Search results for "DECOMPOSITION"

showing 10 items of 766 documents

Two-Dimensional Orthogonal Wavelets and Wavelet Packets

2018

This chapter extends the design of spline-based orthogonal discrete-time wavelets and wavelet packets to two-dimensional case. The corresponding transforms are implemented by using the 2D FFT.

Spline (mathematics)WaveletComputer sciencePhase spectrumFast Fourier transformMathematicsofComputing_NUMERICALANALYSISAlgorithmWavelet packet decomposition
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Discrete-Time Periodic Wavelet Packets

2014

Direct and inverse wavelet and wavelet packet transforms of a spline are implemented by filtering the spline’s coordinates by two-channel critically sampled p-filter banks. In this chapter, those p-filter banks are utilized for processing discrete-time signals. The p-filter banks generate discrete-time wavelets and wavelet packets in the spaces of 1D and 2D periodic signals.

Spline (mathematics)WaveletDiscrete time and continuous timeComputer scienceNetwork packetMathematicsofComputing_NUMERICALANALYSISInverseData_CODINGANDINFORMATIONTHEORYAlgorithmWavelet packet decomposition
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Interference excision algorithm for frequency hopping spread spectrum based on undecimated wavelet packet transform

2002

An algorithm for reducing narrowband interference effects in frequency hopping spread spectrum is presented. The method is based on the undecimated wavelet packet transform. It improves the performance obtained by other methods. Experimental results demonstrate the suitability of the algorithm.

Spread spectrumInterference excisionComputer scienceComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSComputer Science::Networking and Internet ArchitectureElectronic engineeringFrequency-hopping spread spectrumElectrical and Electronic EngineeringAlgorithmWavelet packet decompositionElectronics Letters
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Block Based Deconvolution Algorithm Using Spline Wavelet Packets

2010

This paper presents robust algorithms to deconvolve discrete noised signals and images. The idea behind the algorithms is to solve the convolution equation separately in different frequency bands. This is achieved by using spline wavelet packets. The solutions are derived as linear combinations of the wavelet packets that minimize some parameterized quadratic functionals. Parameters choice, which is performed automatically, determines the trade-off between the solution regularity and the initial data approximation. This technique, which id called Spline Harmonic Analysis, provides a unified computational scheme for the design of orthonormal spline wavelet packets, fast implementation of the…

Statistics and ProbabilityApplied MathematicsSpline waveletCondensed Matter PhysicsDeconvolution · Wavelet packet · Spline · RegularityWavelet packet decompositionSpline (mathematics)Quadratic equationModeling and SimulationOrthonormal basisGeometry and TopologyComputer Vision and Pattern RecognitionDeconvolutionThin plate splineLinear combinationAlgorithmMathematics
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On Association Models Defined over Independence Graphs

1998

Conditions on joint distributions are given under which two variables will be conditionally associated whenever an independence graph does not imply a corresponding conditional independence statement. To this end the notions of parametric cancellation, of stable paths and of quasi-linear models are discussed in some detail.

Statistics and ProbabilityCombinatoricsStatement (computer science)Discrete mathematicsConditional independenceJoint probability distributionIndependence (mathematical logic)Matrix decompositionParametric statisticsCholesky decompositionMathematicsCorresponding conditionalBernoulli
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Online Principal Component Analysis in High Dimension: Which Algorithm to Choose?

2017

Summary Principal component analysis (PCA) is a method of choice for dimension reduction. In the current context of data explosion, online techniques that do not require storing all data in memory are indispensable to perform the PCA of streaming data and/or massive data. Despite the wide availability of recursive algorithms that can efficiently update the PCA when new data are observed, the literature offers little guidance on how to select a suitable algorithm for a given application. This paper reviews the main approaches to online PCA, namely, perturbation techniques, incremental methods and stochastic optimisation, and compares the most widely employed techniques in terms statistical a…

Statistics and ProbabilityComputer scienceComputationDimensionality reductionIncremental methods02 engineering and technologyMissing data01 natural sciences010104 statistics & probabilityData explosionStreaming dataPrincipal component analysis0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processing0101 mathematicsStatistics Probability and UncertaintyAlgorithmEigendecomposition of a matrixInternational Statistical Review
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Large deviations results for subexponential tails, with applications to insurance risk

1996

AbstractConsider a random walk or Lévy process {St} and let τ(u) = inf {t⩾0 : St > u}, P(u)(·) = P(· | τ(u) < ∞). Assuming that the upwards jumps are heavy-tailed, say subexponential (e.g. Pareto, Weibull or lognormal), the asymptotic form of the P(u)-distribution of the process {St} up to time τ(u) is described as u → ∞. Essentially, the results confirm the folklore that level crossing occurs as result of one big jump. Particular sharp conclusions are obtained for downwards skip-free processes like the classical compound Poisson insurance risk process where the formulation is in terms of total variation convergence. The ideas of the proof involve excursions and path decompositions for Mark…

Statistics and ProbabilityExponential distributionRegular variationRuin probabilityExcursionRandom walkDownwards skip-free processLévy processConditioned limit theoremTotal variation convergenceCombinatoricsInsurance riskPath decompositionIntegrated tailProbability theoryModelling and SimulationExtreme value theoryMaximum domain of attractionMathematicsStochastic processApplied MathematicsExtreme value theoryRandom walkSubexponential distributionModeling and SimulationLog-normal distributionLarge deviations theory60K1060F10Stochastic Processes and their Applications
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A note on adjusted responses, fitted values and residuals in Generalized Linear Models

2014

Adjusted responses, adjusted fitted values and adjusted residuals are known to play in Generalized Linear Models the role played in Linear Models by observations, fitted values and ordinary residuals. We think this parallelism, which was widely recognized and used in the early literature on Generalized Linear Models, has been somewhat overlooked in more recent presentations. We revise this parallelism, systematizing and proving some results that are either scattered or not satisfactorily spelled out in the literature. In particular, we formally derive the asymptotic dispersion matrix of the (scaled) adjusted residuals, by proving that in Generalized Linear Models the fitted values are asym…

Statistics and ProbabilityGeneralized linear modelCovariance matrixLinear modelLinear predictionWald testUncorrelatedAdjusted ResidualWald test-statisticRao score test-statisticDecomposition (computer science)Parallelism (grammar)Linear ModelApplied mathematicsStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaGeneralized Linear ModelMathematicsStatistical Modelling
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Combined SANS and SAXS experiments in polyolefins-hydrogenated oligocyclopentadiene (HOCP) blends

1998

Abstract Lamellar morphology in semicrystyalline polymer blends (iPP/HOCP and HDPE/HOCP) is investigated by means of Small Angle X-ray Scattering (SAXS) and Small Angle Neutron Scattering (SANS). The investigated blends present a complex phase diagram, as they show a miscibility gap. SAXS scattering curves of blends lying outside the miscibility gap can be analysed in the frame of the psuedo two phase model. In order to describe the complex morphology of blends lying inside the miscibility gap, the SANS technique revealed necessary. In this paper a novel method to describe the morphology of these complex systems by means of SANS is presented.

Statistics and ProbabilityMaterials scienceSmall-angle X-ray scatteringbusiness.industryScatteringSpinodal decompositionThermodynamicsCondensed Matter PhysicsSmall-angle neutron scatteringOpticsLamellar structureHigh-density polyethylenePolymer blendbusinessPhase diagram
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Multiple factor analysis: principal component analysis for multitable and multiblock data sets

2013

Multiple factor analysis MFA, also called multiple factorial analysis is an extension of principal component analysis PCA tailored to handle multiple data tables that measure sets of variables coll...

Statistics and ProbabilityMeasure (data warehouse)business.industryPattern recognitionMultiple dataMultiple correspondence analysisRelationship squareMultiple factor analysisPrincipal component analysisArtificial intelligenceFactorial analysisGeneralized singular value decompositionbusinessMathematicsWiley Interdisciplinary Reviews: Computational Statistics
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