Search results for "averaging"

showing 10 items of 47 documents

Multi-speckle autocorrelation spectroscopy — a new strategy to monitor ultraslow dynamics in dense and nonergodic media

2007

We present a modification of the conventional dynamic light scattering set-up which allows to monitor the intensity fluctuations of many independent spatial Fourier components of the density fluctuations, i.e. “speckles”, simultaneously by using a charge-coupled device (CCD) camera as area detector. By averaging over the intensity autocorrelation function the final 10–20% decay of the intermediate scattering function in very dense colloidal dispersions is obtained with much higher accuracy. At the same time this multi-speckle autocorrelation spectroscopy provides an alternative route for constructing ensemble-averaged intermediate scattering functions in nonergodic media by replacing the av…

Speckle patternsymbols.namesakeFourier transformDynamic light scatteringChemistryOptical autocorrelationScatteringEnsemble averagingAutocorrelationsymbolsAnalytical chemistryStatistical physicsSpectroscopy
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A fast and recursive algorithm for clustering large datasets with k-medians

2012

Clustering with fast algorithms large samples of high dimensional data is an important challenge in computational statistics. Borrowing ideas from MacQueen (1967) who introduced a sequential version of the $k$-means algorithm, a new class of recursive stochastic gradient algorithms designed for the $k$-medians loss criterion is proposed. By their recursive nature, these algorithms are very fast and are well adapted to deal with large samples of data that are allowed to arrive sequentially. It is proved that the stochastic gradient algorithm converges almost surely to the set of stationary points of the underlying loss criterion. A particular attention is paid to the averaged versions, which…

Statistics and ProbabilityClustering high-dimensional dataFOS: Computer and information sciencesMathematical optimizationhigh dimensional dataMachine Learning (stat.ML)02 engineering and technologyStochastic approximation01 natural sciencesStatistics - Computation010104 statistics & probabilityk-medoidsStatistics - Machine Learning[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]stochastic approximation0202 electrical engineering electronic engineering information engineeringComputational statisticsrecursive estimatorsAlmost surely[ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST]0101 mathematicsCluster analysisComputation (stat.CO)Mathematicsaveragingk-medoidsRobbins MonroApplied MathematicsEstimator[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]stochastic gradient[ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH]MedoidComputational MathematicsComputational Theory and Mathematicsonline clustering020201 artificial intelligence & image processingpartitioning around medoidsAlgorithm
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Recursive estimation of the conditional geometric median in Hilbert spaces

2012

International audience; A recursive estimator of the conditional geometric median in Hilbert spaces is studied. It is based on a stochastic gradient algorithm whose aim is to minimize a weighted L1 criterion and is consequently well adapted for robust online estimation. The weights are controlled by a kernel function and an associated bandwidth. Almost sure convergence and L2 rates of convergence are proved under general conditions on the conditional distribution as well as the sequence of descent steps of the algorithm and the sequence of bandwidths. Asymptotic normality is also proved for the averaged version of the algorithm with an optimal rate of convergence. A simulation study confirm…

Statistics and ProbabilityMallows-Wasserstein distanceRobbins-Monroasymptotic normalityCLTcentral limit theoremAsymptotic distributionMathematics - Statistics TheoryStatistics Theory (math.ST)01 natural sciencesMallows–Wasserstein distanceonline data010104 statistics & probability[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]60F05FOS: MathematicsApplied mathematics[ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST]0101 mathematics62L20MathematicsaveragingSequential estimation010102 general mathematicsEstimatorRobbins–MonroConditional probability distribution[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]Geometric medianstochastic gradient[ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH]robust estimatorRate of convergenceConvergence of random variablesStochastic gradient.kernel regressionsequential estimationKernel regressionStatistics Probability and Uncertainty
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Stochastic algorithms for robust statistics in high dimension

2016

This thesis focus on stochastic algorithms in high dimension as well as their application in robust statistics. In what follows, the expression high dimension may be used when the the size of the studied sample is large or when the variables we consider take values in high dimensional spaces (not necessarily finite). In order to analyze these kind of data, it can be interesting to consider algorithms which are fast, which do not need to store all the data, and which allow to update easily the estimates. In large sample of high dimensional data, outliers detection is often complicated. Nevertheless, these outliers, even if they are not many, can strongly disturb simple indicators like the me…

Stochastic AlgorithmsAlgorithmes StochastiquesAlgorithmes RécursifsRecursive AlgorithmsStatistique RobusteAlgorithmes de Gradient StochastiquesAveragingStochastic Gradient AlgorithmsMoyennisationGrande DimensionRobust StatisticsFunctional DataDonnées Fonctionnelles[MATH.MATH-ST] Mathematics [math]/Statistics [math.ST]Geometric MedianHigh DimensionMédiane Géométrique
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Assessment of Modelling Structure and Data Availability Influence on Urban Flood Damage Modelling Uncertainty

2014

Abstract In modelling application, different model structures may be equally reliable in terms of calibration ability but they may produce different uncertainty levels; moreover, available data during model calibration may influence the uncertainty linked to the predictions of the same modelling structure. In the present paper, Bayesian model-averaging was applied to several flood damage estimation models in order to identify the best model combination for urban flooding distribution analysis in Palermo city center (Italy). During the analysis, was taken into account the effect of the available data growth on the model uncertainty with respect to the different combination of models outputs.

Structure (mathematical logic)Flood mythCalibration (statistics)flooding damage evaluationBayesian probabilityFlooding (psychology)General MedicineData availabilityBayesian Model-AveragingEconometricsEnvironmental scienceSensitivity analysisuncertainty analysis.Engineering(all)Uncertainty analysisProcedia Engineering
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Averaging and optimal control of elliptic Keplerian orbits with low propulsion

2006

This article deals with the optimal transfer of a satellite between Keplerian orbits using low propulsion. It is based on preliminary results of Geffroy [Generalisation des techniques de moyennation en controle optimal, application aux problemes de rendez-vous orbitaux a poussee faible, Ph.D. Thesis, Institut National Polytechnique de Toulouse, France, Octobre 1997] where the optimal trajectories are approximated using averaging techniques. The objective is to introduce the appropriate geometric framework and to complete the analysis of the averaged optimal trajectories for energy minimization, showing in particular the connection with Riemannian problems having integrable geodesics.

[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC]0209 industrial biotechnologyElliptic orbitGeneral Computer ScienceGeodesicIntegrable systemGeometry02 engineering and technology01 natural sciencesoptimal control020901 industrial engineering & automationTransfer orbitApplied mathematics0101 mathematicsElectrical and Electronic EngineeringComputingMilieux_MISCELLANEOUSMathematicsaveragingOrbital transferMechanical Engineering010102 general mathematics[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC]Optimal controlConnection (mathematics)Control and Systems Engineering[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]Orbital maneuverMinimum energy control
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Energy minimization of single input orbit transfer by averaging and continuation

2006

AbstractThis article deals with the transfer between Keplerian coplanar orbits using low propulsion. We focus on the energy minimization problem and compute the averaged system, proving integrability and relating the corresponding trajectories to a three-dimensional Riemannian problem that is analyzed in details. The geodesics provide approximations of the extremals of the energy minimization problem and can be used in order to evaluate the optimal trajectories of the time optimal and the minimization of the consumption problems with continuation methods. In particular, minimizing trajectories for transfer towards the geostationary orbit can be approximated in suitable coordinates by straig…

[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC]0209 industrial biotechnologyMathematics(all)GeodesicGeneral MathematicsMoyennation02 engineering and technologyPropulsionEnergy minimization01 natural sciencesContinuationAveraging020901 industrial engineering & automation0101 mathematicsMinimisation de l'énergieComputingMilieux_MISCELLANEOUSMathematicsTransfert orbital à poussée faibleMéthodes de continuation010102 general mathematicsMathematical analysis[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC]Orbital transfer with low thrustEnergy minimizationContinuation methodsOrbit (dynamics)Geostationary orbit[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]MinificationFocus (optics)
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Time Versus Energy in the Averaged Optimal Coplanar Kepler Transfer towards Circular Orbits

2015

International audience; The aim of this note is to compare the averaged optimal coplanar transfer towards circular orbits when the costs are the transfer time transfer and the energy consumption. While the energy case leads to analyze a 2D Riemannian metric using the standard tools of Riemannian geometry (curvature computations, geodesic convexity), the time minimal case is associated to a Finsler metric which is not smooth. Nevertheless a qualitative analysis of the geodesic flow is given in this article to describe the optimal transfers. In particular we prove geodesic convexity of the elliptic domain.

[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC]ComputationGeodesic convexity02 engineering and technologyRiemannian geometryCurvature01 natural sciencesDomain (mathematical analysis)Low thrust orbit transfersymbols.namesakeAveraging0203 mechanical engineeringFOS: MathematicsTime transferGeodesic convexityCircular orbit0101 mathematicsMathematics - Optimization and ControlMathematics020301 aerospace & aeronauticsApplied Mathematics010102 general mathematicsMathematical analysisOptimal controlOptimization and Control (math.OC)Metric (mathematics)symbolsRiemann-Finsler Geometry[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]Mathematics::Differential Geometry
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An extended Benthic Quality Index for assessment of lake profundal macroinvertebrates: addition of indicator taxa by multivariate ordination and weig…

2014

The chironomid Benthic Quality Index (BQI) is a widely used metric in assessments of lake status. The BQI is based on 7 indicator taxa, which like most profundal fauna, often occur sporadically in low densities. Hence, a major weakness of the index is that it cannot be calculated when indicator taxa are not captured. Thus, an extension of the BQI that incorporates more macroinvertebrate taxa is desirable. We used 2 statistical approaches (Detrended Correspondence Analysis and Weighted Averaging) to estimate new benthic quality indicator scores for profundal macroinvertebrate taxa and to construct modified BQIs called Profundal Invertebrate Community Metrics (PICMs). We calibrated the PICMs …

bioassessmentO/E ratiobenthic invertebratesweighted averagingindikaattorilajitjärvet
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Using Induced Ordered Weighted Averaging (IOWA) Operators for Aggregation in Cross-Efficiency Evaluations

2014

This paper proposes an enhancement of the cross-efficiency evaluation through the aggregation of cross-efficiencies by using a particular type of induced ordered weighted averaging IOWA operator. The use of a weighted average of cross-efficiencies for the calculation of the cross-efficiency scores, instead of the usual arithmetic mean, allows us to introduce some flexibility into the analysis. In particular, the main purpose of the approach we present is to provide aggregation weights that reflect the decision maker DM preferences regarding the relative importance that should be attached to the cross-efficiencies provided by the different decision-making units. To do it, an ordering is to b…

business.industryType (model theory)Theoretical Computer ScienceHuman-Computer InteractionVariable (computer science)Matrix (mathematics)Operator (computer programming)Artificial IntelligenceArtificial intelligencebusinessOrdered weighted averaging aggregation operatorWeighted arithmetic meanAlgorithmRowSoftwareMathematicsArithmetic meanInternational Journal of Intelligent Systems
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