Search results for "Names"

showing 10 items of 6843 documents

An analysis of Ralston's quadrature

1987

Ralston's quadrature achieves higher accuracy in composite rules than analogous Newton-Cotes or Gaussian formulas. His rules are analyzed, computable expressions for the weights and knots are given, and a more suitable form of the remainder is derived.

Computational Mathematicssymbols.namesakeApplied MathematicsGaussianNumerical analysissymbolsApplied mathematicsRemainderAlgorithmGauss–Kronrod quadrature formulaMathematicsQuadrature (mathematics)Numerische Mathematik
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Residuenabschätzung für Polynom-Nullstellen mittels Lagrange-Interpolation

1970

If, for each zero of a polynomial, an approximation is known, estimates for the errors of these approximations are given, based on the evaluation of the polynomial at these points. The procedure can be carried over to the case of multiple roots and root clusters using derivatives up to the orderk - 1, wherek is the multiplicity of the cluster.

Computational Mathematicssymbols.namesakeApplied MathematicsNumerical analysisMathematical analysisLagrange polynomialsymbolsApplied mathematicsMultiplicity (mathematics)Wilkinson's polynomialMathematicsNumerische Mathematik
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On the Computational Complexity of Binary and Analog Symmetric Hopfield Nets

2000

We investigate the computational properties of finite binary- and analog-state discrete-time symmetric Hopfield nets. For binary networks, we obtain a simulation of convergent asymmetric networks by symmetric networks with only a linear increase in network size and computation time. Then we analyze the convergence time of Hopfield nets in terms of the length of their bit representations. Here we construct an analog symmetric network whose convergence time exceeds the convergence time of any binary Hopfield net with the same representation length. Further, we prove that the MIN ENERGY problem for analog Hopfield nets is NP-hard and provide a polynomial time approximation algorithm for this p…

Computational complexity theoryCognitive NeuroscienceComputationBinary numberHopfield networkTuring machinesymbols.namesakeRecurrent neural networkArts and Humanities (miscellaneous)Convergence (routing)symbolsTime complexityAlgorithmMathematicsNeural Computation
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Descriptive Complexity, Lower Bounds and Linear Time

1999

This paper surveys two related lines of research: Logical characterizations of (non-deterministic) linear time complexity classes, and non-expressibility results concerning sublogics of existential second-order logic. Starting from Fagin’s fundamental work there has been steady progress in both fields with the effect that the weakest logics that are used in characterizations of linear time complexity classes are closely related to the strongest logics for which inexpressibility proofs for concrete problems have been obtained. The paper sketches these developments and highlights their connections as well as the obstacles that prevent us from closing the remaining gap between both kinds of lo…

Computational complexity theoryComputer scienceDescriptive complexity theoryMathematical proofCombinatoricsTuring machinesymbols.namesakeTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESRegular languageCalculusComplexity classsymbolsUnary functionTime complexity
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Population Monte Carlo Schemes with Reduced Path Degeneracy

2017

Population Monte Carlo (PMC) algorithms are versatile adaptive tools for approximating moments of complicated distributions. A common problem of PMC algorithms is the so-called path degeneracy; the diversity in the adaptation is endangered due to the resampling step. In this paper we focus on novel population Monte Carlo schemes that present enhanced diversity, compared to the standard approach, while keeping the same implementation structure (sample generation, weighting and resampling). The new schemes combine different weighting and resampling strategies to reduce the path degeneracy and achieve a higher performance at the cost of additional low computational complexity cost. Computer si…

Computational complexity theoryMonte Carlo methodApproximation algorithm020206 networking & telecommunications02 engineering and technology01 natural sciencesStatistics::ComputationWeighting010104 statistics & probabilitysymbols.namesake[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingGaussian noiseResamplingPath (graph theory)0202 electrical engineering electronic engineering information engineeringsymbols0101 mathematicsDegeneracy (mathematics)Algorithm[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingComputingMilieux_MISCELLANEOUS
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A Variational Approach for Denoising Hyperspectral Images Corrupted by Poisson Distributed Noise

2014

Poisson distributed noise, such as photon noise is an important noise source in multi- and hyperspectral images. We propose a variational based denoising approach, that accounts the vectorial structure of a spectral image cube, as well as the poisson distributed noise. For this aim, we extend an approach for monochromatic images, by a regularisation term, that is spectrally and spatially adaptive and preserves edges. In order to take the high computational complexity into account, we derive a Split Bregman optimisation for the proposed model. The results show the advantages of the proposed approach compared to a marginal approach on synthetic and real data.

Computational complexity theorybusiness.industryNoise reductionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONHyperspectral imagingPoisson distributionTerm (time)symbols.namesakeNoiseComputer Science::Computer Vision and Pattern RecognitionsymbolsComputer visionArtificial intelligenceMonochromatic colorCubebusinessAlgorithmMathematics
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Stochastic analysis of dynamical systems with delayed control forces

2006

Abstract Reduction of structural vibration in actively controlled dynamical system is usually performed by means of convenient control forces dependent of the dynamic response. In this paper the existent studies will be extended to dynamical systems subjected to non-normal delta-correlated random process with delayed control forces. Taylor series expansion of the control forces has been introduced and the statistics of the dynamical response have been obtained by means of the extended Ito differential rule. Numerical application provided shows the capabilities of the proposed method to analyze stochastic dynamic systems with delayed actions under delta-correlated process contrasting statist…

Computational methods in classical mechanicNumerical AnalysisDynamical systems theoryStochastic processApplied MathematicsStochastic analysis methodsProcess (computing)General linear dynamical systemDynamical systemLinear dynamical systemsymbols.namesakeControl theoryModeling and SimulationTaylor seriessymbolsNonlinear dynamics and nonlinear dynamical systemDifferential (infinitesimal)Reduction (mathematics)MathematicsCommunications in Nonlinear Science and Numerical Simulation
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GAMIT - A Fading-Gaussian Activation Model of Interval-Timing: Unifying Prospective and Retrospective Time Estimation

2014

Two recent findings constitute a serious challenge for all existing models of interval timing. First, Hass and Hermann (2012) have shown that only variance-based processes will lead to the scalar growth of error that is characteristic of human time judgments. Secondly, a major meta-review of over one hundred studies of participants’ judgments of interval duration (Block et al., 2010) reveals a striking interaction between the way in which temporal judgments are queried (i.e., retrospectively or prospectively) and cognitive load. For retrospective time judgments, estimates under high cognitive load are longer than under low cognitive load. For prospective judgments, the reverse pattern holds…

Computational modelbusiness.industryGaussianScalar (physics)Variance (accounting)Interval (mathematics)behavioral disciplines and activitieshumanitiessymbols.namesakeStatisticssymbolsFadingSpreading activationArtificial intelligencebusinessPsychologyCognitive load
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Efficient parallel computations of flows of arbitrary fluids for all regimes of Reynolds, Mach and Grashof numbers

2002

This paper presents a unified numerical method able to address a wide class of fluid flow problems of engineering interest. Arbitrary fluids are treated specifying totally arbitrary equations of state, either in analytical form or through look‐up tables. The most general system of the unsteady Navier–Stokes equations is integrated with a coupled implicit preconditioned method. The method can stand infinite CFL number and shows the efficiency of a quasi‐Newton method independent of the multi‐block partitioning on parallel machines. Computed test cases ranging from inviscid hydrodynamics, to natural convection loops of liquid metals, and to supersonic gasdynamics, show a solution efficiency i…

Computations Flow FluidNatural convectionApplied MathematicsMechanical EngineeringNumerical analysisCourant–Friedrichs–Lewy conditionGrashof numberMechanicsComputer Science ApplicationsPhysics::Fluid Dynamicssymbols.namesakeClassical mechanicsMach numberMechanics of MaterialsInviscid flowFluid dynamicssymbolsSupersonic speedSettore ING-IND/19 - Impianti NucleariMathematicsInternational Journal of Numerical Methods for Heat & Fluid Flow
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A Random Trajectory Approach for the Development of Nonstationary Channel Models Capturing Different Scales of Fading

2017

This paper introduces a new approach to developing stochastic nonstationary channel models, the randomness of which originates from a random trajectory of the mobile station (MS) rather than from the scattering area. The new approach is employed by utilizing a random trajectory model based on the primitives of Brownian fields (BFs), whereas the position of scatterers can be generated from an arbitrarily 2-D distribution function. The employed trajectory model generates random paths along which the MS travels from a given starting point to a fixed predefined destination point. To capture the path loss, the gain of each multipath component is modeled by a negative power law applied to the tra…

Computer Networks and CommunicationsComputer scienceAerospace Engineering020302 automobile design & engineering020206 networking & telecommunications02 engineering and technologysymbols.namesakeFading distribution0203 mechanical engineeringChannel state informationAutomotive Engineering0202 electrical engineering electronic engineering information engineeringElectronic engineeringTrajectorysymbolsPath lossFadingStatistical physicsElectrical and Electronic EngineeringPower delay profileGaussian processRandomnessComputer Science::Information Theory
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