Search results for "Stochastic process"

showing 10 items of 346 documents

Nonlinear Disorder Mapping via Three Wave Mixing in Poled Lithium Tantalate

2010

We introduce and test a simple approach for the characterization of domain distribution in bulk quadratic ferroelectric crystals, such as periodically poled Lithium Tantalate with random mark-to space ratio.

Materials scienceCondensed matter physicsbusiness.industryStochastic processPhysics::OpticsNonlinear opticsSecond-harmonic generationImage processing Nonlinear optics Nonlinear wave mixingFerroelectricitychemistry.chemical_compoundNonlinear systemsymbols.namesakeOpticsFourier transformchemistryLithium tantalatesymbolsbusinessMixing (physics)Conference on Lasers and Electro-Optics 2010
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Statistical prediction of corrosion front penetration

1997

A statistical method to predict the stochastic evolution of corrosion fronts has been developed. The method is based on recording material loss and maximum front depth. In this paper we introduce the method and test its applicability. In the absence of experimental data we use simulation data from a three-dimensional corrosion model for this test. The corrosion model simulates localized breakdown of a protective oxide layer, hydrolysis of corrosion product and repassivation of the exposed surface. In the long time limit of the model, pits tend to coalesce. For different model parameters the model reproduces corrosion patterns observed in experiment. The statistical prediction method is base…

Materials scienceStochastic processEconometricsProtective oxideConditional probabilityMechanicsPenetration (firestop)Physics::Chemical PhysicsStochastic evolutionPenetration depthResidualCorrosionPhysical Review E
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Time scales of adaptive behavior and motor learning in the presence of stochastic perturbations.

2009

In this paper, the major assumptions of influential approaches to the structure of variability in practice conditions are discussed from the perspective of a generalized evolving attractor landscape model of motor learning. The efficacy of the practice condition effects is considered in relation to the theoretical influence of stochastic perturbations in models of gradient descent learning of multiple dimension landscapes. A model for motor learning is presented combining simulated annealing and stochastic resonance phenomena against the background of different time scales for adaptation and learning processes. The practical consequences of the model's assumptions for the structure of pract…

Mathematical optimizationAcclimatizationMovementBiophysicsExperimental and Cognitive PsychologyMotor ActivityOscillometryAttractorAdaptation PsychologicalHumansLearningOrthopedics and Sports MedicineAttentionMotor skillAdaptive behaviorBehaviorStochastic ProcessesStochastic processbusiness.industryGeneral MedicineStochastic resonance (sensory neurobiology)Motor SkillsSimulated annealingArtificial intelligenceMotor learningGradient descentbusinessPsychologyNoiseHuman movement science
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Learning for allocations in the long-run average core of dynamical cooperative TU games

2011

We consider repeated coalitional TU games characterized by unknown but bounded and time-varying coalitions' values. We build upon the assumption that the Game Designer uses a vague measure of the extra reward that each coalition has received up to the current time to learn on how to re-adjust the allocations among the players. As main result, we present an allocation rule based on the extra reward variable that converges with probability one to the core of the long-run average game. Analogies with stochastic stability theory are put in evidence.

Mathematical optimizationComputer scienceRobustness (computer science)Stochastic processBounded functionRule-based systemRobust controlVideo game designGame theoryMathematical economicsUpper and lower boundsgame theory control
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Stochastic reconstruction of sandstones

2000

A simulated annealing algorithm is employed to generate a stochastic model for a Berea and a Fontainebleau sandstone with prescribed two-point probability function, lineal path function, and ``pore size'' distribution function, respectively. We find that the temperature decrease of the annealing has to be rather quick to yield isotropic and percolating configurations. A comparison of simple morphological quantities indicates good agreement between the reconstructions and the original sandstones. Also, the mean survival time of a random walker in the pore space is reproduced with good accuracy. However, a more detailed investigation by means of local porosity theory shows that there may be s…

Mathematical optimizationCondensed Matter - Materials ScienceStochastic modellingStochastic processIsotropyMaterials Science (cond-mat.mtrl-sci)FOS: Physical sciencesGeometryProbability density functionPhysics::GeophysicsDistribution functionRandom walker algorithmSimulated annealingPorosityGeology
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Statistical validation of rival models for observable stochastic process and its identification

2011

In this paper, for statistical validation of rival (analytical or simulation) models collected for modeling observable process in stochastic system (say, transportation or service system), a uniformly most powerful invariant (UMPI) test is developed from the generalized maximum likelihood ratio (GMLR). This test can be considered as a result of a new approach to solving the Behrens-Fisher problem when covariance matrices of multivariate normal populations (compared with respect to their means) are different and unknown. The test makes use of an invariant statistic whose distribution, under the null hypothesis, does not depend on the unknown (nuisance) parameters. The sample size and thresho…

Mathematical optimizationCovariance matrixStochastic processMultivariate normal distributionCovarianceInvariant (mathematics)Null hypothesisBehrens–Fisher problemStatisticMathematics2011 Baltic Congress on Future Internet and Communications
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Stochastic analysis of external and parametric dynamical systems under sub-Gaussian Levy white-noise

2008

In this study stochastic analysis of non-linear dynamical systems under α-stable, multiplicative white noise has been conducted. The analysis has dealt with a special class of α-stable stochastic processes namely sub-Gaussian white noises. In this setting the governing equation either of the probability density function or of the characteristic function of the dynamical response may be obtained considering the dynamical system forced by a Gaussian white noise with an uncertain factor with α/2- stable distribution. This consideration yields the probability density function or the characteristic function of the response by means of a simple integral involving the probability density function …

Mathematical optimizationDynamical systems theoryCharacteristic function (probability theory)Stochastic processMechanical EngineeringFokker-Planck equationProbability density functionLévy white noiseBuilding and ConstructionWhite noiseStable processstochastic differential calculusymbols.namesakeAdditive white Gaussian noiseMechanics of MaterialssymbolsStatistical physicssub-Gaussian white noise.Settore ICAR/08 - Scienza Delle CostruzioniRandom dynamical systemCivil and Structural EngineeringMathematicsStructural Engineering and Mechanics
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A Comparative Analysis of Different Robust Design Approaches in Sheet Stamping Operations

2011

A crucial issue in sheet stamping optimization problems is related to the process robustness improvement: critical scattering in the investigated performances arises due to some noise variables influence, often evolving up design failure itself. In fact, strong variations in the final stamped part or fluctuations of strain distribution may lead to an uncontrolled process design. Such variability cannot be controlled but anyway it is possible to develop proper design tools able to identify robust process calibrations above which the noises variations effects are admissible. In this paper, a multi‐objective optimization problem was analyzed, with the aim to minimize both excessive thinning an…

Mathematical optimizationEngineeringFEMOptimization problembusiness.industryStochastic processProcess designStampingmeta-modelingFinite element methodReliability engineeringRobust designspringbackmulti-objective optimizationRobustness (computer science)Strain distributionrobust designbusinessThinningSettore ING-IND/16 - Tecnologie E Sistemi Di Lavorazione
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Achieving Fair Load Balancing by Invoking a Learning Automata-Based Two-Time-Scale Separation Paradigm.

2020

Author's accepted manuscript. © 2020 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/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. In this article, we consider the problem of load balancing (LB), but, unlike the approaches that have been proposed earlier, we attempt to resolve the problem in a fair manner (or rather, it would probably be more appropriate to describe it as an ε-fair manner because, although the LB…

Mathematical optimizationLearning automataComputer Networks and Communicationsbusiness.industryStochastic processComputer scienceQuality of serviceResource allocationsCloud computingLoad balancing (computing)Continuous learning automatonsComputer Science ApplicationsArtificial IntelligenceServerResource allocationFair load balancingbusinessVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550SoftwareIEEE transactions on neural networks and learning systems
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A parsimonious model for generating arbitrage-free scenario trees

2016

Simulation models of economic, financial and business risk factors are widely used to assess risks and support decision-making. Extensive literature on scenario generation methods aims at describing some underlying stochastic processes with the least number of scenarios to overcome the ‘curse of dimensionality’. There is, however, an important requirement that is usually overlooked when one departs from the application domain of security pricing: the no-arbitrage condition. We formulate a moment matching model to generate multi-factor scenario trees for stochastic optimization satisfying no-arbitrage restrictions with a minimal number of scenarios and without any distributional assumptions.…

Mathematical optimizationMatching (statistics)021103 operations researchStochastic process05 social sciencesPricing in incomplete market0211 other engineering and technologiesStochastic programming02 engineering and technologyStochastic programmingConvex lower boundingSettore SECS-S/06 -Metodi Mat. dell'Economia e d. Scienze Attuariali e Finanz.Bounding overwatch0502 economics and businessPricing in incomplete marketsStochastic optimizationGlobal optimizationArbitrage050207 economicsGeneral Economics Econometrics and FinanceGlobal optimizationFinanceScenario treeCurse of dimensionalityMathematics
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