Search results for " function"

showing 10 items of 9395 documents

Out-of-Band Signaling Scheme for High Speed Wireless LANs

2007

In recent years, the physical layer data rate provided by 802.11 Wireless LANs has dramatically increased thanks to significant advances in the modulation and coding techniques employed. However, previous studies show that the 802.11 MAC operation, namely the distributed coordination function (DCF), represents a limiting factor: the throughput efficiency drops as the channel bit rate increases, and a throughput upper limit does indeed exist when the channel bit rate goes to infinite high. These findings indicate that the performance of the DCF protocol will not be efficiently improved by merely increasing the channel bit rate. This paper shows that the DCF performance may significantly bene…

Computer scienceComputer network performanceWireless LANThroughputDistributed coordination functionBackward compatibilityIEEE 802.11Packet switchingWireless lanWireless LAN Throughput Bit rate Physical layer Modulation coding Access protocols Content management Signal design Media Access Protocol Performance analysisElectrical and Electronic EngineeringIEEE 802.11Settore ING-INF/03 - Telecomunicazionibusiness.industryApplied MathematicsComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSPhysical layerCode rateComputer Science ApplicationsComputer network performance; IEEE 802.11; Wireless LANBurst switchingModulationOut-of-band managementbusinessCommunication channelComputer networkIEEE Transactions on Wireless Communications
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Fake Nodes approximation for Magnetic Particle Imaging

2020

Accurately reconstructing functions with discontinuities is the key tool in many bio-imaging applications as, for instance, in Magnetic Particle Imaging (MPI). In this paper, we apply a method for scattered data interpolation, named mapped bases or Fake Nodes approach, which incorporates discontinuities via a suitable mapping function. This technique naturally mitigates the Gibbs phenomenon, as numerical evidence for reconstructing MPI images confirms.

Computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONradial basis functionsFunction (mathematics)Magnetic Particle ImagingClassification of discontinuitieskernelsinterpolationGibbs phenomenonSettore MAT/08 - Analisi Numericasymbols.namesakeMagnetic particle imagingsymbolsKey (cryptography)Radial basis functioninterpolation; kernels; Magnetic Particle Imaging; radial basis functionsGFadial basis functionAlgorithmComputingMethodologies_COMPUTERGRAPHICSInterpolation2020 IEEE 20th Mediterranean Electrotechnical Conference ( MELECON)
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Least-squares community extraction in feature-rich networks using similarity data

2021

We explore a doubly-greedy approach to the issue of community detection in feature-rich networks. According to this approach, both the network and feature data are straightforwardly recovered from the underlying unknown non-overlapping communities, supplied with a center in the feature space and intensity weight(s) over the network each. Our least-squares additive criterion allows us to search for communities one-by-one and to find each community by adding entities one by one. A focus of this paper is that the feature-space data part is converted into a similarity matrix format. The similarity/link values can be used in either of two modes: (a) as measured in the same scale so that one may …

Computer scienceEconomicsKernel FunctionsSocial Sciences02 engineering and technologyLeast squaresInfographicsTranslocation GeneticGeographical LocationsMedical Conditions0202 electrical engineering electronic engineering information engineeringMedicine and Health SciencesPsychologyCluster AnalysisOperator TheoryData ManagementMultidisciplinaryApplied MathematicsSimulation and ModelingQRExperimental PsychologyEuropeFeature (computer vision)Research DesignPhysical SciencesMedicine020201 artificial intelligence & image processingGraphsAlgorithmsNetwork AnalysisNetwork analysisResearch ArticleComputer and Information SciencesScienceFeature vectorScale (descriptive set theory)Research and Analysis MethodsColumn (database)Similarity (network science)020204 information systemsParasitic DiseasesLeast-Squares AnalysisFeature databusiness.industryData VisualizationBiology and Life SciencesPattern recognitionTropical DiseasesEconomic AnalysisMalariaPeople and PlacesArtificial intelligencebusinessMathematicsPLoS ONE
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Introduction: Digital Filters and Filter Banks

2015

A basic operation of spectr is filterin. In this introductory chapter, processing of one- and two-dimensional signals by digital filters and filter banks is outlined. A polyphase implementation of multirate filtering is described. The application of filtering with IIR filters, whose transfer functions are rational, is described. Bases and frames in the signals’ space that are generated by perfect reconstruction filter banks are discussed. The Butterworth filters, which are used in further constructions, are introduced.

Computer scienceElectronic engineeringPolyphase systemButterworth filterFilter (signal processing)Capacitor-input filterFilter bankTransfer functionInfinite impulse responseDigital filter
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A Bayesian unified framework for risk estimation and cluster identification in small area health data analysis.

2020

Many statistical models have been proposed to analyse small area disease data with the aim of describing spatial variation in disease risk. In this paper, we propose a Bayesian hierarchical model that simultaneously allows for risk estimation and cluster identification. Our model formulation assumes that there is an unknown number of risk classes and small areas are assigned to a risk class by means of independent allocation variables. Therefore, areas within each cluster are assumed to share a common risk but they may be geographically separated. The posterior distribution of the parameter representing the number of risk classes is estimated using a novel procedure that combines its prior …

Computer scienceEpidemiologyPathology and Laboratory Medicine01 natural sciencesGeographical locations010104 statistics & probabilityChickenpoxMathematical and Statistical TechniquesStatisticsMedicine and Health SciencesPublic and Occupational Health0303 health sciencesMultidisciplinarySimulation and ModelingQREuropeIdentification (information)Medical MicrobiologySmall-Area AnalysisViral PathogensVirusesPhysical SciencesMedicinePathogensAlgorithmsResearch ArticleHerpesvirusesScienceBayesian probabilityPosterior probabilityBayesian MethodDisease SurveillanceDisease clusterResearch and Analysis MethodsRisk AssessmentMicrobiologyVaricella Zoster Virus03 medical and health sciencesRisk classPrior probabilityCovariateBayesian hierarchical modelingHumansEuropean Union0101 mathematicsMicrobial Pathogens030304 developmental biologyBiology and life sciencesOrganismsStatistical modelBayes TheoremProbability TheoryProbability DistributionMarginal likelihoodConvolutionSpainPeople and placesDNA virusesMathematical FunctionsMathematicsPloS one
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Towards an Efficient Implementation of an Accurate SPH Method

2020

A modified version of the Smoothed Particle Hydrodynamics (SPH) method is considered in order to overcome the loss of accuracy of the standard formulation. The summation of Gaussian kernel functions is employed, using the Improved Fast Gauss Transform (IFGT) to reduce the computational cost, while tuning the desired accuracy in the SPH method. This technique, coupled with an algorithmic design for exploiting the performance of Graphics Processing Units (GPUs), makes the method promising, as shown by numerical experiments.

Computer scienceGauss transformOrder (ring theory)Smoothed Particle Hydrodynamics Improved Fast Gauss Transform Graphics Processing UnitsSmoothed-particle hydrodynamicsSmoothed Particle Hydrodynamicssymbols.namesakeImproved Fast Gauss TransformGaussian functionsymbolsAlgorithm designGraphics Processing UnitsGraphicsAlgorithmComputingMethodologies_COMPUTERGRAPHICS
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Experimental validation for spectrum cartography using adaptive multi-kernels

2017

This paper validates the functionality of an algorithm for spectrum cartography, generating a radio environment map (REM) using adaptive radial basis functions (RBF) based on a limited number of measurements. The power at all locations is estimated as a linear combination of different RBFs without assuming any prior information about either power spectral densities (PSD) of the transmitters or their locations. The RBFs are represented as centroids at optimized locations, using machine learning to jointly optimize their positions, weights and Gaussian decaying parameters. Optimization is performed using expectation maximization with a least squares loss function and a quadratic regularizer. …

Computer scienceGaussianCentroid020206 networking & telecommunications02 engineering and technologyFunction (mathematics)Least squaressymbols.namesakeQuadratic equationExpectation–maximization algorithm0202 electrical engineering electronic engineering information engineeringsymbolsRadial basis functionLinear combinationCartography2017 11th International Conference on Signal Processing and Communication Systems (ICSPCS)
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Optimal Filter Estimation for Lucas-Kanade Optical Flow

2012

Optical flow algorithms offer a way to estimate motion from a sequence of images. The computation of optical flow plays a key-role in several computer vision applications, including motion detection and segmentation, frame interpolation, three-dimensional scene reconstruction, robot navigation and video compression. In the case of gradient based optical flow implementation, the pre-filtering step plays a vital role, not only for accurate computation of optical flow, but also for the improvement of performance. Generally, in optical flow computation, filtering is used at the initial level on original input images and afterwards, the images are resized. In this paper, we propose an image filt…

Computer scienceGaussianComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONOptical flowGaussian blurlcsh:Chemical technologyGaussian filteringcomputer.software_genreBiochemistryArticleAnalytical Chemistryoptical flowsymbols.namesakeLucas–Kanade methodoptical flow; Lucas-Kanade; Gaussian filtering; optimal filteringGaussian functionlcsh:TP1-1185SegmentationComputer visionLucas-KanadeElectrical and Electronic EngineeringInstrumentationbusiness.industryoptimal filteringMotion detectionFilter (signal processing)Atomic and Molecular Physics and OpticsComputer Science::Computer Vision and Pattern RecognitionsymbolsArtificial intelligenceData miningMotion interpolationbusinesscomputerData compressionSensors
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Computational issues in fitting joint frailty models for recurrent events with an associated terminal event.

2020

Abstract Background and objective: Joint frailty regression models are intended for the analysis of recurrent event times in the presence of informative drop-outs. They have been proposed for clinical trials to estimate the effect of some treatment on the rate of recurrent heart failure hospitalisations in the presence of drop-outs due to cardiovascular death. Whereas a R-software-package for fitting joint frailty models is available, some technical issues have to be solved in order to use SASⓇ 1 software, which is required in the regulatory environment of clinical trials. Methods: First, we demonstrate how to solve these issues by deriving proper likelihood-decompositions, in particular fo…

Computer scienceHealth InformaticsMachine learningcomputer.software_genre030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineLinear regressionHumansComputer SimulationEvent (probability theory)ProbabilityProportional Hazards ModelsHeart FailureLikelihood FunctionsFrailtybusiness.industryModels CardiovascularReproducibility of ResultsRegression analysisConfidence intervalComputer Science ApplicationsHospitalizationTransformation (function)Data Interpretation StatisticalMultivariate AnalysisArtificial intelligencebusinesscomputer030217 neurology & neurosurgeryAlgorithmsSoftwareComputer methods and programs in biomedicine
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A new Adaptive and Progressive Image Transmission Approach using Function Superpositions

2010

International audience; We present a novel approach to adaptive and progressive image transmission, based on the decomposition of an image into compositions and superpositions of monovariate functions. The monovariate functions are iteratively constructed and transmitted, one after the other, to progressively reconstruct the original image: the progressive transmission is performed directly in the 1D space of the monovariate functions and independently of any statistical properties of the image. Each monovariate function contains only a fraction of the pixels of the image. Each new transmitted monovariate function adds data to the previously transmitted monovariate functions. After each tra…

Computer scienceImage qualityComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyIterative reconstructionmultidimensional function decompositionSuperposition principleRobustness (computer science)[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineeringComputer visionsignal processingspatial scalability.Image resolutionImage restorationSignal processingPixelbusiness.industryprogressive image transmissionGeneral Engineering020206 networking & telecommunicationsAtomic and Molecular Physics and Opticsfunctional representation[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Computer Science::Computer Vision and Pattern RecognitionKolmogorov superposition theorem020201 artificial intelligence & image processingTomographyArtificial intelligencebusinessDigital filterAlgorithmspatial scalabilityImage compression
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