Search results for "Random variable"

showing 10 items of 151 documents

Cross-Layer MAC Protocol for Unbiased Average Consensus Under Random Interference

2019

Wireless Sensor Networks have been revealed as a powerful technology to solve many different problems through sensor nodes cooperation. One important cooperative process is the so-called average gossip algorithm, which constitutes a building block to perform many inference tasks in an efficient and distributed manner. From the theoretical designs proposed in most previous work, this algorithm requires instantaneous symmetric links in order to reach average consensus. However, in a realistic scenario wireless communications are subject to interferences and other environmental factors, which results in random instantaneous topologies that are, in general, asymmetric. Consequently, the estimat…

0209 industrial biotechnologyComputer Networks and CommunicationsComputer sciencebusiness.industryEstimator020206 networking & telecommunications02 engineering and technologyExpected valueNetwork topology020901 industrial engineering & automationMinimum-variance unbiased estimatorBias of an estimatorSignal Processing0202 electrical engineering electronic engineering information engineeringWirelessbusinessAlgorithmWireless sensor networkRandom variableInformation SystemsIEEE Transactions on Signal and Information Processing over Networks
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Adaptive Consensus-Based Distributed Kalman Filter for WSNs with Random Link Failures

2016

Wireless Sensor Networks have emerged as a very powerful tool for the monitoring and control, over large areas, of diverse phenomena. One of the most appealing properties of these networks is their potentiality to perform complex tasks in a total distributed fashion, without requiring a central entity. In this scenario, where nodes are constrained to use only local information and communicate with one-hop neighbors, iterative consensus algorithms are extensively used due to their simplicity. In this work, we propose the design of a consensus-based distributed Kalman filter for state estimation, in a sensor network whose connections are subject to random failures. As a result of this unrelia…

0209 industrial biotechnologyComputer scienceDistributed computingEstimator020206 networking & telecommunications02 engineering and technologyKalman filterInvariant extended Kalman filterExtended Kalman filter020901 industrial engineering & automationFilter (video)0202 electrical engineering electronic engineering information engineeringFast Kalman filterWireless sensor networkRandom variable2016 International Conference on Distributed Computing in Sensor Systems (DCOSS)
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A strategic oscillation simheuristic for the Time Capacitated Arc Routing Problem with stochastic demands

2021

Abstract The Time Capacitated Arc Routing Problem (TCARP) extends the classical Capacitated Arc Routing Problem by considering time-based capacities instead of traditional loading capacities. In the TCARP, the costs associated with traversing and servicing arcs, as well as the vehicle’s capacity, are measured in time units. The increasing use of electric vehicles and unmanned aerial vehicles, which use batteries of limited duration, illustrates the importance of time-capacitated routing problems. In this paper, we consider the TCARP with stochastic demands, i.e.: the actual demands on each edge are random variables which specific values are only revealed once the vehicle traverses the arc. …

0209 industrial biotechnologyMathematical optimization021103 operations researchTraverseGeneral Computer ScienceUnit of timeComputer science0211 other engineering and technologies02 engineering and technologyManagement Science and Operations ResearchArc (geometry)020901 industrial engineering & automationModeling and SimulationEnhanced Data Rates for GSM EvolutionDuration (project management)Routing (electronic design automation)Arc routingRandom variableComputers & Operations Research
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Longitudinal Investigation into Genetics in the Conservation of Metabolic Phenotypes in Danish and Chinese Twins

2016

Longitudinal twin studies on long term conservation of individual metabolic phenotypes can help to explore the genetic and environmental basis in maintaining metabolic homeostasis and metabolic health. We performed a longitudinal twin study on 12 metabolic phenotypes from Danish twins followed up for 12 years and Chinese twins traced for 7 years. The study covered a relatively large sample of 502 pairs of Danish adult twins with a mean age at intake of 38 years and a total of 181 Chinese adult twin pairs with a mean baseline age of 39.5 years. Bivariate twin models were fitted to the longitudinal measurements taken at two time points (at baseline and follow-up) to estimate the genetic and e…

0301 basic medicineDenmarkTwinslcsh:MedicineGene ExpressionBlood PressureVascular MedicineBiochemistryCorrelation0302 clinical medicineGlucose MetabolismMedicine and Health SciencesEthnicitiesLongitudinal Studieslcsh:Sciencemetabolic phenotypes phenotype stability Danish Chinese twin modelsGeneticsMultidisciplinaryCovarianceDanesPhenotypePhenotypesPhenotypePhysical ScienceslanguageCarbohydrate MetabolismEnvironmental regulationResearch ArticleAdultChina030209 endocrinology & metabolismBivariate analysisBiologyDanish03 medical and health sciencesGeneticsHumansGene RegulationMetabolic healthlcsh:RBiology and Life SciencesRandom VariablesProbability TheoryTwin studylanguage.human_languageMetabolism030104 developmental biologyBlood pressurePeople and Placeslcsh:QPopulation GroupingsMathematicsDevelopmental BiologyPLOS ONE
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Basic Measure Theory

2020

In this chapter, we lay the measure theoretic foundations of probability theory. We introduce the classes of sets (semirings, rings, algebras, σ-algebras) that allow for a systematic treatment of events and random observations. Using the measure extension theorem, we construct measures, in particular probability measures on σ-algebras. Finally, we define random variables as measurable maps and study the σ-algebras generated by certain maps.

AlgebraProbability theoryExtension (predicate logic)Construct (philosophy)Random variableMeasure (mathematics)SemiringMathematicsProbability measure
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Measuring Observable Quantum Contextuality

2016

Contextuality is a central property in comparative analysis of classical, quantum, and supercorrelated systems. We examine and compare two well-motivated approaches to contextuality. One approach (“contextuality-by-default”) is based on the idea that one and the same physical property measured under different conditions (contexts) is represented by different random variables. The other approach is based on the idea that while a physical property is represented by a single random variable irrespective of its context, the joint distributions of the random variables describing the system can involve negative (quasi-)probabilities. We show that in the Leggett-Garg and EPR-Bell systems, the two …

CHSH inequalityObservableContext (language use)16. Peace & justice01 natural sciences010305 fluids & plasmasTheoretical physicsNegative probabilityJoint probability distribution0103 physical sciencesStatistical physics010306 general physicsQuantum contextualityRandom variableQuantumMathematics
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Statistical properties of the capacity of multipath fading channels

2009

It is well known that a frequency-nonselective multipath fading channel can be modeled by a sum of complex sinusoids, also called sum-of-cisoids (SOC). By using the SOC, we can efficiently model the scattered component of the received signal in non-isotropic scattering environments. Such SOC-based multipath channel models provide the flexibility of having correlated in-phase and quadrature phase components of the received signal. This paper presents the derivation and analysis of the statistical properties of the capacity of multipath fading channels under LOS conditions. As an appropriate stochastic model for the multipath fading channel, we have adopted the SOC model. We have derived the …

Channel capacityStochastic modellingComputer scienceCumulative distribution functionStatisticsAlgorithmRandom variableMultipath propagationComputer Science::Information TheoryCommunication channel2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications
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Is there an absolutely continuous random variable with equal probability density and cumulative distribution functions in its support? Is it unique? …

2014

This paper inquires about the existence and uniqueness of a univariate continuous random variable for which both cumulative distribution and density functions are equal and asks about the conditions under which a possible extrapolation of the solution to the discrete case is possible. The issue is presented and solved as a problem and allows to obtain a new family of probability distributions. The different approaches followed to reach the solution could also serve to warn about some properties of density and cumulative functions that usually go unnoticed, helping to deepen the understanding of some of the weapons of the mathematical statistician’s arsenal.

Characteristic function (probability theory)Cumulative distribution functionCalculusProbability mass functionProbability distributionApplied mathematicsProbability density functionMoment-generating functionRandom variableLaw of the unconscious statisticianMathematicsInternational Journal of Advanced Statistics and Probability
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On the use of fractional calculus for the probabilistic characterization of random variables

2009

In this paper, the classical problem of the probabilistic characterization of a random variable is re-examined. A random variable is usually described by the probability density function (PDF) or by its Fourier transform, namely the characteristic function (CF). The CF can be further expressed by a Taylor series involving the moments of the random variable. However, in some circumstances, the moments do not exist and the Taylor expansion of the CF is useless. This happens for example in the case of $\alpha$--stable random variables. Here, the problem of representing the CF or the PDF of random variables (r.vs) is examined by introducing fractional calculus. Two very remarkable results are o…

Characteristic function (probability theory)FOS: Physical sciencesAerospace EngineeringMathematics - Statistics TheoryOcean EngineeringProbability density functionComplex order momentStatistics Theory (math.ST)Fractional calculusymbols.namesakeIngenieurwissenschaftenFOS: MathematicsTaylor seriesApplied mathematicsCharacteristic function serieMathematical PhysicsCivil and Structural EngineeringMathematicsGeneralized Taylor serieMechanical EngineeringStatistical and Nonlinear PhysicsProbability and statisticsMathematical Physics (math-ph)Condensed Matter PhysicsFractional calculusFourier transformNuclear Energy and EngineeringPhysics - Data Analysis Statistics and ProbabilitysymbolsFractional calculus; Generalized Taylor series; Complex order moments; Fractional moments; Characteristic function series; Probability density function seriesddc:620Series expansionFractional momentProbability density function seriesSettore ICAR/08 - Scienza Delle CostruzioniRandom variableData Analysis Statistics and Probability (physics.data-an)
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A method for the probabilistic analysis of nonlinear systems

1995

Abstract The probabilistic description of the response of a nonlinear system driven by stochastic processes is usually treated by means of evaluation of statistical moments and cumulants of the response. A different kind of approach, by means of new quantities here called Taylor moments, is proposed. The latter are the coefficients of the Taylor expansion of the probability density function and the moments of the characteristic function too. Dual quantities with respect to the statistical cumulants, here called Taylor cumulants, are also introduced. Along with the basic scheme of the method some illustrative examples are analysed in detail. The examples show that the proposed method is an a…

Characteristic function (probability theory)Stochastic processMechanical EngineeringAerospace EngineeringOcean EngineeringStatistical and Nonlinear PhysicsProbability density functionCondensed Matter Physicssymbols.namesakeNonlinear systemNuclear Energy and EngineeringTaylor seriessymbolsCalculusApplied mathematicsProbabilistic analysis of algorithmsCumulantCivil and Structural EngineeringMathematicsTaylor expansions for the moments of functions of random variables
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