Search results for "probability"

showing 10 items of 3417 documents

Stability under influence of noise with regulated periodicity

2009

A very simple stochastic differential equation with quasi‐periodical multiplicative noise is investigated analytically. For fixed noise intensity the system can be stable at high noise periodicity and unstable at low noise periodicity.

Stochastic differential equationsymbols.namesakeStochastic resonanceGaussian noiseQuantum mechanicsQuantum noiseMathematical analysissymbolsShot noiseStability (probability)Multiplicative noiseNoise (radio)Mathematics
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Interdependence Between Tool Fracture and Wear

1985

Wear and fracture are the main causes of tool scrapping. However fracture plays a major role for increasing values of the hardness and brittleness of tool materials or when low-cobalt tungsten carbides are used or in interrupted cutting conditions where it is the most relevant factor for tool scrapping. In order to obtain the optimal values of the cutting speed both these factors should be considered. The hypothesis of stochastic independence among them simplifies the mathematical formulation of the optimization problem; but experimental investigations do not agree with this assumption and, as a matter of fact, the probability density function of tool fracture results to be dependent on the…

Stochastic independenceOptimization problemBrittlenessComputer scienceMechanical EngineeringMetallurgyFracture (geology)Mechanical engineeringProbability density functionIndustrial and Manufacturing EngineeringTool materialCIRP Annals
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Spatio-temporal behaviour of the deep chlorophyll maximum in Mediterranean Sea: Development of a stochastic model for picophytoplankton dynamics

2013

In this paper, by using a stochastic reaction-diffusion-taxis model, we analyze the picophytoplankton dynamics in the basin of the Mediterranean Sea, characterized by poorly mixed waters. The model includes intraspecific competition of picophytoplankton for light and nutrients. The multiplicative noise sources present in the model account for random fluctuations of environmental variables. Phytoplankton distributions obtained from the model show a good agreement with experimental data sampled in two different sites of the Sicily Channel. The results could be extended to analyze data collected in different sites of the Mediterranean Sea and to devise predictive models for phytoplankton dynam…

Stochastic modellingFOS: Physical sciencesStructural basinBiologyRandom processe01 natural sciencesIntraspecific competitionMediterranean sea0103 physical sciencesPhytoplanktonMarine ecosystemSpatial ecologyMarine ecosystem14. Life underwaterQuantitative Biology - Populations and Evolution010306 general physicsPhytoplankton dynamic010301 acousticsEcology Evolution Behavior and SystematicsDeep chlorophyll maximumEcologyEcological ModelingPopulations and Evolution (q-bio.PE)Spatial ecology; Marine ecosystems; Phytoplankton dynamics; Deep chlorophyll maximum; Random processes; Stochastic differential equationsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Oceanography13. Climate actionPhysics - Data Analysis Statistics and ProbabilityFOS: Biological sciencesSpatial ecologyStochastic differential equationsDeep chlorophyll maximumData Analysis Statistics and Probability (physics.data-an)
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A non-homogeneous Poisson based model for daily rainfall data

2007

In this paper we report some results of the application of a new stochastic model applied to rainfall daily data. The Poisson models, characterized only by the expected rate of events (impulse occurrences, that is the mean number of impulses per unit time) and the assigned probability distribution of the phenomenon magnitude, do not take into consideration the datum regarding the duration of the occurrences, that is fundamental from a hydrological point of view. In order to describe the phenomenon in a way more adherent to its physical nature, we propose a new model simple and manageable. This model takes into account another random variable, representing the duration of the rainfall due to…

Stochastic modellingSettore SECS-S/02 - Statistica Per La Ricerca Sperimentale E TecnologicaGeodetic datumConfidence Region Daily Rainfall Data Linear Stochastic Differential Equation Poisson White Noise Probabilistic Engineer MechanicsImpulse (physics)Poisson distributionsymbols.namesakeNon homogeneousStatisticssymbolsProbability distributionSettore ICAR/08 - Scienza Delle CostruzioniRandom variableConfidence regionMathematics
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Stochastic Differential Equations

2020

Stochastic differential equations describe the time evolution of certain continuous n-dimensional Markov processes. In contrast with classical differential equations, in addition to the derivative of the function, there is a term that describes the random fluctuations that are coded as an Ito integral with respect to a Brownian motion. Depending on how seriously we take the concrete Brownian motion as the driving force of the noise, we speak of strong and weak solutions. In the first section, we develop the theory of strong solutions under Lipschitz conditions for the coefficients. In the second section, we develop the so-called (local) martingale problem as a method of establishing weak so…

Stochastic partial differential equationExamples of differential equationsStochastic differential equationWeak solutionApplied mathematicsMartingale (probability theory)Malliavin calculusNumerical partial differential equationsIntegrating factorMathematics
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Einstein-Smoluchowsky equation handled by complex fractional moments

2014

In this paper the response of a non linear half oscillator driven by α-stable white noise in terms of probability density function (PDF) is investigated. The evolution of the PDF of such a system is ruled by the so called Einstein-Smoluchowsky equation involving, in the diffusive term, the Riesz fractional derivative. The solution is obtained by the use of complex fractional moments of the PDF, calculated with the aid of Mellin transform operator. It is shown that solution can be found for various values of stability index α and for any nonlinear function of the drift term in the stochastic differential equation.

Stochastic partial differential equationNonlinear systemStochastic differential equationMellin transformDifferential equationOperator (physics)Mathematical analysisProbability density functiona-stable white noise Nonlinear systems Einstein-Smoluchowsky equation Complex fractional momentsFractional calculusMathematics
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Exact stationary solution for a class of non-linear systems driven by a non-normal delta-correlated process

1995

In this paper the exact stationary solution in terms of probability density function for a restricted class of non-linear systems under both external and parametric non-normal delta-correlated processes is presented. This class has been obtained by imposing a given probability distribution and finding the corresponding dynamical system which satisfies the modified Fokker-Planck equation. The effectiveness of the results has been verified by means of a Monte Carlo simulation.

Stochastic processApplied MathematicsMechanical EngineeringMonte Carlo methodProbability density functionStationary sequenceDynamical systemMechanics of MaterialsApplied mathematicsProbability distributionFokker–Planck equationStatistical physicsMathematicsParametric statisticsInternational Journal of Non-Linear Mechanics
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THE ROLE OF UNBOUNDED TIME-SCALES IN GENERATING LONG-RANGE MEMORY IN ADDITIVE MARKOVIAN PROCESSES

2013

Any additive stationary and continuous Markovian process described by a Fokker–Planck equation can also be described in terms of a Schrödinger equation with an appropriate quantum potential. By using such analogy, it has been proved that a power-law correlated stationary Markovian process can stem from a quantum potential that (i) shows an x-2 decay for large x values and (ii) whose eigenvalue spectrum admits a null eigenvalue and a continuum part of positive eigenvalues attached to it. In this paper we show that such two features are both necessary. Specifically, we show that a potential with tails decaying like x-μ with μ < 2 gives rise to a stationary Markovian process which is not p…

Stochastic processGeneral MathematicsAutocorrelationNull (mathematics)Mathematical analysisSpectrum (functional analysis)Quantum potentialstochastic processes survival probabilityGeneral Physics and AstronomyMarkov processStochastic processeSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Schrödinger equationsymbols.namesakelong range correlationsymbolsEigenvalues and eigenvectorsMathematicsFluctuation and Noise Letters
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Stochastic seismic analysis of multidegree of freedom systems

1984

Abstract A unconditionally stable step-by-step procedure is proposed to evaluate the mean square response of a linear system with several degrees of freedom, subjected to earthquake ground motion. A non-stationary modulated random process, obtained as the product of a deterministic time envelope function and a stationary noise, is used to simulate earthquake acceleration. The accuracy of the procedure and its extension to nonlinear systems are discussed. Numerical examples are given for a hysteretic system, a duffing oscillator and a linear system with several degrees of freedom.

Stochastic processMathematical analysisLinear systemDegrees of freedom (statistics)stochastic analysisDuffing equationAcceleration (differential geometry)earthquakes; probability theory; stochastic analysisSeismic analysisNonlinear systemEarthquake simulationControl theoryprobability theoryearthquakesCivil and Structural EngineeringMathematics
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Noise-enhanced propagation in a dissipative chain of triggers

2002

International audience; We study the influence of spatiotemporal noise on the propagation of square waves in an electrical dissipative chain of triggers. By numerical simulation, we show that noise plays an active role in improving signal transmission. Using the Signal to Noise Ratio at each cell, we estimate the propagation length. It appears that there is an optimum amount of noise that maximizes this length. This specific case of stochastic resonance shows that noise enhances propagation.

Stochastic resonanceAcousticsnoise enhanced propagation01 natural sciencesNoise (electronics)[ PHYS.PHYS.PHYS-DATA-AN ] Physics [physics]/Physics [physics]/Data Analysis Statistics and Probability [physics.data-an]010305 fluids & plasmasnonlinear dynamicsSignal-to-noise ratio[NLIN.NLIN-PS]Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS]Control theory0103 physical sciencesPhase noise[ NLIN.NLIN-PS ] Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS]stochastic resonance010306 general physicsEngineering (miscellaneous)PhysicsComputer simulationApplied MathematicsQuantum noise[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsNonlinear systemModeling and SimulationDissipative system[PHYS.PHYS.PHYS-DATA-AN]Physics [physics]/Physics [physics]/Data Analysis Statistics and Probability [physics.data-an]
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