergenceK-Nearest NeighborpaikannusK-means clusteringRF fingerprintingmatkaviestinverkotradioaallotLTEWLANkoneoppiminenmobiililaitteetFuzzy C-means ClusteringklusterianalyysiMahalanobis distancehierarchical clustering
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