Search results for "vector [form factor]"

showing 10 items of 770 documents

Orientation of a Surface

2012

We know from Chap. 4 that in order to evaluate the flux of a vector field across a regular surface S, we need to choose a unit normal vector at each point of S in such a way that the resulting vector field is continuous. For instance, if we submerge a permeable sphere into a fluid and we select the field of unit normal outward vectors on the sphere, then the flux of the velocity field of the fluid across the sphere gives the amount of fluid leaving the sphere per unit time. However, if we select the field of unit normal inward vectors on the sphere, then the flux of the velocity field of the fluid across the sphere gives the amount of fluid entering the sphere per unit time (which is the ne…

Surface (mathematics)Orientation (vector space)PhysicsField (physics)Standard basisMathematical analysisTangent spaceFluxSPHERESVector field
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Limit Periodic Sets

1998

As explained at the end of the previous chapter, the most difficult problem in the study of bifurcations in a family of vector fields on a surface of genus 0 is the control of the periodic orbits. In fact, in generic smooth families the periodic orbits will be isolated for each value of the parameter. For analytic families we have two possibilities for each orbit: it may be isolated or belong to a whole annulus of periodic orbits. In this last case and for the parameter values for which the system has infinitely many periodic orbits, the vector field has a local analytic first integral and the nearby vector fields in the family may be studied by the perturbation theory introduced in Chapter…

Surface (mathematics)PhysicsMathematical analysisOrbit (dynamics)Periodic sequenceAnnulus (mathematics)Vector fieldAstrophysics::Earth and Planetary AstrophysicsSingular point of a curvePerturbation theoryLimit superior and limit inferior
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Non-invasive localization of atrial ectopic beats by using simulated body surface P-wave integral maps

2017

Non-invasive localization of continuous atrial ectopic beats remains a cornerstone for the treatment of atrial arrhythmias. The lack of accurate tools to guide electrophysiologists leads to an increase in the recurrence rate of ablation procedures. Existing approaches are based on the analysis of the P-waves main characteristics and the forward body surface potential maps (BSPMs) or on the inverse estimation of the electric activity of the heart from those BSPMs. These methods have not provided an efficient and systematic tool to localize ectopic triggers. In this work, we propose the use of machine learning techniques to spatially cluster and classify ectopic atrial foci into clearly diffe…

TachycardiaPhysiologyComputer sciencemedicine.medical_treatment02 engineering and technology030204 cardiovascular system & hematologyBioinformaticsBiochemistryACTIVATIONElectrocardiography0302 clinical medicineHeart RateAtrial FibrillationMedicine and Health SciencesImage Processing Computer-AssistedDEPOLARIZATIONBody surface P-wave integral mapsCardiac AtriaAtrial ectopic beatsMultidisciplinarymedicine.diagnostic_testORIGINApplied MathematicsSimulation and ModelingP waveBody Surface Potential MappingQRHeartHUMANSaarhythmiasAblationANATOMYBioassays and Physiological Analysismachine learningPhysical SciencesAtrial ectopic beatsMedicineAtrial Premature ComplexesFIBRILLATIONmedicine.symptomTACHYCARDIAAlgorithmsResearch ArticleclusteringTachycardia Ectopic AtrialComputer and Information SciencesSVMScienceCORONARY-SINUS0206 medical engineeringCardiologyResearch and Analysis MethodsMembrane PotentialTECNOLOGIA ELECTRONICAMachine Learning Algorithms03 medical and health sciencesArtificial IntelligenceHeart Conduction SystemSupport Vector MachinesBody surfacemedicineComputer SimulationHeart AtriaCoronary sinusFibrillationbusiness.industryElectrophysiological TechniquesBiology and Life SciencesPattern recognitionAtrial arrhythmiasELECTROPHYSIOLOGY020601 biomedical engineeringMODELElectrophysiologyCardiovascular AnatomyCardiac ElectrophysiologyArtificial intelligencebusinessElectrocardiographyBiomarkersMathematics
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Ventricular Fibrillation and Tachycardia detection from surface ECG using time-frequency representation images as input dataset for machine learning

2017

Parameter-less ventricular fibrillation detection with time-frequency representation.Time-frequency representations are treated as images for a classifier.A comparison for four classifiers demonstrates the validity of the proposed method.The proposed technique could be applied to any signal and research field.This is a novel approach to signal analysis. Background and objectiveTo safely select the proper therapy for Ventricullar Fibrillation (VF) is essential to distinct it correctly from Ventricular Tachycardia (VT) and other rhythms. Provided that the required therapy would not be the same, an erroneous detection might lead to serious injuries to the patient or even cause Ventricular Fibr…

TachycardiaSupport Vector MachineComputer scienceSpeech recognition0206 medical engineeringDatasets as TopicHealth Informatics02 engineering and technologyVentricular tachycardiaMachine learningcomputer.software_genreMachine LearningElectrocardiographyTachycardia0202 electrical engineering electronic engineering information engineeringmedicineHumansFibrillationbusiness.industrySignal Processing Computer-AssistedPattern recognitionmedicine.disease020601 biomedical engineeringComputer Science ApplicationsVentricular FibrillationVentricular fibrillation020201 artificial intelligence & image processingNeural Networks ComputerArtificial intelligencemedicine.symptombusinessClassifier (UML)computerSoftwareComputer Methods and Programs in Biomedicine
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Spacelike energy of timelike unit vector fields on a Lorentzian manifold

2004

On a Lorentzian manifold, we define a new functional on the space of unit timelike vector fields given by the L2 norm of the restriction of the covariant derivative of the vector field to its orthogonal complement. This spacelike energy is related with the energy of the vector field as a map on the tangent bundle endowed with the Kaluza–Klein metric, but it is more adapted to the situation. We compute the first and second variation of the functional and we exhibit several examples of critical points on cosmological models as generalized Robertson–Walker spaces and Godel universe, on Einstein and contact manifolds and on Lorentzian Berger’s spheres. For these critical points we have also stu…

Tangent bundleMathematical analysisGeneral Physics and AstronomyOrthogonal complementCongruence (general relativity)ManifoldCovariant derivativeGeneral Relativity and Quantum CosmologyDifferential geometryUnit vectorVector fieldMathematics::Differential GeometryGeometry and TopologyMathematical PhysicsMathematicsMathematical physicsJournal of Geometry and Physics
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Robust g-filter using support vector method

2004

This Letter presents a new approach to time series modelling using the support vector machines (SVM). Although the g filter can provide stability in several time series models, the SVM is proposed here to provide robustness in the estimation of the g filter coefficients. Examples in chaotic time series prediction and channel equalization show the advantages of the joint SVM g filter. Publicado

TelecomunicacionesChannel equalizationGamma filterIterated predictionSuuport vector machines
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Learning non-linear time-scales with kernel -filters

2009

A family of kernel methods, based on the @c-filter structure, is presented for non-linear system identification and time series prediction. The kernel trick allows us to develop the natural non-linear extension of the (linear) support vector machine (SVM) @c-filter [G. Camps-Valls, M. Martinez-Ramon, J.L. Rojo-Alvarez, E. Soria-Olivas, Robust @c-filter using support vector machines, Neurocomput. J. 62(12) (2004) 493-499.], but this approach yields a rigid system model without non-linear cross relation between time-scales. Several functional analysis properties allow us to develop a full, principled family of kernel @c-filters. The improved performance in several application examples suggest…

TelecomunicacionesSupport vector machinesbusiness.industryCognitive NeuroscienceNonlinear System IdentificationPattern recognitionKernel principal component analysisComputer Science ApplicationsKernel methodMercer's KernelArtificial IntelligenceVariable kernel density estimationString kernelKernel embedding of distributionsPolynomial kernelRadial basis function kernelGamma-FiltersArtificial intelligenceTree kernelbusinessMathematicsNeurocomputing
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Robust γ-filter using support vector machines

2009

This Letter presents a new approach to time-series modelling using the support vector machines (SVM). Although the g-filter can provide stability in several time-series models, the SVM is proposed here to provide robustness in the estimation of the g-filter coefficients. Examples in chaotic time-series prediction and channel equalization show the advantages of the joint SVM g-filter. Teoría de la Señal y Comunicaciones

Telecomunicacionesbusiness.industryComputer scienceCognitive NeuroscienceChaoticPattern recognitionComputer Science ApplicationsSupport vector machineFilter designArtificial IntelligenceRobustness (computer science)3325 Tecnología de las TelecomunicacionesArtificial intelligencebusinessNeurocomputing
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A novel correction method for a low cost sensorless control system of IPMSM electrical drives

2008

In this paper a novel correction method for sensorless Field Oriented Control System of Brushless internal Permanent Magnet Electrical Drives is introduced discussed and experimentally validated. The novelty of this control system is the estimation of rotor speed and angular position is based on the back electromotive force space vector determination, without the aid of voltage probes. Actual voltage signals needed for estimation are replaced with the reference ones given by the current controller. This choice obviously introduces an error that have been vanished by means of a new compensating function or with the aid of data coming from experimental tests. Experimental verifications of the…

Test benchVector controlAngular displacementControl theoryComputer scienceMagnetControl systemTorqueControl engineeringCounter-electromotive forceVoltage2008 IEEE International Symposium on Industrial Electronics
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Experimental Implementation of an Enhanced Field Oriented Control Strategy for Induction Motors Using a Low-Cost ATSAM3X8E Microcontroller

2020

This paper presents a low-cost Micro Controller Unit (MCU) implementation of an enhanced Field Oriented Control (FOC) technique that takes into account the non-linearity of the ferromagnetic material. The algorithm is applied to a three-phase 5.5 kW Induction Motor (IM) and experimentally carried out by means of an ATMEL ATSAM3X8E microcontroller. The effectiveness of the enhanced control strategy is verified by comparing the dynamic performances of the electric drive with those obtained by means of a traditional FOC technique. For this purpose, an experimental test bench is set up for the implementation of the enhanced FOC technique. Finally, the technical and economic features of the simp…

Test benchVector controlComputer science020209 energy020208 electrical & electronic engineeringControl engineering02 engineering and technologyField Oriented Control (FOC)Settore ING-IND/32 - Convertitori Macchine E Azionamenti ElettriciElectrical drivesSet (abstract data type)Microcontrollermicrocontrollerinduction motors0202 electrical engineering electronic engineering information engineeringElectric driveInduction motor2020 Fifteenth International Conference on Ecological Vehicles and Renewable Energies (EVER)
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