Search results for "algorithm"

showing 10 items of 4887 documents

Occlusion-based estimation of independent multinomial random variables using occurrence and sequential information

2017

Abstract This paper deals with the relatively new field of sequence-based estimation in which the goal is to estimate the parameters of a distribution by utilizing both the information in the observations and in their sequence of appearance. Traditionally, the Maximum Likelihood (ML) and Bayesian estimation paradigms work within the model that the data, from which the parameters are to be estimated, is known, and that it is treated as a set rather than as a sequence. The position that we take is that these methods ignore, and thus discard, valuable sequence -based information, and our intention is to obtain ML estimates by “extracting” the information contained in the observations when perc…

Sequential estimationBayes estimatorSequenceComputer scienceMaximum likelihood02 engineering and technologycomputer.software_genre01 natural sciencesBinomial distributionCardinalityArtificial IntelligenceControl and Systems Engineering0103 physical sciences0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingMultinomial distributionData miningElectrical and Electronic Engineering010306 general physicsAlgorithmRandom variablecomputerEngineering Applications of Artificial Intelligence
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Mutual nonlinear prediction as a tool to evaluate coupling strength and directionality in bivariate time series: Comparison among different strategie…

2008

We compare the different existing strategies of mutual nonlinear prediction regarding their ability to assess the coupling strength and directionality of the interactions in bivariate time series. Under the common framework of $k$-nearest neighbor local linear prediction, we test three approaches based on cross prediction, mixed prediction, and predictability improvement. The measures of interdependence provided by these approaches are first evaluated on short realizations of bivariate time series generated by coupled Henon models, investigating also the effects of noise. The usefulness of the three mutual nonlinear prediction schemes is then assessed in a common physiological application d…

Series (mathematics)Computer scienceBivariate analysisCondensed Matter PhysicSynchronizationk-nearest neighbors algorithmNoisePhysics and Astronomy (all)StatisticsSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaPredictabilityTime seriesAlgorithmMathematical PhysicsInterpretabilityStatistical and Nonlinear Physic
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A comparison between a two feedback control loop and a reinforcement learning algorithm for compliant low-cost series elastic actuators

2020

Highly-compliant elastic actuators have become progressively prominent over the last years for a variety of robotic applications. With remarkable shock tolerance, elastic actuators are appropriate for robots operating in unstructured environments. In accordance with this trend, a novel elastic actuator was recently designed by our research group for Serpens, a low-cost, open-source and highly-compliant multi-purpose modular snake robot. To control the newly designed elastic actuators of Serpens, a two-feedback loops position control algorithm was proposed. The inner controller loop is implemented as a model reference adaptive controller (MRAC), while the outer control loop adopts a fuzzy pr…

Series (mathematics)Computer sciencebusiness.industryFeedback controlRoboticsLoop (topology)Computer Science::RoboticsVDP::Teknologi: 500Control theoryReinforcement learningArtificial intelligenceReinforcement learning algorithmActuatorbusiness
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Quantifying the complexity of short-term heart period variability through K nearest neighbor local linear prediction

2008

The complexity of short-term heart period (HP) variability was quantified exploiting the paradigm that associates the degree of unpredictability of a time series to its dynamical complexity. Complexity was assessed through k-nearest neighbor local linear prediction. A proper selection of the parameter k allowed us to perform either linear or nonlinear prediction, and the comparison of the two approaches to infer the presence of nonlinear dynamics. The method was validated on simulations reproducing linear and nonlinear time series with varying levels of predictability. It was then applied to HP variability series measured from healthy subjects during head-up tilt test, showing that short-te…

Series (mathematics)Degree (graph theory)Computer Science Applications1707 Computer Vision and Pattern Recognitionk-nearest neighbors algorithmTerm (time)Nonlinear systemPosition (vector)Control theorySettore ING-INF/06 - Bioingegneria Elettronica E InformaticaComputer Science Applications1707 Computer Vision and Pattern Recognition; Cardiology and Cardiovascular MedicineTime seriesPredictabilityCardiology and Cardiovascular MedicineAlgorithmMathematics
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A new interpretation and practical aspects of the direct-methods modulus sum function. VIII

2001

Since the first publication of the direct-methods modulus sum function [Rius (1993). Acta Cryst. A49, 406-409], the application of this function to a variety of situations has been shown in a series of seven subsequent papers. In this way, much experience about this function and its practical use has been gained. It is thought by the authors that it is now the right moment to publish a more complete study of this function which also considers most of this practical knowledge. The first part of the study relates, thanks to a new interpretation, this function to other existing phase-refinement functions, while the second shows, with the help of test calculations on a selection of crystal stru…

Series (mathematics)Direct methodProteinsTangentField (mathematics)Function (mathematics)Biomechanical PhenomenaInterpretation (model theory)Moment (mathematics)Structural BiologyDirect methodsCalculusCrystallizationAlgorithmsMathematicsActa Crystallographica Section A Foundations of Crystallography
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Segmentation algorithm for non-stationary compound Poisson processes

2010

We introduce an algorithm for the segmentation of a class of regime switching processes. The segmentation algorithm is a non parametric statistical method able to identify the regimes (patches) of a time series. The process is composed of consecutive patches of variable length. In each patch the process is described by a stationary compound Poisson process, i.e. a Poisson process where each count is associated with a fluctuating signal. The parameters of the process are different in each patch and therefore the time series is non-stationary. Our method is a generalization of the algorithm introduced by Bernaola-Galván, et al. [Phys. Rev. Lett. 87, 168105 (2001)]. We show that the new algori…

Series (mathematics)GeneralizationEconophysicsProcess (computing)Nonparametric statisticsStochastic processes Statistics Financial markets EconophysicsStochastic processeFinancial marketCondensed Matter PhysicsPoisson distribution01 natural sciencesSignal010305 fluids & plasmasElectronic Optical and Magnetic Materialssymbols.namesake0103 physical sciencesCompound Poisson processsymbolsSegmentation010306 general physicsAlgorithmStatisticMathematicsThe European Physical Journal B
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Selection of the Best Subset of Variables in Regression and Time Series Models

2009

The problem of variable selection is one of the most pervasive model selection problems in statistical applications. Often referred to as the problem of subset selection, it arises when one wants to model the relationship between a variable of interest and a subset of potential explanatory variables or predictors, but there is uncertainty about which subset to use. Several papers have dealt with various aspects of the problem but it appears that the typical regression user has not benefited appreciably. One reason for the lack of resolution of the problem is the fact that it is has not been well defined. Indeed, it is apparent that there is not a single problem, but rather several problems …

Series (mathematics)StatisticsDesign matrixErrors-in-variables modelsRegression analysisCross-sectional regressionSelection (genetic algorithm)RegressionMathematics
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An effective opportunistic maintenance policy for a global service

2010

The aim of the present paper is to develop a model for an effective maintenance policy with refer to a global service contract between a services provider company and a company for the waste management. The contract requires, with fixed performance levels of the service, the supplying of a mandatory set of maintenance services on a set of waste compactors vehicles of the outsourcer company. In particular, the service provider (SP) must perform corrective maintenance actions and the replacement of the fault parts. The tackled problem concerns the determination of an effective opportunistic maintenance policy in order to assure the required service performance levels at the minimum global mai…

Service (business)Service qualityEngineeringCorrective maintenanceOperations researchbusiness.industryService level requirementService providerPartition (database)Order (business)Genetic algorithmcorrective maintenancebusinessglobal service contractseries systemSettore ING-IND/16 - Tecnologie E Sistemi Di LavorazioneOpportunistic maintenanceInternational Journal of Services Sciences
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GPCALMA: A Grid-based tool for mammographic screening

2005

The next generation of High Energy Physics (HEP) experiments requires a GRID approach to a distributed computing system and the associated data management: the key concept is the Virtual Organisation (VO), a group of distributed users with a common goal and the will to share their resources. A similar approach is being applied to a group of Hospitals which joined the GPCALMA project (Grid Platform for Computer Assisted Library for MAmmography), which will allow common screening programs for early diagnosis of breast and, in the future, lung cancer. HEP techniques come into play in writing the application code, which makes use of neural networks for the image analysis and proved to be useful…

Service (systems architecture)InternationalityDatabases FactualMedical Records Systems ComputerizedTeleradiologyVirtual organizationComputer scienceGrid; Mammogram; Screening; Virtual organizationFOS: Physical sciencesBreast NeoplasmsHealth InformaticsTeleradiologycomputer.software_genregridSet (abstract data type)User-Computer InterfaceHealth Information ManagementmammogramHumansDiagnosis Computer-AssistedProgram DevelopmentAdvanced and Specialized NursingInternetbusiness.industryscreeningGridPhysics - Medical PhysicsEuropeSystems IntegrationRadiology Information SystemsItalyKey (cryptography)Database Management SystemsSystem integrationFemaleThe InternetMedical Physics (physics.med-ph)Data miningvirtual organizationbusinesscomputerAlgorithmsMammography
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A genetic approach for adding QoS to distributed virtual environments

2007

Distributed virtual environment (DVE) systems have been designed last years as a set of distributed servers. These systems allow a large number of remote users to share a single 3D virtual scene. In order to provide quality of service in a DVE system, clients should be properly assigned to servers taking into account system throughput and system latency. The latter one is composed of both network and computational delays. This highly complex problem is known as the quality of service (QoS) problem. In this paper, we study the implementation of a genetic algorithm (GA) for solving the QoS problem in DVE systems. Performance evaluation results show that, due to its ability of both finding goo…

Service qualityComputer Networks and CommunicationsSearch algorithmVirtual machineComputer scienceDistributed computingQuality of serviceServerReal-time computingGenetic algorithmShortest path problemcomputer.software_genrecomputerComputer Communications
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