Search results for "stochastic"

showing 10 items of 1018 documents

Hedging of Spatial Temperature Risk with Market-Traded Futures

2011

The main objective of this work is to construct optimal temperature futures from available market-traded contracts to hedge spatial risk. Temperature dynamics are modelled by a stochastic differential equation with spatial dependence. Optimal positions in market-traded futures minimizing the variance are calculated. Examples with numerical simulations based on a fast algorithm for the generation of random fields are presented.

Mathematical optimizationStochastic differential equationWork (thermodynamics)Random fieldApplied MathematicsStochastic simulationEconometricsVariance (accounting)Spatial dependenceHedge (finance)Futures contractFinanceMathematicsApplied Mathematical Finance
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A novel technique for stochastic root-finding: Enhancing the search with adaptive d-ary search

2017

The most fundamental problem encountered in the field of stochastic optimization, is the Stochastic Root Finding (SRF) problem where the task is to locate an unknown point x∗ for which g(x∗) = 0 for a given function g that can only be observed in the presence of noise [15]. The vast majority of the state-of-the-art solutions to the SRF problem involve the theory of stochastic approximation. The premise of the latter family of algorithms is to oper ate by means of so-called “small-step”processesthat explorethe search space in a conservative manner. Using this paradigm, the point investigated at any time instant is in the proximity of the point investigated at the previous time instant, render…

Mathematical optimizationStochastic point location problemsInformation Systems and ManagementLearning automataComputer scienceStochastic root finding problemsLearning Automata020206 networking & telecommunications02 engineering and technologyInterval (mathematics)Function (mathematics)Stochastic approximationComputer Science ApplicationsTheoretical Computer ScienceArtificial IntelligenceControl and Systems Engineering0202 electrical engineering electronic engineering information engineeringSearch problem020201 artificial intelligence & image processingStochastic optimizationAlgorithmRoot-finding algorithmSoftwareInformation Sciences
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Approximation-Based Adaptive Fuzzy Tracking Control for a Class of Nonstrict-Feedback Stochastic Nonlinear Time-Delay Systems

2015

This paper focuses on the problem of approximation-based adaptive fuzzy tracking control for a class of stochastic nonlinear time-delay systems with a nonstrict-feedback structure. A variable separation approach is introduced to overcome the design difficulty from the nonstrict-feedback structure. Mamdani-type fuzzy logic systems are utilized to model the unknown nonlinear functions in the process of controller design, and an adaptive fuzzy tracking controller is systematically designed by using a backstepping technique. It is shown that the proposed controller guarantees that all signals in the closed-loop system are fourth-moment semiglobally uniformly ultimately bounded, and the tracking…

Mathematical optimizationStochastic processApplied MathematicsFuzzy logicTracking errorNonlinear systemComputational Theory and MathematicsArtificial IntelligenceControl and Systems EngineeringControl theoryBacksteppingAdaptive systemBounded functionMathematicsIEEE Transactions on Fuzzy Systems
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Average flow constraints and stabilizability in uncertain production-distribution systems

2009

We consider a multi-inventory system with controlled flows and uncertain demands (disturbances) bounded within assigned compact sets. The system is modelled as a first-order one integrating the discrepancy between controlled flows and demands at different sites/nodes. Thus, the buffer levels at the nodes represent the system state. Given a long-term average demand, we are interested in a control strategy that satisfies just one of two requirements: (i) meeting any possible demand at each time (worst case stability) or (ii) achieving a predefined flow in the average (average flow constraints). Necessary and sufficient conditions for the achievement of both goals have been proposed by the aut…

Mathematical optimizationStochastic stabilityControl and OptimizationComputer scienceSCHEDULING POLICIESUNKNOWN INPUTSInventory control; Robust controlRobust controlUncertain systemsUncertain demandsManagement Science and Operations ResearchControl strategies; Inventory systems; Uncertain demands; Worst caseStability (probability)Distribution systemMULTI-INVENTORY SYSTEMSControl theoryProduction (economics)Inventory control Robust control Stochastic stabilityAverage costInventory systemsMathematicsInventory controlStochastic processControl strategiesApplied MathematicsWorst caseNETWORKSControllabilityFlow (mathematics)Bounded functionProduction controlRobust controlSettore MAT/09 - Ricerca OperativaMANUFACTURING SYSTEMS
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Subsignal-based denoising from piecewise linear or constant signal

2011

15 pages; International audience; n the present work, a novel signal denoising technique for piecewise constant or linear signals is presented termed as "signal split." The proposed method separates the sharp edges or transitions from the noise elements by splitting the signal into different parts. Unlike many noise removal techniques, the method works only in the nonorthogonal domain. The new method utilizes Stein unbiased risk estimate (SURE) to split the signal, Lipschitz exponents to identify noise elements, and a polynomial fitting approach for the sub signal reconstruction. At the final stage, merging of all parts yield in the fully denoised signal at a very low computational cost. St…

Mathematical optimization[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer scienceStochastic resonanceNoise reduction[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technology01 natural sciencesMultiplicative noisePiecewise linear function010104 statistics & probabilitySpeckle patternsymbols.namesakeSignal-to-noise ratioWavelet[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0202 electrical engineering electronic engineering information engineering0101 mathematicsSignal transfer functionShrinkageSignal reconstructionNoise (signal processing)General EngineeringNonlinear opticsWavelet transform020206 networking & telecommunicationsTotal variation denoisingAtomic and Molecular Physics and OpticsAdditive white Gaussian noiseGaussian noisePiecewisesymbolsStep detectionAlgorithm[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Parasite population delay model of malaria type with stochastic perturbation and environmental criterion for limitation of disease

2009

AbstractWe present a stochastic delay model of an infectious disease (malaria) transmitted by a vectors (mosquitoes) after an incubation time. A criterion for limitation of disease is found.

Mathematical optimizationeducation.field_of_studyStochastic differential equationStochastic modellingApplied MathematicsPopulationDiseaseDelay differential equationPopulation dynamicmedicine.diseaseIncubation periodStochastic differential equationDelay differential equationSettore MAT/05 - Analisi MatematicaInfectious disease (medical specialty)Stochastic differential equation population dynamic delay differential equationStatisticsparasitic diseasesmedicineeducationMalariaAnalysisMathematicsJournal of Mathematical Analysis and Applications
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An IMEX-Scheme for Pricing Options under Stochastic Volatility Models with Jumps

2014

Partial integro-differential equation (PIDE) formulations are often preferable for pricing options under models with stochastic volatility and jumps, especially for American-style option contracts. We consider the pricing of options under such models, namely the Bates model and the so-called stochastic volatility with contemporaneous jumps (SVCJ) model. The nonlocality of the jump terms in these models leads to matrices with full matrix blocks. Standard discretization methods are not viable directly since they would require the inversion of such a matrix. Instead, we adopt a two-step implicit-explicit (IMEX) time discretization scheme, the IMEX-CNAB scheme, where the jump term is treated ex…

Mathematical optimizationimplicit-explicit time discretizationDiscretizationStochastic volatilityApplied Mathematicsta111Linear systemLU decompositionMathematics::Numerical Analysislaw.inventionComputational MathematicsMatrix (mathematics)stochastic volatility modelMultigrid methodlawValuation of optionsjump-diffusion modelJumpoption pricingfinite difference methodMathematicsSIAM Journal on Scientific Computing
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Regularity of solutions to differential equations with non-Lipschitz coefficients

2008

AbstractWe study the ordinary and stochastic differential equations whose coefficients satisfy certain non-Lipschitz conditions, namely, we study the behaviors of small subsets under the flows generated by these equations.

Mathematics(all)Hölder continuousGeneral MathematicsMathematical analysisHausdorff dimensionNon-Lipschitz conditionMethod of undetermined coefficientsExamples of differential equationsStochastic partial differential equationDifferential equationCollocation methodC0-semigroupDifferential algebraic equationMathematicsSeparable partial differential equationNumerical partial differential equationsBulletin des Sciences Mathématiques
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Spatial Besov regularity for stochastic partial differential equations on Lipschitz domains

2010

We use the scale of Besov spaces B^\alpha_{\tau,\tau}(O), \alpha>0, 1/\tau=\alpha/d+1/p, p fixed, to study the spatial regularity of the solutions of linear parabolic stochastic partial differential equations on bounded Lipschitz domains O\subset R^d. The Besov smoothness determines the order of convergence that can be achieved by nonlinear approximation schemes. The proofs are based on a combination of weighted Sobolev estimates and characterizations of Besov spaces by wavelet expansions.

Mathematics::Functional AnalysisSmoothness (probability theory)General MathematicsProbability (math.PR)Mathematics::Analysis of PDEsScale (descriptive set theory)Numerical Analysis (math.NA)Lipschitz continuitySobolev spaceStochastic partial differential equation60H15 Secondary: 46E35 65C30WaveletRate of convergenceBounded functionFOS: MathematicsApplied mathematicsMathematics - Numerical AnalysisMathematics - ProbabilityMathematicsStudia Mathematica
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Stabilization of discrete-time systems with stochastic sampling

2012

This paper is concerned with the stabilization problem of discrete-time systems with stochastic sampling. It is assumed that there are a single-rate sampling in the plant input and two stochastic sampling rates in the controller input whose occurrence probabilities are given constants and satisfy a Bernoulli distribution. By Lyapunov function approach, a new sufficient condition is presented for the mean square asymptotic stability of the system. Based on this, the design procedure for stabilization controllers is proposed. Finally, an example is given to demonstrate the effectiveness of the proposed techniques.

Mean squareLyapunov functionsymbols.namesakeExponential stabilityDiscrete time and continuous timeRobustness (computer science)Bernoulli distributionStochastic processControl theorysymbolsSampling (statistics)Mathematics2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA)
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