Search results for "Applied Mathematic"

showing 10 items of 4398 documents

Advanced stochastic control systems with engineering applications

2014

1 School of Astronautics, Harbin Institute of Technology, Harbin, Heilongjiang, China 2 School of Electrical and Electronic Engineering, The University of Adelaide, SA 5005, Australia 3 Department of Engineering, Faculty of Engineering and Science, University of Agder, 4898 Grimstad, Norway 4 Institute of Automation and Complex Systems, University of Duisburg-Essen, Duisburg, Germany 5 College of Automation, Chongqing University, Chongqing 400044, China

Stochastic controlAstronauticsArticle Subjectbusiness.industrylcsh:MathematicsApplied MathematicsVDP::Technology: 500::Mechanical engineering: 570Analysis; Applied Mathematicslcsh:QA1-939AutomationEngineering physicsEngineering managementbusinessAnalysisMathematicsElektrotechnik
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A Fokker–Planck control framework for multidimensional stochastic processes

2013

AbstractAn efficient framework for the optimal control of probability density functions (PDFs) of multidimensional stochastic processes is presented. This framework is based on the Fokker–Planck equation that governs the time evolution of the PDF of stochastic processes and on tracking objectives of terminal configuration of the desired PDF. The corresponding optimization problems are formulated as a sequence of open-loop optimality systems in a receding-horizon control strategy. Many theoretical results concerning the forward and the optimal control problem are provided. In particular, it is shown that under appropriate assumptions the open-loop bilinear control function is unique. The res…

Stochastic controlMathematical optimizationContinuous-time stochastic processOptimization problemoptimal control stochastic processesStochastic processApplied MathematicsOptimal controlComputational MathematicsModel predictive controlMultidimensional stochastic processOptimal control theoryLimit cycleProbability density functionFokker–Planck equationFokker–Planck equationModel predictive controlMathematicsJournal of Computational and Applied Mathematics
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Solving fully randomized first-order linear control systems: Application to study the dynamics of a damped oscillator with parametric noise under sto…

2022

[EN] This paper is devoted to study random linear control systems where the initial condition, the final target, and the elements of matrices defining the coefficients are random variables, while the control is a stochastic process. The so-called Random Variable Transformation technique is adapted to obtain closed-form expressions of the probability density functions of the solution and of the control. The theoretical findings are applied to study the dynamics of a damped oscillator subject to parametric noise.

Stochastic controlStochastic processApplied MathematicsRandom damped linear oscillatorsProbability density functionNoise (electronics)Computational MathematicsTransformation (function)Random control systemsInitial value problemApplied mathematicsFirst probability density functionMATEMATICA APLICADARandom variableRandom Variable Transformation techniqueMathematicsParametric statistics
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European Option Pricing and Hedging with Both Fixed and Proportional Transaction Costs

2003

Abstract In this paper we provide a systematic treatment of the utility based option pricing and hedging approach in markets with both fixed and proportional transaction costs: we extend the framework developed by Davis et al. (SIAM J. Control Optim., 31 (1993) 470) and formulate the option pricing and hedging problem. We propose and implement a numerical procedure for computing option prices and corresponding optimal hedging strategies. We present a careful analysis of the optimal hedging strategy and elaborate on important differences between the exact hedging strategy and the asymptotic hedging strategy of Whalley and Wilmott (RISK 7 (1994) 82). We provide a simulation analysis in order …

Stochastic controlTransaction costEconomics and EconometricsMathematical optimizationControl and OptimizationApplied MathematicsMonte Carlo methods for option pricingjel:C61Implied volatilityjel:G13jel:G11option pricing transaction costs stochastic control Markov chain approximationMicroeconomicsVariable pricingOrder (business)Valuation of optionsEconomicsAsian optionFinite difference methods for option pricingSSRN Electronic Journal
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American Option Pricing and Exercising with Transaction Costs

2005

In this paper we examine the problem of finding the reservation option prices and corresponding exercise policies of American options in a market with proportional transaction costs using the utility based approach proposed by Davis and Zariphopoulou (1995). We present a model where the option holder has a constant absolute risk aversion. We discuss the numerical algorithm and propose a new characterization of the option holder's value function. We suggest original discretization schemes for computing reservation prices and exercise policies of American options. The discretization schemes are implemented for the cases of American put and call options. We present the study of the optimal tra…

Stochastic controlTransaction costFinancial economicsApplied MathematicsReservationComputer Science ApplicationsMicroeconomicsVariable pricingValuation of optionsEconomicsOptimal stoppingAsian optionFinite difference methods for option pricingDatabase transactionFinanceSSRN Electronic Journal
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Stochastic Control Problems

2003

The general theory of stochastic processes originated in the fundamental works of A. N. Kolmogorov and A. Ya. Khincin at the beginning of the 1930s. Kolmogorov, 1938 gave a systematic and rigorous construction of the theory of stochastic processes without aftereffects or, as it is customary to say nowadays, Markov processes. In a number of works, Khincin created the principles of the theory of so-called stationary processes.

Stochastic controlsymbols.namesakeMarkov chainWiener processComputer scienceStochastic processsymbolsStochastic matrixApplied mathematicsMarkov processStochastic optimizationStochastic programming
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A class of stochastic differential equations with non-Lipschitzian coefficients: pathwise uniqueness and no explosion

2003

Abstract A new result for the pathwise uniqueness of solutions of stochastic differential equations with non-Lipschitzian coefficients is established. Furthermore, we prove that the solution has no explosion under the growth ξlogξ. To cite this article: S. Fang, T. Zhang, C. R. Acad. Sci. Paris, Ser. I 337 (2003).

Stochastic differential equationClass (set theory)Probability theoryContinuous functionDifferential equationMathematical analysisApplied mathematicsGeneral MedicineUniquenessMathematicsComptes Rendus Mathematique
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What is Differential Stochastic Calculus?

1999

Some well known concepts of stochastic differential calculus of non linear systems corrupted by parametric normal white noise are here outlined. Ito and Stratonovich integrals concepts as well as Ito differential rule are discussed. Applications to the statistics of the response of some linear and non linear systems is also presented.

Stochastic differential equationMathematics::ProbabilityQuantum stochastic calculusMultivariable calculusStochastic calculusApplied mathematicsDifferential calculusTime-scale calculusMalliavin calculusDifferential (mathematics)Mathematics
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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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Modeling of Sensory Characteristics Based on the Growth of Food Spoilage Bacteria

2016

During last years theoretical works shed new light and proposed new hypothesis on the mechanisms which regulate the time behaviour of biological populations in different natural systems. Despite of this, the role of environmental variables in ecological systems is still an open question. Filling this gap of knowledge is a crucial task for a deeper comprehension of the dynamics of biological populations in real ecosystems. In this work we study how the dynamics of food spoilage bacteria influences the sensory characteristics of fresh fish specimens. This topic is crucial for a better understanding of the role played by the bacterial growth on the organoleptic properties, and for the quality …

Stochastic ordinary differential equationmedia_common.quotation_subjectFood spoilageOrganolepticFOS: Physical sciencesSensory systemContext (language use)BiologyPopulation dynamic01 natural sciencesSensory analysisPopulation dynamics; Predictive microbiology; Stochastic ordinary differential equations; Modeling and Simulation010305 fluids & plasmas0103 physical sciencesStatisticsQuality (business)010306 general physicsQuantitative Biology - Populations and EvolutionCondensed Matter - Statistical Mechanicsmedia_commonPredictive microbiologyStatistical Mechanics (cond-mat.stat-mech)EcologyApplied MathematicsPopulations and Evolution (q-bio.PE)Experimental dataSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Modeling and SimulationFOS: Biological sciencesPredictive microbiology
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