Search results for "Probability."

showing 10 items of 3396 documents

Stability analysis of neutral systems with mixed time-varying delays and nonlinear perturbations

2009

In this paper, the problem of stability analysis for a class of neutral systems with mixed time-varying neutral, discrete and distributed delays and nonlinear perturbations are addressed. By introducing a novel Lyapunov-Krasovskii functional and combining the descriptor model transformation, the Leibniz-Newton formula, some free weighting matrices and a suitable change of variables, new sufficient conditions are established for the stability of the considered system, which are neutral-delay-dependent, discrete-delay-range-dependent and distributed-delay-dependent. The conditions are presented in terms of linear matrix inequalities (LMIs) and can be easily solved by existing convex optimizat…

Change of variablesControl theoryControl and Systems EngineeringModel transformationConvex optimizationNonlinear perturbationsLinear matrixNeutral systemsStability (probability)computerWeightingMathematicscomputer.programming_language
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Aggregate Behavior and Microdata

2004

Abstract It is shown how one can effectively use microdata in modelling the change over time in an aggregate (e.g. mean consumption expenditure) of a large and heterogeneous population. The starting point of our aggregation analysis is a specification of explanatory variables on the micro-level. Typically, some of these explanatory variables are observable and others are unobservable. Based on certain hypotheses on the evolution over time of the joint distributions across the population of these explanatory variables we derive a decomposition of the change in the aggregate which allows a partial analysis: to isolate and to quantify the effect of a change in the observable explanatory variab…

Change over timeEconomics and Econometricseducation.field_of_studyPopulationAggregate behaviorMicrodata (statistics)jel:E21Observablejel:D12UnobservableHeterogeneous populationJoint probability distributionStatisticsEconometricsEconomicseducationFinance
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An Adaptive Combination of Dark and Bright Channel Priors for Single Image Dehazing

2017

Dehazing methods based on prior assumptions derived from statistical image properties fail when these properties do not hold. This is most likely to happen when the scene contains large bright areas, such as snow and sky, due to the ambiguity between the airlight and the depth information. This is the case for the popular dehazing method Dark Channel Prior. In order to improve its performance, the authors propose to combine it with the recent multiscale STRESS, which serves to estimate Bright Channel Prior. Visual and quantitative evaluations show that this method outperforms Dark Channel Prior and competes with the most robust dehazing methods, since it separates bright and dark areas and …

Channel (digital image)business.industryComputer science020206 networking & telecommunications[ INFO.INFO-GR ] Computer Science [cs]/Graphics [cs.GR][ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingAstrophysics::Cosmology and Extragalactic Astrophysics02 engineering and technologyGeneral Chemistry[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]Atomic and Molecular Physics and OpticsComputer Science ApplicationsElectronic Optical and Magnetic Materials[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Computer graphics (images)[ INFO.INFO-TI ] Computer Science [cs]/Image ProcessingPrior probability0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionArtificial intelligenceSingle imagebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingJournal of Imaging Science and Technology
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On the statistical properties of the capacity of OSTBC Nakagami-lognormal MIMO channels

2010

This article presents a thorough statistical analysis of the capacity of orthogonal space-time block coded (OSTBC) Nakagami-lognormal (NLN) multiple-input multipleoutput (MIMO) channels. The NLN channel model allows to study the joint effects of fast fading and shadowing on the statistical properties of the channel capacity. We have derived exact analytical expressions for the probability density function (PDF), cumulative distribution function (CDF), level-crossing rate (LCR), and average duration of fades (ADF) of the capacity of NLN MIMO channels. It is observed that an increase in the MIMO dimension1 or a decrease in the severity of fading results in an increase in the mean channel capa…

Channel capacityCumulative distribution functionMIMOLog-normal distributionStatisticsFadingNakagami distributionProbability density functionStandard deviationComputer Science::Information TheoryMathematics2010 4th International Conference on Signal Processing and Communication Systems
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Is there an absolutely continuous random variable with equal probability density and cumulative distribution functions in its support? Is it unique? …

2014

This paper inquires about the existence and uniqueness of a univariate continuous random variable for which both cumulative distribution and density functions are equal and asks about the conditions under which a possible extrapolation of the solution to the discrete case is possible. The issue is presented and solved as a problem and allows to obtain a new family of probability distributions. The different approaches followed to reach the solution could also serve to warn about some properties of density and cumulative functions that usually go unnoticed, helping to deepen the understanding of some of the weapons of the mathematical statistician’s arsenal.

Characteristic function (probability theory)Cumulative distribution functionCalculusProbability mass functionProbability distributionApplied mathematicsProbability density functionMoment-generating functionRandom variableLaw of the unconscious statisticianMathematicsInternational Journal of Advanced Statistics and Probability
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On the use of fractional calculus for the probabilistic characterization of random variables

2009

In this paper, the classical problem of the probabilistic characterization of a random variable is re-examined. A random variable is usually described by the probability density function (PDF) or by its Fourier transform, namely the characteristic function (CF). The CF can be further expressed by a Taylor series involving the moments of the random variable. However, in some circumstances, the moments do not exist and the Taylor expansion of the CF is useless. This happens for example in the case of $\alpha$--stable random variables. Here, the problem of representing the CF or the PDF of random variables (r.vs) is examined by introducing fractional calculus. Two very remarkable results are o…

Characteristic function (probability theory)FOS: Physical sciencesAerospace EngineeringMathematics - Statistics TheoryOcean EngineeringProbability density functionComplex order momentStatistics Theory (math.ST)Fractional calculusymbols.namesakeIngenieurwissenschaftenFOS: MathematicsTaylor seriesApplied mathematicsCharacteristic function serieMathematical PhysicsCivil and Structural EngineeringMathematicsGeneralized Taylor serieMechanical EngineeringStatistical and Nonlinear PhysicsProbability and statisticsMathematical Physics (math-ph)Condensed Matter PhysicsFractional calculusFourier transformNuclear Energy and EngineeringPhysics - Data Analysis Statistics and ProbabilitysymbolsFractional calculus; Generalized Taylor series; Complex order moments; Fractional moments; Characteristic function series; Probability density function seriesddc:620Series expansionFractional momentProbability density function seriesSettore ICAR/08 - Scienza Delle CostruzioniRandom variableData Analysis Statistics and Probability (physics.data-an)
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Path integral solution for non-linear system enforced by Poisson White Noise

2008

Abstract In this paper the response in terms of probability density function of non-linear systems under Poisson White Noise is considered. The problem is handled via path integral (PI) solution that may be considered as a step-by-step solution technique in terms of probability density function. First the extension of the PI to the case of Poisson White Noise is derived, then it is shown that at the limit when the time step becomes an infinitesimal quantity the Kolmogorov–Feller (K–F) equation is fully restored enforcing the validity of the approximations made in obtaining the conditional probability appearing in the Chapman Kolmogorov equation (starting point of the PI). Spectral counterpa…

Characteristic function (probability theory)Mechanical EngineeringMathematical analysisFokker-Planck equationAerospace EngineeringConditional probabilityKolmogorov-Feller eqautionOcean EngineeringStatistical and Nonlinear PhysicsProbability density functionWhite noiseCondensed Matter PhysicsPoisson distributionPath Integral Solutionsymbols.namesakeNuclear Energy and EngineeringPath integral formulationsymbolsFokker–Planck equationSettore ICAR/08 - Scienza Delle CostruzioniChapman–Kolmogorov equationCivil and Structural EngineeringMathematicsProbabilistic Engineering Mechanics
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A method for the probabilistic analysis of nonlinear systems

1995

Abstract The probabilistic description of the response of a nonlinear system driven by stochastic processes is usually treated by means of evaluation of statistical moments and cumulants of the response. A different kind of approach, by means of new quantities here called Taylor moments, is proposed. The latter are the coefficients of the Taylor expansion of the probability density function and the moments of the characteristic function too. Dual quantities with respect to the statistical cumulants, here called Taylor cumulants, are also introduced. Along with the basic scheme of the method some illustrative examples are analysed in detail. The examples show that the proposed method is an a…

Characteristic function (probability theory)Stochastic processMechanical EngineeringAerospace EngineeringOcean EngineeringStatistical and Nonlinear PhysicsProbability density functionCondensed Matter Physicssymbols.namesakeNonlinear systemNuclear Energy and EngineeringTaylor seriessymbolsCalculusApplied mathematicsProbabilistic analysis of algorithmsCumulantCivil and Structural EngineeringMathematicsTaylor expansions for the moments of functions of random variables
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Probabilistic response of nonlinear systems under combined normal and Poisson white noise via path integral method

2011

In this paper the response in terms of probability density function of nonlinear systems under combined normal and Poisson white noise is considered. The problem is handled via a Path Integral Solution (PIS) that may be considered as a step-by-step solution technique in terms of probability density function. A nonlinear system under normal white noise, Poissonian white noise and under the superposition of normal and Poisson white noise is performed through PIS. The spectral counterpart of the PIS, ruling the evolution of the characteristic functions is also derived. It is shown that at the limit when the time step becomes an infinitesimal quantity an equation ruling the evolution of the pro…

Characteristic function (probability theory)Stochastic resonanceMechanical EngineeringMathematical analysisShot noiseAerospace EngineeringOcean EngineeringStatistical and Nonlinear PhysicsProbability density functionWhite noiseCondensed Matter PhysicsPoisson distributionsymbols.namesakeNormal white noise Poisonian white noise combined white noisesAdditive white Gaussian noiseNuclear Energy and EngineeringGaussian noisesymbolsSettore ICAR/08 - Scienza Delle CostruzioniCivil and Structural EngineeringMathematics
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Critical point and coexistence curve properties of the Lennard-Jones fluid: A finite-size scaling study

1995

Monte Carlo simulations within the grand canonical ensemble are used to explore the liquid-vapour coexistence curve and critical point properties of the Lennard-Jones fluid. Attention is focused on the joint distribution of density and energy fluctuations at coexistence. In the vicinity of the critical point, this distribution is analysed using mixed-field finite-size scaling techniques aided by histogram reweighting methods. The analysis yields highly accurate estimates of the critical point parameters, as well as exposing the size and character of corrections to scaling. In the sub-critical coexistence region the density distribution is obtained by combining multicanonical simulations wit…

Chemical Physics (physics.chem-ph)BinodalCondensed Matter (cond-mat)Monte Carlo methodFOS: Physical sciencesCondensed MatterGrand canonical ensembleTricritical pointCritical point (thermodynamics)Joint probability distributionHistogramPhysics - Chemical PhysicsStatistical physicsScalingMathematics
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