Search results for "Mathematical optimization"

showing 10 items of 1300 documents

Decomposing the transfer entropy to quantify lag-specific Granger causality in cardiovascular variability.

2013

We present a modification of the well known transfer entropy (TE) which makes it able to detect, besides the direction and strength of the information transfer between coupled processes, its exact timing. The approach follows a decomposition strategy which identifies--according to a lag-specific formulation of the concept of Granger causality--the set of time delays carrying significant information, and then assigns to each of these delays an amount of information transfer such that the total contribution yields the overall TE. We propose also a procedure for the practical estimation from time series data of the relevant delays and lag-specific TE in both bivariate and multivariate settings…

Multivariate statisticsMathematical optimizationInformation transferMedicine (all)LagEntropyBivariate analysisCardiovascular Physiological PhenomenaGranger causalitySettore ING-INF/06 - Bioingegneria Elettronica E InformaticaMultivariate AnalysisEntropy (information theory)HumansTransfer entropyComputer SimulationTime seriesAlgorithmsMathematicsAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
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Kernel intensity for space-time point processes with application to seismological problems

2010

Dealing with data coming from a space-time inhomogeneous process, there is often the need of semi-parametric estimates of the conditional intensity function; isotropic or anisotropic multivariate kernel estimates can be used, with windows sizes h. The properties of the intensities estimated with this choice of h are not always good for specific fields of application; we could try to choose h in order to have good predictive properties of the estimated intensity function. Since a direct ML approach cannot be followed, we propose an estimation procedure, computationally intensive, based on the subsequent increments of likelihood obtained adding an observation at time. The first results obtain…

Multivariate statisticsMathematical optimizationSpace timeKernel (statistics)IsotropyProcess (computing)Applied mathematicskernel intensity space-time point porcesses seismic activityAnisotropySettore SECS-S/01 - StatisticaIntensity (heat transfer)Point processMathematics
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Stochastic Nonlinear Time Series Forecasting Using Time-Delay Reservoir Computers: Performance and Universality

2014

International audience; Reservoir computing is a recently introduced machine learning paradigm that has already shown excellent performances in the processing of empirical data. We study a particular kind of reservoir computers called time-delay reservoirs that are constructed out of the sampling of the solution of a time-delay diFFerential equation and show their good performance in the forecasting of the conditional covariances associated to multivariate discrete-time nonlinear stochastic processes of VEC-GARCH type as well as in the prediction of factual daily market realized volatilities computed with intraday quotes, using as training input daily log-return series of moderate size. We …

Multivariate statisticsMathematical optimizationTime FactorsRealized varianceDifferential equationComputer scienceCognitive NeuroscienceMathematicsofComputing_NUMERICALANALYSIS02 engineering and technologyComputer Communication NetworksArtificial Intelligence0502 economics and business0202 electrical engineering electronic engineering information engineeringHumansTime seriesSimulation050205 econometrics Stochastic Processes[PHYS.PHYS.PHYS-OPTICS]Physics [physics]/Physics [physics]/Optics [physics.optics]Series (mathematics)Artificial neural networkComputersStochastic process05 social sciencesReservoir computingSampling (statistics)Universality (dynamical systems)Nonlinear systemNonlinear DynamicsData Interpretation Statistical020201 artificial intelligence & image processingNeural Networks ComputerForecastingSSRN Electronic Journal
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Forecasting correlated time series with exponential smoothing models

2011

Abstract This paper presents the Bayesian analysis of a general multivariate exponential smoothing model that allows us to forecast time series jointly, subject to correlated random disturbances. The general multivariate model, which can be formulated as a seemingly unrelated regression model, includes the previously studied homogeneous multivariate Holt-Winters’ model as a special case when all of the univariate series share a common structure. MCMC simulation techniques are required in order to approach the non-analytically tractable posterior distribution of the model parameters. The predictive distribution is then estimated using Monte Carlo integration. A Bayesian model selection crite…

Multivariate statisticsMathematical optimizationsymbols.namesakeModel selectionExponential smoothingPosterior probabilitysymbolsUnivariateMarkov chain Monte CarloBusiness and International ManagementSeemingly unrelated regressionsBayesian inferenceMathematicsInternational Journal of Forecasting
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A Smoothed Particle Image Reconstruction method

2010

Many image processing techniques work with scattered data distribution usually employing grid based methods leading to numerical problems. To address this issue, a numerical method avoiding mesh generation can be used. Such a method performs an integral representation by means of a smoothing kernel function and, in the discrete formulation, involves domain particles. In this paper the meshless Smoothed Particle Hydrodynamics method is proposed in the Image Reconstruction context and a new computational strategy called Smoothed Particle Image Reconstruction is presented; the new method is based on a scatter approach and several innovative ideas are introduced in order to improve the computat…

Nearest neighboring searchMathematical optimizationAlgebra and Number TheoryConsistency restoringNumerical analysisMeshless particle methodContext (language use)Image processingFunction (mathematics)Iterative reconstructionSmoothed-particle hydrodynamicsSettore MAT/08 - Analisi NumericaComputational MathematicsImage processingMesh generationImage reconstruction reconstructionTheory of computationSmoothed particle Hydrodinamics methodAlgorithmMathematicsCalcolo
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FUZZY TCP: A PRELIMINARY STUDY

2002

Implementing efficient TCP for the Internet necessarily has to cope with the problem that the source does not know in advance which window allocation policy should be the best to use for a given network condition. In this paper, an on-line adaptive fuzzy system is used at the source in an objective to find the best possible weighted combination among the available policies.

Network congestionMathematical optimizationEngineeringTCP accelerationbusiness.industryDistributed computingHSTCPZeta-TCPTCP tuningTCP delayed acknowledgmentbusinessCommunications protocolFuzzy logicIFAC Proceedings Volumes
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On the role of symmetry in solving maximum lifetime problem in two-dimensional sensor networks

2016

We analyze a continuous and discrete symmetries of the maximum lifetime problem in two dimensional sensor networks. We show, how a symmetry of the network and invariance of the problem under a given transformation group $G$ can be utilized to simplify its solution. We prove, that for a $G$-invariant maximum lifetime problem there exists a $G$-invariant solution. Constrains which follow from the $G$-invariance allow to reduce the problem and its solution to a subset, an optimal fundamental region of the sensor network. We analyze in detail solutions of the maximum lifetime problem invariant under a group of isometry transformations of a two dimensional Euclidean plane.

Networking and Internet Architecture (cs.NI)FOS: Computer and information sciencesMathematical optimizationComputer scienceGroup (mathematics)Computer Networks and CommunicationsSymmetry groupInvariant (physics)TopologySymmetry (physics)Computer Science - Networking and Internet Architecturesymmetry groupEuclidean geometryHomogeneous spaceIsometryInvariant (mathematics)Electrical and Electronic Engineeringwireless sensor networksWireless sensor networkenergy efficiencyInformation SystemsWireless Networks
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Consensus for networks with unknown but bounded disturbances

2009

We consider stationary consensus protocols for networks of dynamic agents. The measure of the neighbors' states is affected by unknown but bounded disturbances. Here the main contribution is the formulation and solution of what we call the $\epsilon$-consensus problem, where the states are required to converge in a target set of radius $\epsilon$ asymptotically or in finite time. We introduce as a solution a dead-zone policy that we denote as the lazy rule.

Networks; UBB; Consensus; Dynamic AgentsMathematical optimizationConsensusControl and OptimizationApplied MathematicsDynamic Agentsnetworks; unknown but bounded; consensus; dynamic agentsUBBRadiusdynamic agentsMeasure (mathematics)Set (abstract data type)unknown but boundedSettore ING-INF/04 - AutomaticaconsensusnetworksBounded functionNetworks UBB Consensus Dynamic AgentsApplied mathematicsNetworksFinite timeMathematics
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Numerical methods for nonlinear inverse problems

1996

AbstractInverse problems of distributed parameter systems with applications to optimal control and identification are considered. Numerical methods and their numerical analysis for solving this kind of inverse problems are presented, main emphasis being on the estimates of the rate of convergence for various schemes. Finally, based on the given error estimates, a two-grid method and related algorithms are introduced, which can be used to solve nonlinear inverse problems effectively.

Nonlinear inverse problemInverse problemsMathematical optimizationFinite element methodNumerical analysisApplied MathematicsInverse problemOptimal controlFinite element methodTwo-grid methodIdentification (information)Computational MathematicsRate of convergenceDistributed parameter systemError estimatesMathematicsJournal of Computational and Applied Mathematics
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An Interactive Multiple Objective Linear Programming Method for a Class of Underlying Nonlinear Utility Functions

1983

This paper develops a method for interactive multiple objective linear programming assuming an unknown pseudo concave utility function satisfying certain general properties. The method is an extension of our earlier method published in this journal (Zionts, S., Wallenius, J. 1976. An interactive programming method for solving the multiple criteria problem. Management Sci. 22 (6) 652–663.). Various technical problems present in predecessor versions have been resolved. In addition to presenting the supporting theory and algorithm, we discuss certain options in implementation and summarize our practical experience with several versions of the method.

Nonlinear systemClass (computer programming)Mathematical optimizationInteractive programmingLinear programmingMultiple objectiveStrategy and Managementmultiple criteria utility/preference: multi-attribute [programming]Function (mathematics)Extension (predicate logic)Management Science and Operations ResearchMathematicsLinear-fractional programmingManagement Science
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