Search results for "algorithm"

showing 10 items of 4887 documents

Highlighting numerical insights of an efficient SPH method

2018

Abstract In this paper we focus on two sources of enhancement in accuracy and computational demanding in approximating a function and its derivatives by means of the Smoothed Particle Hydrodynamics method. The approximating power of the standard method is perceived to be poor and improvements can be gained making use of the Taylor series expansion of the kernel approximation of the function and its derivatives. The modified formulation is appealing providing more accurate results of the function and its derivatives simultaneously without changing the kernel function adopted in the computation. The request for greater accuracy needs kernel function derivatives with order up to the desidered …

Computer scienceApplied MathematicsGaussianComputation010103 numerical & computational mathematicsFunction (mathematics)01 natural sciences010101 applied mathematicsSmoothed-particle hydrodynamicsComputational Mathematicssymbols.namesakeSettore MAT/08 - Analisi NumericaKernel based methods Smoothed Particle Hydrodynamics Accuracy Convergence Improved fast Gaussian transform.Convergence (routing)symbolsTaylor seriesGaussian function0101 mathematicsFocus (optics)Algorithm
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An abstract inf-sup problem inspired by limit analysis in perfect plasticity and related applications

2021

This paper is concerned with an abstract inf-sup problem generated by a bilinear Lagrangian and convex constraints. We study the conditions that guarantee no gap between the inf-sup and related sup-inf problems. The key assumption introduced in the paper generalizes the well-known Babuška–Brezzi condition. It is based on an inf-sup condition defined for convex cones in function spaces. We also apply a regularization method convenient for solving the inf-sup problem and derive a computable majorant of the critical (inf-sup) value, which can be used in a posteriori error analysis of numerical results. Results obtained for the abstract problem are applied to continuum mechanics. In particular…

Computer scienceApplied MathematicsRegular polygonDuality (optimization)Bilinear interpolationPlasticityRegularization (mathematics)Mathematics::Numerical Analysissymbols.namesakeLimit analysisTheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITYModeling and SimulationConvex optimizationsymbolsApplied mathematicsLagrangianMathematical Models and Methods in Applied Sciences
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Performance of Hybrid-ARQ with Incremental Redundancy over Double Rayleigh Fading Channels

2011

In this paper, we study the performance of hybrid automatic repeat request (HARQ) with incremental redundancy (IR) over double Rayleigh channels. Such channels can be used to model the fading amplitude for vehicle-to-vehicle (V2V) communications. We study the performance of HARQ from an information theoretic perspective. Analytical expressions are derived for the $\epsilon$-outage capacity, the average number of transmissions, and the average transmission rate for HARQ with IR, assuming a maximum number of rounds for the HARQ protocol. In our study, the communication rate per HARQ round is adjusted to the average signal-to-noise ratio (SNR) such that a target outage probability is not excee…

Computer scienceAutomatic repeat requestTransmitterHybrid automatic repeat requestSpectral efficiencyRedundancy (information theory)Channel state informationRedundancy (engineering)Electronic engineeringFadingAlgorithmDecoding methodsComputer Science::Information TheoryRayleigh fadingCommunication channel2011 IEEE 73rd Vehicular Technology Conference (VTC Spring)
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Particle identification algorithms for the PANDA Barrel DIRC

2020

The International Conference Instrumentation for Colliding Beam Physics , INSTR2020, Novosibirsk, Russia, 24 Feb 2020 - 28 Feb 2020; Journal of Instrumentation 15(09), C09057 (2020). doi:10.1088/1748-0221/15/09/C09057

Computer scienceBarrel (horology)610ddc:610InstrumentationAlgorithmMathematical PhysicsParticle identificationJournal of Instrumentation
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A comparison of STARFM and an unmixing-based algorithm for Landsat and MODIS data fusion

2015

article i nfo The focus of the current study is to compare data fusion methods applied to sensors with medium- and high- spatial resolutions. Two documented methods are applied, the spatial and temporal adaptive reflectance fusion model (STARFM) and an unmixing-based method which proposes a Bayesian formulation to incorporate prior spectral information.Furthermore, thestrengths of both algorithms arecombined ina novel data fusionmethod: the Spatial and Temporal Reflectance Unmixing Model (STRUM). The potential of each method is demonstrated using simulation imagery and Landsat and MODIS imagery. The theoretical basis of the algorithms causes STARFM and STRUM to produce Landsat-like reflecta…

Computer scienceBayesian formulationSpatial ecologySoil ScienceGeologyMETIS-308148Computers in Earth SciencesSensor fusionFocus (optics)ReflectivityAlgorithmNormalized Difference Vegetation IndexRemote sensingRemote Sensing of Environment
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Efficient linear fusion of partial estimators

2018

Abstract Many signal processing applications require performing statistical inference on large datasets, where computational and/or memory restrictions become an issue. In this big data setting, computing an exact global centralized estimator is often either unfeasible or impractical. Hence, several authors have considered distributed inference approaches, where the data are divided among multiple workers (cores, machines or a combination of both). The computations are then performed in parallel and the resulting partial estimators are finally combined to approximate the intractable global estimator. In this paper, we focus on the scenario where no communication exists among the workers, de…

Computer scienceBayesian probabilityInferenceAsymptotic distribution02 engineering and technology01 natural sciences010104 statistics & probability[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingArtificial Intelligence0202 electrical engineering electronic engineering information engineeringStatistical inferenceFusion rules0101 mathematicsElectrical and Electronic EngineeringComputingMilieux_MISCELLANEOUSMinimum mean square errorApplied MathematicsConstrained optimizationEstimator020206 networking & telecommunicationsComputational Theory and MathematicsSignal ProcessingComputer Vision and Pattern RecognitionStatistics Probability and Uncertainty[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingAlgorithmDigital Signal Processing
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Adaptive Importance Sampling: The past, the present, and the future

2017

A fundamental problem in signal processing is the estimation of unknown parameters or functions from noisy observations. Important examples include localization of objects in wireless sensor networks [1] and the Internet of Things [2]; multiple source reconstruction from electroencephalograms [3]; estimation of power spectral density for speech enhancement [4]; or inference in genomic signal processing [5]. Within the Bayesian signal processing framework, these problems are addressed by constructing posterior probability distributions of the unknowns. The posteriors combine optimally all of the information about the unknowns in the observations with the information that is present in their …

Computer scienceBayesian probabilityPosterior probabilityInference02 engineering and technologyMachine learningcomputer.software_genre01 natural sciences010104 statistics & probabilityMultidimensional signal processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingPrior probability0202 electrical engineering electronic engineering information engineering0101 mathematicsElectrical and Electronic EngineeringComputingMilieux_MISCELLANEOUSbusiness.industryApplied Mathematics020206 networking & telecommunicationsApproximate inferenceSignal ProcessingProbability distributionArtificial intelligencebusinessAlgorithmcomputer[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingImportance sampling
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A New Simple Computational Method of Simultaneous Constructing and Comparing Confidence Intervals of Shortest Length and Equal Tails for Making Effic…

2021

A confidence interval is a range of values that provides the user with useful information about how accurately a statistic estimates a parameter. In the present paper, a new simple computational method is proposed for simultaneous constructing and comparing confidence intervals of shortest length and equal tails in order to make efficient decisions under parametric uncertainty. This unified computational method provides intervals in several situations that previously required separate analysis using more advanced methods and tables for numerical solutions. In contrast to the Bayesian approach, the proposed approach does not depend on the choice of priors and is a novelty in the theory of st…

Computer scienceBayesian probabilityPrior probabilityProbability distributionQuantile functionPivotal quantityAlgorithmConfidence intervalParametric statisticsQuantile
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Influence Diagnostics for Meta-Analysis of Individual Patient Data Using Generalized Linear Mixed Models

2014

In meta-analysis, generalized linear mixed models (GLMMs) are usually used when heterogeneity is present and individual patient data (IPD) are available, while accepting binary, discrete as well as continuous response variables. In the present paper some measures of influence diagnostics based on log-likelihood are suggested and discussed. A known measure is approximated to get a simpler form, for which the information matrix is no more necessary. The performance of the proposed measure is assessed through a diagnostic analysis on simulated data reproducing a possible meta-analytical context of IPD with influential outliers. The proposed measure is showed to work well and to have a form sim…

Computer scienceBinary numberContext (language use)Diagnostics Individual Patient Data Meta-Analysis OutliersMeasure (mathematics)Generalized linear mixed modelsymbols.namesakeMeta-analysisOutlierStatisticssymbolsSettore SECS-S/01 - StatisticaFisher informationAlgorithmStatistic
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A chirp-z transform-based synchronizer for power system measurements

2005

In the last few years, increased interest in power and voltage quality has forced international working groups to standardize testing and measurement techniques. IEC 61000-4-30, which defines the characteristics of instrumentation for the measurement of power quality, refers to IEC 61000-4-7 for the evaluation of harmonics and interharmonics. This standard, revised in 2002, requires a synchronous sampling of voltage or current signal, in order to limit errors and to ensure reproducible results even in the presence of nonstationary signals. Therefore, an accurate estimation of the fundamental frequency is required, even in the presence of disturbances. In this paper, an algorithm to detect t…

Computer scienceBluestein's FFT algorithmFast Fourier transformChirp-z transform power quality synchronizationFundamental frequencyPower (physics)Electric power systemSampling (signal processing)SynchronizerHarmonicsElectronic engineeringElectrical and Electronic EngineeringInstrumentationSettore ING-INF/07 - Misure Elettriche E ElettronicheInterpolation
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