Search results for "Nonlinear"

showing 10 items of 3684 documents

Experimental and numerical study of noise effects in a FitzHugh-Nagumo system driven by a biharmonic signal

2013

Using a nonlinear circuit ruled by the FitzHugh-Nagumo equations, we experimentally investigate the combined effect of noise and a biharmonic driving of respective high and low frequency F and f. Without noise, we show that the response of the circuit to the low frequency can be maximized for a critical amplitude B of the high frequency via the effect of Vibrational Resonance (V.R.). We report that under certain conditions on the biharmonic stimulus, white noise can induce V.R. The effects of colored noise on V.R. are also discussed by considering an Ornstein-Uhlenbeck process. All experimental results are confirmed by numerical analysis of the system response.

Stochastic Resonancenoisevibrational Resonance[PHYS.PHYS.PHYS-BIO-PH] Physics [physics]/Physics [physics]/Biological Physics [physics.bio-ph]neural network[NLIN.NLIN-PS] Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS]nonlinear circuits[SPI.TRON] Engineering Sciences [physics]/Electronics
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Stochastic acceleration in generalized squared Bessel processes

2015

We analyze the time behavior of generalized squared Bessel processes, which are useful for modeling the relevant scales of stochastic acceleration problems. These nonstationary stochastic processes obey a Langevin equation with a non-Gaussian multiplicative noise. We obtain the long-time asymptotic behavior of the probability density function for non-Gaussian white and colored noise sources. We find that the functional form of the probability density functions is independent of the statistics of the noise source considered. Theoretical results are in good agreement with those obtained by numerical simulations of the Langevin equation with pulse noise sources.

Stochastic controlGeneralized inverse Gaussian distributionStatistics and ProbabilityMathematical optimizationBessel processexact resultStatistical and Nonlinear Physicsstochastic processes (theory)Noise (electronics)Multiplicative noiseLangevin equationStochastic differential equationColors of noiseStatistical physicsstochastic particle dynamics (theory)Statistics Probability and UncertaintyMathematicsStatistical and Nonlinear Physic
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On stability and dissipativity of stochastic nonlinear systems

2012

Input-to-state stability of nonlinear control system is described in several different manners, and has been a central concept since the equivalences among them were verified. In this paper, a framework of stability and dissipativity for stochastic control systems is constructed on the maximal existence interval of behaviors (states and external inputs), by the aid of stochastic Barbalat lemma and stochastic dissipativity. The main work consists of three aspects. First, input-to-state stability and robust stability are extended to the stochastic case, and several criteria are established. Second, two forms of dissipativity and their criteria are presented. Third, the key relations among the…

Stochastic controlNonlinear systemWork (thermodynamics)Lemma (mathematics)Control theoryStability (learning theory)Interval (mathematics)Nonlinear controlLipschitz continuityMathematics2012 IEEE 51st IEEE Conference on Decision and Control (CDC)
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Ito and Stratonovich integrals for delta-correlated processes

1993

Abstract In this paper the generalization of the Itd and Stratonovich integrals for the case of non-linear systems excited by parametric delta-correlated processes is presented. This generalization gives a new light on the corrective coefficients in the stochastic differential equations driven by parametric delta-correlated processes. The full significance of these corrective terms is evidenced by means of some examples.

Stochastic differential equationNuclear Energy and EngineeringGeneralizationMechanical EngineeringMathematical analysisAerospace EngineeringOcean EngineeringStatistical and Nonlinear PhysicsCondensed Matter PhysicsCivil and Structural EngineeringMathematicsParametric statistics
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A subtle error in conventional stochastic linearization techniques

1998

Abstract The stochastic linearization technique as applied to the SDOF system is re-examined. Two standard procedures associated with the stochastic linearization, widely adopted in the literature, are shown to be erroneous. Two new procedures to correct the errors made in previous works are introduced. To gain more insight, the procedures are applied to the quintic oscillator. Comparative numerical analysis is performed.

Stochastic linearization; Random processesControl theoryLinearizationGeneral MathematicsApplied MathematicsNumerical analysisStochastic linearizationRandom processesGeneral Physics and AstronomyStatistical and Nonlinear PhysicsMathematicsQuintic functionChaos, Solitons & Fractals
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Stochastic integro-differential and differential equations of non-linear systems excited by parametric Poisson pulses

1997

Abstract The connection between stochastic integro-differential equation and stochastic differential equation of non-linear systems driven by parametric Poisson delta correlated processes is presented. It is shown that the two different formulations are fully equivalent in the case of external excitation. In the case of parametric type excitation the two formulation are equivalent if the non-linear argument in the integral representation is related by means of a series to the corresponding non-linear parametric term in the stochastic differential equation. Differential rules for the two representations to find moment equations of every order of the response are also compared.

Stochastic partial differential equationNonlinear systemStochastic differential equationMechanics of MaterialsStochastic processDifferential equationApplied MathematicsMechanical EngineeringNumerical analysisMathematical analysisFirst-order partial differential equationParametric statisticsMathematics
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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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ORDERING KINETICS IN QUASI-ONE-DIMENSIONAL ISING-LIKE SYSTEMS

1993

We present results of a Monte Carlo simulation of the kinetics of ordering in the two-dimensional nearest-neighbor Ising model in anL xM geometry with two free boundaries of length M≫L. This model can be viewed as representing an adsorbant on a stepped surface with mean terrace widthL. We follow the ordering kinetics after quenches to temperatures 0.25 ⩽ T/Tc ⩽ 1 starting from a random initial configuration at a coverage ofΘ=0.5 in the corresponding lattice gas picture. The systems evolve in time according to a Glauber kinetics with nonconserved order parameter. The equilibrium structure is given by a one-dimensional sequence of ordered domains. The ordering process evolves from a short ini…

Stochastic processLattice (order)Logarithmic growthMonte Carlo methodStatistical and Nonlinear PhysicsIsing modelStatistical physicsStatistical mechanicsStructure factorRandom walkMathematical PhysicsMathematics
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BROWNIAN DYNAMICS SIMULATIONS WITHOUT GAUSSIAN RANDOM NUMBERS

1991

We point out that in a Brownian dynamics simulation it is justified to use arbitrary distribution functions of random numbers if the moments exhibit the correct limiting behavior prescribed by the Fokker-Planck equation. Our argument is supported by a simple analytical consideration and some numerical examples: We simulate the Wiener process, the Ornstein-Uhlenbeck process and the diffusion in a Φ4 potential, using both Gaussian and uniform random numbers. In these examples, the rate of convergence of the mean first exit time is found to be nearly identical for both types of random numbers.

Stochastic processMathematical analysisGeneral Physics and AstronomyStatistical and Nonlinear PhysicsOrnstein–Uhlenbeck processBrownian excursionBrownian bridgeComputer Science Applicationssymbols.namesakeComputational Theory and MathematicsWiener processReflected Brownian motionStochastic simulationsymbolsStatistical physicsGaussian processMathematical PhysicsMathematicsInternational Journal of Modern Physics C
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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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