Search results for "Stationary process"

showing 10 items of 16 documents

Role of conditional probability in multiscale stationary markovian processes.

2010

The aim of the paper is to understand how the inclusion of more and more time-scales into a stochastic stationary Markovian process affects its conditional probability. To this end, we consider two Gaussian processes: (i) a short-range correlated process with an infinite set of time-scales bounded from below, and (ii) a power-law correlated process with an infinite and unbounded set of time-scales. For these processes we investigate the equal position conditional probability P(x,t|x,0) and the mean First Passage Time T(L). The function P(x,t|x,0) can be considered as a proxy of the persistence, i.e. the fact that when a process reaches a position x then it spends some time around that posit…

Continuous-time stochastic processPure mathematicsStationary processStationary distributionStatistical Mechanics (cond-mat.stat-mech)Stochastic processStochastic ProcesseFokker-Plank EquationFOS: Physical sciencesOrnstein–Uhlenbeck processConditional probability distributionSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)CombinatoricsStable processPhysics - Data Analysis Statistics and ProbabilityMarkovian processeFirst-hitting-time modelCondensed Matter - Statistical MechanicsData Analysis Statistics and Probability (physics.data-an)MathematicsPhysical review. E, Statistical, nonlinear, and soft matter physics
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Fractional Spectral Moments for Digital Simulation of Multivariate Wind Velocity Fields

2012

In this paper, a method for the digital simulation of wind velocity fields by Fractional Spectral Moment function is proposed. It is shown that by constructing a digital filter whose coefficients are the fractional spectral moments, it is possible to simulate samples of the target process as superposition of Riesz fractional derivatives of a Gaussian white noise processes. The key of this simulation technique is the generalized Taylor expansion proposed by the authors. The method is extended to multivariate processes and practical issues on the implementation of the method are reported.

FOS: Computer and information sciencesMultivariate wind velocity fieldMultivariate statisticsStatistical Mechanics (cond-mat.stat-mech)Fractional spectral momentRenewable Energy Sustainability and the EnvironmentMechanical EngineeringMathematical analysisFOS: Physical sciencesGeneralized Taylor formWhite noiseFunction (mathematics)Digital simulation of Gaussian stationary processeFractional calculuStatistics - ComputationTransfer functionWind speedFractional calculusSuperposition principleSettore ICAR/08 - Scienza Delle CostruzioniComputation (stat.CO)Condensed Matter - Statistical MechanicsLinear filterCivil and Structural EngineeringMathematics
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A novel exact representation of stationary colored Gaussian processes (fractional differential approach)

2010

A novel representation of functions, called generalized Taylor form, is applied to the filtering of white noise processes. It is shown that every Gaussian colored noise can be expressed as the output of a set of linear fractional stochastic differential equations whose solution is a weighted sum of fractional Brownian motions. The exact form of the weighting coefficients is given and it is shown that it is related to the fractional moments of the target spectral density of the colored noise.

FOS: Computer and information sciencesStatistics and ProbabilityDifferential equationFOS: Physical sciencesGeneral Physics and AstronomyStatistics - ComputationStochastic differential equationsymbols.namesakeSpectral MomentsApplied mathematicsStationary processeGaussian processCondensed Matter - Statistical MechanicsComputation (stat.CO)Mathematical PhysicsMathematicsGeneralized functionStatistical Mechanics (cond-mat.stat-mech)Statistical and Nonlinear PhysicsMathematical Physics (math-ph)White noiseClosed and exact differential formsColors of noiseGaussian noiseFractional CalculuModeling and SimulationsymbolsSettore ICAR/08 - Scienza Delle Costruzioni
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Nonlinear nonviscous hydrodynamical models for charge transport in the framework of extended thermodynamic methods

2002

This paper develops a procedure, based on methods of extended thermodynamics, to design nonlinear hydrodynamical models for charge transport in metals or in semiconductors, neglecting viscous phenomena. Models obtained in this way allow the study of the motion of electric charges in the presence of arbitrary external electric fields and may be useful when one wishes to study phenomena in a neighborhood of a stationary nonequilibrium process: indeed, the drift velocity of the charge gas with respect to the crystal lattice is not regarded as a small parameter.

PhysicsDrift velocityStationary processNon-equilibrium thermodynamicsElectric chargeComputer Science ApplicationsNonlinear systemsymbols.namesakeClassical mechanicsModeling and SimulationElectric fieldLagrange multiplierModelling and SimulationsymbolsBalance equationMathematical and Computer Modelling
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CHANGES OF ELECTRONIC NOISE INDUCED BY OSCILLATING FIELDS IN BULK GaAs SEMICONDUCTORS

2008

A Monte Carlo study of hot-electron intrinsic noise in a n-type GaAs bulk driven by one or two mixed cyclostationary electric fields is presented. The noise properties are investigated by computing the spectral density of velocity fluctuations. An analysis of the noise features as a function of the amplitudes and frequencies of two applied fields is presented. Numerical results show that it is possible to reduce the intrinsic noise. The best conditions to realize this effect are discussed.

PhysicsElectronic noiseCyclostationary processGeneral MathematicsMonte Carlo methodQuantum noiseShot noiseField-mixing conditionGeneral Physics and AstronomySpectral densityNoise (electronics)Settore FIS/03 - Fisica Della MateriaComputational physicsElectric fieldFlicker noiseStatistical physicsMonte Carlo simulationFluctuation and Noise Letters
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Monte Carlo analysis of electronic noise in semiconductors under sub‐terahertz cyclostationary mixed fields

2006

This paper reports the results of Monte Carlo simulations of electronic noise in a GaAs bulk driven by two mixed high-frequency large-amplitude periodic electric fields. Under these conditions, the system response shows some peculiarities in the noise performance, such as a resonant-like enhancement of the spectra near the two frequencies of the applied fields. The relations among the frequency response and the velocity fluctuations as a function of intensities and frequencies of the sub-terahertz mixed excitation fields have been investigated. (© 2006 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

PhysicsFrequency responseCondensed matter physicsTerahertz radiationCyclostationary processElectric fieldMonte Carlo methodCondensed Matter PhysicsNoise (electronics)ExcitationSpectral linephysica status solidi c
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Frequency influence on the hot-electron noise reduction in GaAs operating under periodic signals

2008

A Monte Carlo study of the role of the frequency on the hot-electron intrinsic noise reduction in an n-type GaAs bulk driven by two mixed cyclostationary electric fields is presented. Previous numerical results showed the possibility to reduce the diffusion noise under specific wave-mixing conditions. In this work the variations of the noise properties are investigated by computing and integrating the spectral density of the velocity fluctuations. We found that the effect of reduction of the noise level due to the addition of a second field at twice frequency is almost independent of the frequency.

PhysicsNoise temperatureCondensed matter physicsCyclostationary processNoise reductionNoise spectral densityMonte Carlo methodSemiconducting gallium arsenideGeneral Physics and AstronomySpectral densityVelocity fluctuationSettore FIS/03 - Fisica Della MateriaMonte Carlo methodPeriodic signalSpectral densityNoise generatorElectric fieldNoise abatementNoise (radio)Hot electrons
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A modal approach for the evaluation of the response sensitivity of structural systems subjected to non-stationary random processes

2005

A method for the evaluation of the response sensitivity of both classically and non-classically damped discrete linear structural systems under stochastic actions is presented. The proposed approach requires the following items: (a) a suitable modal expansion of the response; (b) the derivation in analytical form of the equations governing the evolution of the derivatives of the response (the so-called sensitivity equations) with respect to the parameters that define the structural model; (c) an extensive use of the Kronecker algebra for determining the analytical expressions of the sensitivity of the structural response statistics to non-stationary random input processes. Moreover, a step-…

STOCHASTIC SENSITIVITYProcess (engineering)Modal analysisModal analysisStructural systemStochastic responseComputational MechanicsGeneral Physics and Astronomysymbols.namesakeSensitivityControl theoryKronecker deltaApplied mathematicsSensitivity (control systems)DESIGN SENSITIVITYMathematicsCross-correlationStochastic processMechanical EngineeringSensitivity; Modal analysis; Stochastic response; Non stationary processNon stationary processComputer Science ApplicationsSettore ICAR/09 - Tecnica Delle CostruzioniModalMechanics of MaterialsMECHANICSsymbolsSettore ICAR/08 - Scienza Delle CostruzioniDYNAMIC-SYSTEMSComputer Methods in Applied Mechanics and Engineering
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Explicit form of the time operator of a gaussian stationary process

2004

We present the time operator theory in the framework of stationary stochastic processes. The main results of the paper is the derivation of the time operator acting on the Fock space associated with a discrete time gaussian stationary process.

Semi-elliptic operatorStationary processPhysics and Astronomy (miscellaneous)Multiplication operatorGeneral MathematicsMathematical analysisDisplacement operatorOrnstein–Uhlenbeck processStationary sequenceShift operatorMathematicsOrder of integration
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Event signal characterization for disturbance interpretation in power grid

2018

This paper presents the signal processing approach to detect and characterize the physical events that occur in power system using PMUs signals. A small window is applied so that the extracted spectral features belong to a stationary signal. This is based on applying empirical mode decomposition, followed by square root of spectral kurtosis (SRSK) for computation of statistical indices to indicate the event occurrence. Subsequently, features from these events are extracted using mel frequency cepstral coefficients on SRSK. © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/re…

Signal processingWaveletStationary processComputer sciencebusiness.industryKurtosisPattern recognitionMel-frequency cepstrumArtificial intelligencebusinessSignalHilbert–Huang transformEvent (probability theory)
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