Search results for "impulse"

showing 10 items of 159 documents

On the dynamics of non-local fractional viscoelastic beams under stochastic agencies

2018

Abstract Non-local viscoelasticity is a subject of great interest in the context of non-local theories. In a recent study, the authors have proposed a non-local fractional beam model where non-local effects are represented as viscoelastic long-range volume forces and moments, exchanged by non-adjacent beam segments depending on their relative motion, while local effects are modelled by elastic classical stress resultants. Long-range interactions have been given a fractional constitutive law, involving the Caputo's fractional derivative. This paper introduces a comprehensive numerical approach to calculate the stochastic response of the non-local fractional beam model under Gaussian white no…

Materials scienceDiscretization02 engineering and technologyWhite noiseIndustrial and Manufacturing Engineering0203 mechanical engineeringFractional viscoelasticityComposite materialImpulse responseNon local Timoshenko beamMechanical EngineeringMathematical analysisEquations of motionWhite noise021001 nanoscience & nanotechnologyPhysics::History of PhysicsNon local Timoshenko beam; Fractional viscoelasticity; White noise; State variable expansionFractional calculusNumerical integration020303 mechanical engineering & transportsMechanics of MaterialsStress resultantsFrequency domainCeramics and CompositesState variable expansionSettore ICAR/08 - Scienza Delle CostruzioniFractional viscoelasticity Non local Timoshenko beam State variable expansion White noise0210 nano-technologyNon local Timoshenko beam Fractional viscoelasticity White noise State variable expansionComposites Part B: Engineering
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Optical sectioning with a Wiener-like filter in Fourier integral imaging microscopy

2018

Non-scanning, single-shot, 3D integral microscopy with optical sectioning is presented. The method is based on the combination of Fourier-mode integral microscopy with a 3D deconvolution technique. Specifically, the refocused volume provided by a regular back-projection algorithm is 3D deconvolved with a synthetic 3D impulse response function that takes into account the number and positions of the elemental images. The use of this hybrid technique provides a stack of true-color depth-refocused images with significant gain of optical sectioning. The stack can be used, among other applications, to inspect inside the thick microscope specimen, to calculate collections of perspective views wit…

Materials scienceMicroscopePhysics and Astronomy (miscellaneous)Optical sectioning02 engineering and technology01 natural scienceslaw.invention010309 opticssymbols.namesakeOpticslaw0103 physical sciencesMicroscopyAngular resolutionFourier Anàlisi deImage resolutionImpulse responsebusiness.industryÒptica021001 nanoscience & nanotechnologyMicroscòpiaFourier transformsymbolsDeconvolution0210 nano-technologybusiness
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High power impulse magnetron sputtering of Zn/Al target in an Ar and Ar/O2 atmosphere: The study of sputtering process and AZO films

2019

Financial support provided by Scientific Research Project for Students and Young Researchers Nr. SJZ/2017/4 realised at the Institute of Solid State Physics, University of Latvia is greatly acknowledged.

Materials scienceReactive sputteringAnalytical chemistryAl (AZO) films [ZnO]02 engineering and technology7. Clean energy01 natural sciencesSputteringElectrical resistivity and conductivity0103 physical sciencesMaterials ChemistryTransmittance:NATURAL SCIENCES:Physics [Research Subject Categories]Thin filmPower density010302 applied physicsPulse durationHiPIMSSurfaces and InterfacesGeneral ChemistryPartial pressure021001 nanoscience & nanotechnologyCondensed Matter PhysicsSurfaces Coatings and FilmsSustained self-sputteringHigh-power impulse magnetron sputtering0210 nano-technologyRoom temperature depositionSurface and Coatings Technology
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Non-linear systems under parametric white noise input: digital simulation and response

2005

Abstract Monte Carlo technique is constituted of three steps. Therefore, improving such technique in practice means, improving the procedure used in one of the three following steps: (i) sample paths of the stochastic input process, (ii) calculation of the outputs corresponding to the generated input samples by using methods of classical dynamics and (iii) estimating statistics of the output process from sample outputs related to the previous step. For linear and non-linear systems driven by parametric impulsive inputs such as normal or non-normal white noises, a general integration method requires a considerable reduction of the integration step when the impulse occurs, treating the impuls…

Mathematical optimizationApplied MathematicsMechanical EngineeringMonte Carlo methodα-stable white noiseParametric impulseWhite noiseImpulse (physics)Poissonian white noiseWindow functionα-stable white noise; Normal white noise; Parametric impulse; Poissonian white noiseNonlinear systemMechanics of MaterialsMonte Carlo integrationQuasi-Monte Carlo methodAlgorithmParametric statisticsMathematicsNormal white noise
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Explicit Recursive and Adaptive Filtering in Reproducing Kernel Hilbert Spaces

2014

This brief presents a methodology to develop recursive filters in reproducing kernel Hilbert spaces. Unlike previous approaches that exploit the kernel trick on filtered and then mapped samples, we explicitly define the model recursivity in the Hilbert space. For that, we exploit some properties of functional analysis and recursive computation of dot products without the need of preimaging or a training dataset. We illustrate the feasibility of the methodology in the particular case of the $\gamma$ -filter, which is an infinite impulse response filter with controlled stability and memory depth. Different algorithmic formulations emerge from the signal model. Experiments in chaotic and elect…

Mathematical optimizationComputer Networks and Communications02 engineering and technologyautoregressive and moving-averagekernel methodssymbols.namesakeArtificial Intelligence0202 electrical engineering electronic engineering information engineeringKernel adaptive filterInfinite impulse responseMathematicsfilterrecursiveHilbert space020206 networking & telecommunicationsFilter (signal processing)AdaptiveComputer Science ApplicationsAdaptive filterKernel methodKernel (statistics)symbols020201 artificial intelligence & image processingAlgorithmSoftwareReproducing kernel Hilbert spaceIEEE Transactions on Neural Networks and Learning Systems
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Robust control of uncertain multi-inventory systems via linear matrix inequality

2008

We consider a continuous time linear multi inventory system with unknown demands bounded within ellipsoids and controls bounded within ellipsoids or polytopes. We address the problem of "-stabilizing the inventory since this implies some reduction of the inventory costs. The main results are certain conditions under which "-stabilizability is possible through a saturated linear state feedback control. All the results are based on a Linear Matrix Inequalities (LMIs) approach and on some recent techniques for the modeling and analysis of polytopic systems with saturations.

Mathematical optimizationLinear Matrix InequalitiesPolytopeDynamical Systems (math.DS)stock control93xxcontinuous systems linear matrix inequalities linear systems manufacturing systems robust control state feedback stock control uncertain systemsimpulse control inventory control hybrid systemsSettore ING-INF/04 - AutomaticaControl theoryFOS: Mathematicsmanufacturing systemsMathematics - Dynamical Systemslinear matrix inequalitiesstate feedbackTime complexityMathematics - Optimization and ControlInventory systemsMathematicsInventory controlLinear Matrix Inequalities; Inventory systemsLinear systemlinear systemsLinear matrix inequality93Cxx;93xxLinearity93Cxxhybrid systemsEllipsoidComputer Science Applicationsimpulse control; inventory control; hybrid systemsuncertain systemsControl and Systems EngineeringOptimization and Control (math.OC)Control systemBounded functioncontinuous systemsPerpetual inventorycontinuous systems; linear matrix inequalities; linear systems; manufacturing systems; robust control; state feedback; stock control; uncertain systemsinventory controlRobust controlSettore MAT/09 - Ricerca Operativarobust controlimpulse control
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Patch-Based Image Denoising Model for Mixed Gaussian Impulse Noise Using L1 Norm

2017

Image denoising is the classes of technique used to free the image form the noise. The noise in the image may be added during the observation process due to the improper setting of the camera lance, low-resolution camera, cheap, and low-quality sensors, etc. Noise in the image may also be added during the image restoration, image transmission through the transmission media. To obtain required information from image, image must be noise free, i.e., high-frequency details must be present in the image. There are number of applications where image denoising is needed such as remote location detection, computer vision, computer graphics, video surveillance, etc. In last two decades, numbers of m…

Mathematical optimizationbusiness.industryComputer scienceGaussianComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONTransmission mediumImpulse (physics)Non-local meansImpulse noiseComputer graphicssymbols.namesakeGaussian noiseComputer Science::Computer Vision and Pattern RecognitionsymbolsComputer visionArtificial intelligencebusinessImage restoration
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Explicit recursivity into reproducing kernel Hilbert spaces

2011

This paper presents a methodology to develop recursive filters in reproducing kernel Hilbert spaces (RKHS). Unlike previous approaches that exploit the kernel trick on filtered and then mapped samples, we explicitly define model recursivity in the Hilbert space. The method exploits some properties of functional analysis and recursive computation of dot products without the need of pre-imaging. We illustrate the feasibility of the methodology in the particular case of the gamma-filter, an infinite impulse response (IIR) filter with controlled stability and memory depth. Different algorithmic formulations emerge from the signal model. Experiments in chaotic and electroencephalographic time se…

Mathematical optimizationgamma filterHilbert spaceDot productFilter (signal processing)pre-imagefunctional analysissymbols.namesakekernel methodsKernel methodKernel (statistics)symbolsRecursive filterInfinite impulse responseAlgorithmMathematicsReproducing kernel Hilbert spaceRecursive filter
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Therapeutic Drug Monitoring of Kidney Transplant Recipients Using Profiled Support Vector Machines

2007

This paper proposes a twofold approach for therapeutic drug monitoring (TDM) of kidney recipients using support vector machines (SVMs), for both predicting and detecting Cyclosporine A (CyA) blood concentrations. The final goal is to build useful, robust, and ultimately understandable models for individualizing the dosage of CyA. We compare SVMs with several neural network models, such as the multilayer perceptron (MLP), the Elman recurrent network, finite/infinite impulse response networks, and neural network ARMAX approaches. In addition, we present a profile-dependent SVM (PD-SVM), which incorporates a priori knowledge in both tasks. Models are compared numerically, statistically, and in…

Mean squared errorComputer sciencecomputer.software_genreBlood concentrationmedicineElectrical and Electronic EngineeringInfinite impulse responseKidney transplantationArtificial neural networkmedicine.diagnostic_testbusiness.industryPattern recognitionmedicine.diseaseComputer Science ApplicationsHuman-Computer InteractionSupport vector machineNoiseAutoregressive modelControl and Systems EngineeringTherapeutic drug monitoringMultilayer perceptronData miningArtificial intelligencebusinesscomputerSoftwareInformation SystemsIEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)
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Direct evaluation of jumps for nonlinear systems under external and multiplicative impulses

2015

In this paper the problem of the response evaluation of nonlinear systems under multiplicative impulsive input is treated. Such systems exhibit a jump at each impulse occurrence, whose value cannot be predicted through the classical differential calculus. In this context here the correct jump evaluation of nonlinear systems is obtained in closed form for two general classes of nonlinear multiplicative functions. Analysis has been performed to show the different typical behaviors of the response, which in some cases could diverge or converge to zero instantaneously, depending on the amplitude of the Dirac's delta.

Mechanical EngineeringMultiplicative functionMathematical analysisAerospace Engineering020101 civil engineeringDifferential calculus02 engineering and technologyImpulse (physics)0201 civil engineeringNonlinear system020303 mechanical engineering & transportsAmplitude0203 mechanical engineeringMechanics of MaterialsControl theoryAutomotive EngineeringNonlinear systemJumpGeneral Materials ScienceDirac's deltaDirect evaluationSettore ICAR/08 - Scienza Delle Costruzionimultiplicative impulsive inputMathematicsJournal of Vibration and Control
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