Search results for "vector [form factor]"

showing 10 items of 770 documents

A survey of active learning algorithms for supervised remote sensing image classification

2011

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active …

FOS: Computer and information sciencesComputer scienceComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern RecognitionMachine learningcomputer.software_genreactive learningHyperspectral image classificationEntropy (information theory)Electrical and Electronic EngineeringArchitectureRemote sensingvery high resolution (VHR)PixelContextual image classificationbusiness.industryHyperspectral imagingSupport vector machinehyperspectraltraining set definitionSignal Processingsupport vector machine (SVM)Artificial intelligenceHeuristicsbusinessAlgorithmcomputerimage classification
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Multiscale Information Decomposition: Exact Computation for Multivariate Gaussian Processes

2017

Exploiting the theory of state space models, we derive the exact expressions of the information transfer, as well as redundant and synergistic transfer, for coupled Gaussian processes observed at multiple temporal scales. All of the terms, constituting the frameworks known as interaction information decomposition and partial information decomposition, can thus be analytically obtained for different time scales from the parameters of the VAR model that fits the processes. We report the application of the proposed methodology firstly to benchmark Gaussian systems, showing that this class of systems may generate patterns of information decomposition characterized by prevalently redundant or sy…

FOS: Computer and information sciencesInformation transferComputer scienceGaussianSocial SciencesGeneral Physics and AstronomyInformation theory01 natural sciences010305 fluids & plasmasState spaceStatistical physicslcsh:Scienceinformation theorymultiscale entropylcsh:QC1-999Interaction informationMathematics and Statisticssymbolsinformation dynamicsInformation dynamics; Information transfer; Multiscale entropy; Multivariate time series analysis; Redundancy and synergy; State space models; Vector autoregressive models; Physics and Astronomy (all)information dynamics; information transfer; multiscale entropy; multivariate time series analysis; redundancy and synergy; state space models; vector autoregressive modelsMultivariate time series analysiMathematics - Statistics Theorylcsh:AstrophysicsStatistics Theory (math.ST)Statistics - ApplicationsMethodology (stat.ME)symbols.namesakePhysics and Astronomy (all)0103 physical scienceslcsh:QB460-466FOS: Mathematicsinformation transferRelevance (information retrieval)Applications (stat.AP)Transfer Entropy010306 general physicsGaussian processStatistics - MethodologyState space modelstate space modelsmultivariate time series analysisredundancy and synergyvector autoregressive modelsInformation dynamicVector autoregressive modelSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaTransfer entropylcsh:Qlcsh:PhysicsEntropy
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Local Granger causality

2021

Granger causality is a statistical notion of causal influence based on prediction via vector autoregression. For Gaussian variables it is equivalent to transfer entropy, an information-theoretic measure of time-directed information transfer between jointly dependent processes. We exploit such equivalence and calculate exactly the 'local Granger causality', i.e. the profile of the information transfer at each discrete time point in Gaussian processes; in this frame Granger causality is the average of its local version. Our approach offers a robust and computationally fast method to follow the information transfer along the time history of linear stochastic processes, as well as of nonlinear …

FOS: Computer and information sciencesInformation transferGaussianFOS: Physical sciencestechniques; information theory; granger causalityMachine Learning (stat.ML)Quantitative Biology - Quantitative Methods01 natural sciences010305 fluids & plasmasVector autoregressionsymbols.namesakegranger causalityGranger causalityStatistics - Machine Learning0103 physical sciencesApplied mathematicstime serie010306 general physicsQuantitative Methods (q-bio.QM)Mathematicsinformation theoryStochastic processDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksComputational Physics (physics.comp-ph)Discrete time and continuous timeAutoregressive modelFOS: Biological sciencesSettore ING-INF/06 - Bioingegneria Elettronica E InformaticasymbolsTransfer entropytechniquesPhysics - Computational Physics
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Randomized Block Frank–Wolfe for Convergent Large-Scale Learning

2017

Owing to their low-complexity iterations, Frank-Wolfe (FW) solvers are well suited for various large-scale learning tasks. When block-separable constraints are present, randomized block FW (RB-FW) has been shown to further reduce complexity by updating only a fraction of coordinate blocks per iteration. To circumvent the limitations of existing methods, the present work develops step sizes for RB-FW that enable a flexible selection of the number of blocks to update per iteration while ensuring convergence and feasibility of the iterates. To this end, convergence rates of RB-FW are established through computational bounds on a primal sub-optimality measure and on the duality gap. The novel b…

FOS: Computer and information sciencesMathematical optimization0102 computer and information sciences02 engineering and technology01 natural sciencesMeasure (mathematics)Machine Learning (cs.LG)Convergence (routing)FOS: Mathematics0202 electrical engineering electronic engineering information engineeringFraction (mathematics)Electrical and Electronic EngineeringMathematics - Optimization and ControlMathematicsSequenceDuality gapComputer Science - Numerical Analysis020206 networking & telecommunicationsNumerical Analysis (math.NA)Stationary pointSupport vector machineComputer Science - LearningOptimization and Control (math.OC)010201 computation theory & mathematicsIterated functionSignal ProcessingAlgorithmIEEE Transactions on Signal Processing
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A Unified SVM Framework for Signal Estimation

2013

This paper presents a unified framework to tackle estimation problems in Digital Signal Processing (DSP) using Support Vector Machines (SVMs). The use of SVMs in estimation problems has been traditionally limited to its mere use as a black-box model. Noting such limitations in the literature, we take advantage of several properties of Mercer's kernels and functional analysis to develop a family of SVM methods for estimation in DSP. Three types of signal model equations are analyzed. First, when a specific time-signal structure is assumed to model the underlying system that generated the data, the linear signal model (so called Primal Signal Model formulation) is first stated and analyzed. T…

FOS: Computer and information sciencesbusiness.industryNoise (signal processing)Computer scienceApplied MathematicsSpectral density estimationArray processingPattern recognitionMachine Learning (stat.ML)Statistics - ApplicationsSupport vector machineKernel (linear algebra)Kernel methodComputational Theory and MathematicsStatistics - Machine LearningArtificial IntelligenceSignal ProcessingApplications (stat.AP)Computer Vision and Pattern RecognitionArtificial intelligenceElectrical and Electronic EngineeringStatistics Probability and UncertaintybusinessDigital signal processingReproducing kernel Hilbert space
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Multiscale partial information decomposition of dynamic processes with short and long-range correlations: theory and application to cardiovascular co…

2022

Abstract Objective. In this work, an analytical framework for the multiscale analysis of multivariate Gaussian processes is presented, whereby the computation of Partial Information Decomposition measures is achieved accounting for the simultaneous presence of short-term dynamics and long-range correlations. Approach. We consider physiological time series mapping the activity of the cardiac, vascular and respiratory systems in the field of Network Physiology. In this context, the multiscale representation of transfer entropy within the network of interactions among Systolic arterial pressure (S), respiration (R) and heart period (H), as well as the decomposition into unique, redundant and s…

FOS: Computer and information sciencesmultivariate time seriesPhysiologyEntropyRespirationBiomedical EngineeringBiophysicsheart rate variabilitytransfer entropyredundancy and synergyBlood PressureHeartQuantitative Biology - Quantitative MethodsCardiovascular SystemMethodology (stat.ME)Heart RatePhysiology (medical)FOS: Biological sciencesCardiovascular controlSettore ING-INF/06 - Bioingegneria Elettronica E Informaticavector autoregressive fractionally integrated (VARFI) modelsHumansQuantitative Methods (q-bio.QM)Statistics - MethodologyPhysiological measurement
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Audio-video people recognition system for an intelligent environment

2011

In this paper an audio-video system for intelligent environments with the capability to recognize people is presented. Users are tracked inside the environment and their positions and activities can be logged. Users identities are assessed through a multimodal approach by detecting and recognizing voices and faces through the different cameras and microphones installed in the environment. This approach has been chosen in order to create a flexible and cheap but reliable system, implemented using consumer electronics. Voice features are extracted by a short time cepstrum analysis, and face features are extracted using the eigenfaces technique. The recognition task is solved using the same Su…

Face featureSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionibusiness.industryComputer scienceIntelligent environmentPeople recognitionFeature extractionReliable systemSet-up phaseSingle sensorFacial recognition systemSelection principleSupport vector machineSoftwareEigenfaceMulti-modal approachMiddlewareCepstrumLearning ruleIntelligent environmentCepstrum analysiComputer visionArtificial intelligenceEigenfacebusiness
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Current signature based fault diagnosis of field-oriented and direct torque-controlled induction motor drives

2017

In this article, the operation of three-phase squirrel-cage induction motors is analysed under faulty conditions in closed loop with state-of-the-art controllers, namely, the field-oriented control...

Field-oriented controlVector controlmodified winding function theorydirect torque controlComputer science020209 energyMechanical Engineering020208 electrical & electronic engineeringfault diagnostics02 engineering and technologydirect torque control; fault diagnostics; Field-oriented control; induction motor drives; modified winding function theory; Control and Systems Engineering; Mechanical EngineeringFault (power engineering)induction motor drivesSignature (logic)Field (computer science)Direct torque controlControl theoryControl and Systems Engineering0202 electrical engineering electronic engineering information engineeringTorqueCurrent (fluid)Induction motor
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‘Too interconnected to fail’ financial network of US CDS market: Topological fragility and systemic risk

2012

A small segment of credit default swaps (CDS) on residential mortgage backed securities (RMBS) stand implicated in the 2007 financial crisis. The dominance of a few big players in the chains of insurance and reinsurance for CDS credit risk mitigation for banks' assets has led to the idea of too interconnected to fail (TITF) resulting, as in the case of AIG, of a tax payer bailout. We provide an empirical reconstruction of the US CDS network based on the FDIC Call Reports for off balance sheet bank data for the 4th quarter in 2007 and 2008. The propagation of financial contagion in networks with dense clustering which reflects high concentration or localization of exposures between few parti…

FinanceOrganizational Behavior and Human Resource ManagementEconomics and EconometricsFinancial contagionCredit default swapFinancial contagionbusiness.industryFinancial networksFinancial marketFinancial systemFinancial networksEigenvector centralityCredit default swapsSystemic riskEconomicsSystemic riskFinancial contagion systemic riskBank failurebusinessSuper-spreader taxBailoutCredit riskJournal of Economic Behavior & Organization
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Existence and uniqueness of solutions to superdifferential equations

1993

Abstract We state and prove the theorem of existence and uniqueness of solutions to ordinary superdifferential equations on supermanifolds. It is shown that any supervector field, X = X0 + X1, has a unique integral flow, Г: R 1¦1 x (M, AM) → (M, AM), satisfying a given initial condition. A necessary and sufficient condition for this integral flow to yield an R 1¦1-action is obtained: the homogeneous components, X0, and, X1, of the given field must define a Lie superalgebra of dimension (1, 1). The supergroup structure on R 1¦1, however, has to be specified: there are three non-isomorphic Lie supergroup structures on R 1¦1, all of which have addition as the group operation in the underlying …

Flow (mathematics)Simple Lie groupMathematical analysisLie bracket of vector fieldsAdjoint representationGeneral Physics and AstronomyLie groupLie derivativeLie superalgebraGeometry and TopologySupergroupMathematical PhysicsMathematicsJournal of Geometry and Physics
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