Search results for "Estimation theory"

showing 10 items of 84 documents

Process parameters calibration in 3D tube hydroforming processes

2007

In tube hydroforming the concurrent actions of pressurized fluid and mechanical feeding allow to obtain tube shapes characterized by complex geometries such as different diameters sections and/or bulged zones. What is crucial in such processes is the proper design of operative parameters aimed to avoid defects (for instance shape defects or ductile fractures). The main process parameters are material feeding history (i.e. the punches velocity history) and internal pressure path during the process. In more complex three dimensional processes, also the action of a counterpunch is generally useful to reduce thinning in particular in expansion zones of the tube (i.e. T or Y shaped tubes). The g…

Optimal designEngineeringHydroformingTube hydroformingbusiness.industryEstimation theoryProcess (computing)Mechanical engineeringForming processesInternal pressureWrinklingDesign for manufacturabilityGradient methodTube (container)business
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Block bootstrap methods and the choice of stocks for the long run

2013

Financial advisors commonly recommend that the investment horizon should be rather long in order to benefit from the ‘time diversification’. In this case, in order to choose the optimal portfolio, it is necessary to estimate the risk and reward of several alternative portfolios over a long-run given a sample of observations over a short-run. Two interrelated obstacles in these estimations are lack of sufficient data and the uncertainty in the nature of the return generating process. To overcome these obstacles researchers rely heavily on block bootstrap methods. In this paper we demonstrate that the estimates provided by a block bootstrap method are generally biased and we propose two metho…

Order (exchange)Computer scienceProcess (engineering)Estimation theoryEconometricsPortfolioSample (statistics)Time seriesInvestment (macroeconomics)General Economics Econometrics and FinanceFinanceBlock (data storage)Quantitative Finance
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Stellar physics with the ALHAMBRA photometric system

2011

GREAT-ESF Workshop: Stellar Atmospheres in the Gaia Era 23–24 June 2011, Vrije Universiteit Brussels, Belgium.

PhysicsHistoryEstimation theoryExtinction (astronomy)AstronomyPhotometric systemAstrophysicsStellar classificationComputer Science ApplicationsEducationStarsPhotometry (astronomy)Stellar physicsRange (statistics)
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Approaches to evaluate the virtual instrumentation measurement uncertainties

2002

This paper deals with the metrological characterization of virtual instruments. After a brief description of the features, the components and the working principle of the virtual instruments and the various uncertainty sources are analyzed. Then, two methods to evaluate the uncertainty of the measurement results are presented: a numerical method simulating the physical process of the A/D conversion, and an approximated theoretical method applying the "uncertainty propagation law" of the "guide to the expression of uncertainty in measurement." With both methods, the combined standard uncertainty of the measurement result is obtained, starting from the standard uncertainty generated by each s…

Propagation of uncertaintyComputer simulationVirtual instrumentationEstimation theoryComputer scienceNumerical analysisProcess (computing)Control engineeringMetrologyMeasurement uncertaintySensitivity analysisElectrical and Electronic EngineeringInstrumentationUncertainty analysisIMTC 2001. Proceedings of the 18th IEEE Instrumentation and Measurement Technology Conference. Rediscovering Measurement in the Age of Informatics (Cat. No.01CH 37188)
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Parameter Sensitivity and the Quality of Model Predictions

1994

Using SIM-PEL, a comprehensive model for the pelagic compartment of lake ecosystems, we analyse synergistic toxicant effects in lake ecosystems. We show, that — even for a rather simple model — model predictions may be strongly dependent on the time horizon of the prediction and on the quality of input parameters. For longer time spans, small errors in parameter estimation may lead to qualitatively wrong prediction of toxicant effects. Monte Carlo simulations allow to take errors in parameter estimation into account, but they need rather good estimates of parameter variance.

Quality (physics)Estimation theoryMonte Carlo methodLake ecosystemTime horizonVariance (accounting)Sensitivity (control systems)Statistical physicsQuantitative Biology::OtherPhytoplankton biomassMathematics
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Physics-aware Gaussian processes in remote sensing

2018

Abstract Earth observation from satellite sensory data poses challenging problems, where machine learning is currently a key player. In recent years, Gaussian Process (GP) regression has excelled in biophysical parameter estimation tasks from airborne and satellite observations. GP regression is based on solid Bayesian statistics, and generally yields efficient and accurate parameter estimates. However, GPs are typically used for inverse modeling based on concurrent observations and in situ measurements only. Very often a forward model encoding the well-understood physical relations between the state vector and the radiance observations is available though and could be useful to improve pre…

Signal Processing (eess.SP)FOS: Computer and information sciences010504 meteorology & atmospheric sciences0211 other engineering and technologies02 engineering and technologyStatistics - Applications01 natural sciencessymbols.namesakeFOS: Electrical engineering electronic engineering information engineeringApplications (stat.AP)Electrical Engineering and Systems Science - Signal ProcessingGaussian processGaussian process emulator021101 geological & geomatics engineering0105 earth and related environmental sciencesbusiness.industryEstimation theoryBayesian optimizationState vectorMissing dataBayesian statisticssymbolsGlobal Positioning SystembusinessAlgorithmSoftwareApplied Soft Computing
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Rapid parameter estimation of discrete decaying signals using autoencoder networks

2021

Machine learning: science and technology 2(4), 045024 (2021). doi:10.1088/2632-2153/ac1eea

Signal Processing (eess.SP)FOS: Computer and information sciencesAccuracy and precisionComputer Science - Machine LearningComputer scienceddc:621.3FOS: Physical sciences01 natural sciencesSignalMachine Learning (cs.LG)010309 opticsExponential growthArtificial Intelligence0103 physical sciencesFOS: Electrical engineering electronic engineering information engineeringLimit (mathematics)Neural and Evolutionary Computing (cs.NE)Electrical Engineering and Systems Science - Signal Processing010306 general physicsSignal processingArtificial neural networkEstimation theoryComputer Science - Neural and Evolutionary ComputingAutoencoder621.3Human-Computer InteractionPhysics - Data Analysis Statistics and ProbabilityAlgorithmSoftwareData Analysis Statistics and Probability (physics.data-an)Machine Learning: Science and Technology
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Incipient damage identification through characteristics of the analytical signal response

2008

The analytical signal is a complex representation of a time domain signal: the real part is the time domain signal itself, while the imaginary part is its Hilbert transform. It has been observed that damage, even at a very low level, yields clearly detectable variations of analytical signal quantities such as phase and instantaneous frequency. This observation can represent a step toward a quick and effective tool to recognize the presence of incipient damage where other frequency-based techniques fail. In this paper a damage identification procedure based on an adimensional functional of the square of the difference between the characteristics of the analytical theoretical and measured sig…

Signal processingComplex representationSignal processingEstimation theoryAnalytical SignalBuilding and ConstructionInstantaneous phasesymbols.namesakeMechanics of MaterialsRobustness (computer science)symbolsTime domainHilbert transformSignal transfer functionSettore ICAR/08 - Scienza Delle CostruzioniStructural damage identificationAlgorithmCivil and Structural EngineeringMathematicsStructural Control and Health Monitoring
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Flip angle considerations in (3)helium-MRI.

2000

3Helium-MRI ((3)He-MRI) can be used for analysis of lung function, e. g. dynamic imaging of ventilation and gas diffusion within the lung, assessment of intrapulmonary oxygen concentrations and their time course. During imaging, the irreversible signal loss due to depolarizing radio frequency excitations can be described using the flip angle (FA) alpha. This parameter has to be quantified in order to account for it during quantitative assessment of the (3)helium signal intensity and its temporal development. This technical report reviews two different methods to determine alpha. Limitations and possible error sources of each method are discussed.

Signal processingMaterials sciencemedicine.diagnostic_testEstimation theoryDynamic imagingMagnetic resonance imagingSignalHeliumMagnetic Resonance ImagingRespiratory Function TestsOxygenNuclear magnetic resonanceFlip angleIsotopesmedicineTidal VolumeMolecular MedicineHumansRadiology Nuclear Medicine and imagingComputer SimulationRadio frequencyHyperpolarization (physics)SpectroscopyNMR in biomedicine
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A Space-Vector State Dynamic Model of the Synchronous Reluctance Motor Including Self and Cross-Saturation Effects and its Parameters Estimation

2018

This paper proposes a space-vector dynamic model of the Synchronous Reluctance Motor (SynRM) including both self-saturation and cross-saturation effects and selecting as state variables the stator currents. The proposed dynamic model is based on an original function between the stator flux and stator current components, and relies on 8 coefficients (fewer than other models in the scientific literature), presenting an interesting physical interpretation. Starting from this approach, both the static and dynamic inductances expressions of the model have been analytically developed, so that the reciprocity conditions for the cross saturation is satisfied. This paper presents also a technique fo…

State variableComputer simulationStatorComputer scienceEstimation theorySpace-vector dynamic model05 social sciences020207 software engineering02 engineering and technologylaw.inventionError functionSettore ING-INF/04 - AutomaticalawControl theoryParameters' estimation0202 electrical engineering electronic engineering information engineering0501 psychology and cognitive sciencesMinificationSynchronous Reluctance Motor (SynRM)Magnetic characteristicsSynchronous reluctance motorSaturation (magnetic)050107 human factors2018 IEEE Energy Conversion Congress and Exposition (ECCE)
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