Search results for "Simulation."

showing 10 items of 4779 documents

Nonlinearities and Adaptation of Color Vision from Sequential Principal Curves Analysis

2016

Mechanisms of human color vision are characterized by two phenomenological aspects: the system is nonlinear and adaptive to changing environments. Conventional attempts to derive these features from statistics use separate arguments for each aspect. The few statistical explanations that do consider both phenomena simultaneously follow parametric formulations based on empirical models. Therefore, it may be argued that the behavior does not come directly from the color statistics but from the convenient functional form adopted. In addition, many times the whole statistical analysis is based on simplified databases that disregard relevant physical effects in the input signal, as, for instance…

FOS: Computer and information sciencesColor visionComputer scienceCognitive NeuroscienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONStandard illuminantMachine Learning (stat.ML)Models BiologicalArts and Humanities (miscellaneous)Statistics - Machine LearningPsychophysicsHumansLearningComputer SimulationChromatic scaleParametric statisticsPrincipal Component AnalysisColor VisionNonlinear dimensionality reductionAdaptation PhysiologicalNonlinear systemNonlinear DynamicsFOS: Biological sciencesQuantitative Biology - Neurons and CognitionMetric (mathematics)A priori and a posterioriNeurons and Cognition (q-bio.NC)AlgorithmColor PerceptionPhotic Stimulation
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Kernel methods and their derivatives: Concept and perspectives for the earth system sciences.

2020

Kernel methods are powerful machine learning techniques which implement generic non-linear functions to solve complex tasks in a simple way. They Have a solid mathematical background and exhibit excellent performance in practice. However, kernel machines are still considered black-box models as the feature mapping is not directly accessible and difficult to interpret.The aim of this work is to show that it is indeed possible to interpret the functions learned by various kernel methods is intuitive despite their complexity. Specifically, we show that derivatives of these functions have a simple mathematical formulation, are easy to compute, and can be applied to many different problems. We n…

FOS: Computer and information sciencesComputer Science - Machine LearningSupport Vector MachineTheoretical computer scienceComputer scienceEntropyKernel FunctionsNormal Distribution0211 other engineering and technologies02 engineering and technologyMachine Learning (cs.LG)Machine LearningStatistics - Machine LearningSimple (abstract algebra)0202 electrical engineering electronic engineering information engineeringOperator TheoryData ManagementMultidisciplinaryGeographyApplied MathematicsSimulation and ModelingQRDensity estimationKernel methodKernel (statistics)Physical SciencessymbolsMedicine020201 artificial intelligence & image processingAlgorithmsResearch ArticleComputer and Information SciencesScienceMachine Learning (stat.ML)Research and Analysis MethodsKernel MethodsKernel (linear algebra)symbols.namesakeArtificial IntelligenceSupport Vector MachinesHumansEntropy (information theory)Computer SimulationGaussian process021101 geological & geomatics engineeringData VisualizationCorrectionRandom VariablesFunction (mathematics)Probability TheorySupport vector machineAlgebraPhysical GeographyLinear AlgebraEarth SciencesEigenvectorsRandom variableMathematicsEarth SystemsPLoS ONE
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Investigating Low Level Protocols for Wireless Body Sensor Networks

2016

The rapid development of medical sensors has increased the interest in Wireless Body Area Network (WBAN) applications where physiological data from the human body and its environment is gathered, monitored, and analyzed to take the proper measures. In WBANs, it is essential to design MAC protocols that ensure adequate Quality of Service (QoS) such as low delay and high scalability. This paper investigates Medium Access Control (MAC) protocols used in WBAN, and compares their performance in a high traffic environment. Such scenario can be induced in case of emergency for example, where physiological data collected from all sensors on human body should be sent simultaneously to take appropria…

FOS: Computer and information sciencesComputer scienceComputer Science - Information TheoryTime division multiple accessAccess control[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]02 engineering and technology[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]Body area network0202 electrical engineering electronic engineering information engineeringWirelessProtocol (science)business.industryInformation Theory (cs.IT)Quality of service020208 electrical & electronic engineeringComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS020206 networking & telecommunications[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationComputer Science - Distributed Parallel and Cluster Computing[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Scalability[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]Distributed Parallel and Cluster Computing (cs.DC)[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]businessWireless sensor networkComputer network
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Efficient and accurate monitoring of the depth information in a Wireless Multimedia Sensor Network based surveillance

2017

International audience; Abstract—Wireless Multimedia Sensor Network (WMSN) is a promising technology capturing rich multimedia data like audio and video, which can be useful to monitor an environment under surveillance. However, many scenarios in real time monitoring requires 3D depth information. In this research work, we propose to use the disparity map that is computed from two or multiple images, in order to monitor the depth information in an object or event under surveillance using WMSN. Our system is based on distributed wireless sensors allowing us to notably reduce the computational time needed for 3D depth reconstruction, thus permitting the success of real time solutions. Each pa…

FOS: Computer and information sciencesComputer scienceComputer Vision and Pattern Recognition (cs.CV)Real-time computingComputer Science - Computer Vision and Pattern Recognition[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]02 engineering and technologyImage (mathematics)[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]0202 electrical engineering electronic engineering information engineeringWirelessWireless multimedia sensor networksEvent (computing)business.industryNode (networking)Bandwidth (signal processing)020206 networking & telecommunicationsObject (computer science)[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationStereopsis[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA][INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]020201 artificial intelligence & image processing[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]business2017 Sensors Networks Smart and Emerging Technologies (SENSET)
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Critical comments on EEG sensor space dynamical connectivity analysis

2019

Many different analysis techniques have been developed and applied to EEG recordings that allow one to investigate how different brain areas interact. One particular class of methods, based on the linear parametric representation of multiple interacting time series, is widely used to study causal connectivity in the brain. However, the results obtained by these methods should be interpreted with great care. The goal of this paper is to show, both theoretically and using simulations, that results obtained by applying causal connectivity measures on the sensor (scalp) time series do not allow interpretation in terms of interacting brain sources. This is because (1) the channel locations canno…

FOS: Computer and information sciencesComputer scienceSocial SciencesTransfer functionStatistics - Applications050105 experimental psychology03 medical and health sciences0302 clinical medicinegranger causalityMVARHumansApplications (stat.AP)Computer Simulation0501 psychology and cognitive sciencesRadiology Nuclear Medicine and imagingBrain connectivityEEGTime domainSpurious relationshipRepresentation (mathematics)Mixing (physics)Parametric statisticsBrain MappingRadiological and Ultrasound TechnologySeries (mathematics)05 social sciencesbrain connectivitysource modellingElectroencephalographyNeurologyFOS: Biological sciencesFrequency domainQuantitative Biology - Neurons and CognitionSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaGranger causalityDirected transfer functionNeurons and Cognition (q-bio.NC)Neurology (clinical)AnatomyAlgorithm030217 neurology & neurosurgery
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Impact of LTE’s Periodic Interference on Heterogeneous Wi-Fi Transmissions

2018

The problem of Wi-Fi and LTE coexistence has been significantly debated in the last years, with the emergence of LTE extensions enabling the utilization of unlicensed spectrum for carrier aggregation. Rather than focusing on the problem of resource sharing between the two technologies, in this paper, we study the effects of LTE's structured transmissions on the Wi-Fi random access protocol. We show how the scheduling of periodic LTE transmissions modifies the behavior of 802.11's distributed coordination function (DCF), leading to a degradation of Wi-Fi performance, both in terms of channel utilization efficiency and in terms of channel access fairness. We also discuss the applicability and…

FOS: Computer and information sciencesComputer scienceThroughput02 engineering and technologyDistributed coordination functionSpectrum managementAnalytical modelScheduling (computing)Computer Science - Networking and Internet ArchitectureC.2.0C.2.50202 electrical engineering electronic engineering information engineeringLong Term EvolutionWireless fidelityElectrical and Electronic EngineeringProbabilitySensorNetworking and Internet Architecture (cs.NI)business.industrySettore ING-INF/03 - TelecomunicazioniComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS020206 networking & telecommunicationsComputer Science Applications1707 Computer Vision and Pattern RecognitionThroughput91A06 91A10 91A80Computer Science ApplicationsShared resourceModeling and SimulationbusinessC.2.0; C.2.5InterferenceRandom accessComputer networkCommunication channel
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A Comprehensive Utility Function for Resource Allocation in Mobile Edge Computing

2020

In mobile edge computing (MEC), one of the important challenges is how much resources of which mobile edge server (MES) should be allocated to which user equipment (UE). The existing resource allocation schemes only consider CPU as the requested resource and assume utility for MESs as either a random variable or dependent on the requested CPU only. This paper presents a novel comprehensive utility function for resource allocation in MEC. The utility function considers the heterogeneous nature of applications that a UE offloads to MES. The proposed utility function considers all important parameters, including CPU, RAM, hard disk space, required time, and distance, to calculate a more realis…

FOS: Computer and information sciencesComputer sciencemedia_common.quotation_subjectG.3Cloud computingComputer Science - Networking and Internet ArchitectureC.2.3BiomaterialsC.2.1Resource (project management)Electrical and Electronic EngineeringFunction (engineering)media_commonNetworking and Internet Architecture (cs.NI)Mobile edge computingbusiness.industryEnergy consumptionComputer Science ApplicationsTask (computing)User equipmentMechanics of MaterialsModeling and SimulationResource allocationG.3; C.2.3; C.2.1business46FxxComputer networkComputers, Materials & Continua
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Upperbounds on the probability of finding marked connected components using quantum walks

2019

Quantum walk search may exhibit phenomena beyond the intuition from a conventional random walk theory. One of such examples is exceptional configuration phenomenon -- it appears that it may be much harder to find any of two or more marked vertices, that if only one of them is marked. In this paper, we analyze the probability of finding any of marked vertices in such scenarios and prove upper bounds for various sets of marked vertices. We apply the upper bounds to large collection of graphs and show that the quantum search may be slow even when taking real-world networks.

FOS: Computer and information sciencesDiscrete Mathematics (cs.DM)FOS: Physical sciences01 natural sciencesUpper and lower bounds010305 fluids & plasmasTheoretical Computer Science0103 physical sciencesFOS: MathematicsMathematics - CombinatoricsQuantum walkElectrical and Electronic Engineering010306 general physicsQuantum computerMathematicsDiscrete mathematicsConnected componentQuantum PhysicsStatistical and Nonlinear PhysicsRandom walkQuantum searchElectronic Optical and Magnetic MaterialsModeling and SimulationSignal ProcessingCombinatorics (math.CO)Quantum Physics (quant-ph)Stationary stateComputer Science - Discrete Mathematics
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Parity Oblivious d-Level Random Access Codes and Class of Noncontextuality Inequalities

2016

One of the fundamental results in quantum foundations is the Kochen-Specker no-go theorem. For the quantum theory, the no-go theorem excludes the possibility of a class of hidden variable models where value attribution is context independent. Recently, the notion of contextuality has been generalized for different operational procedures and it has been shown that preparation contextuality of mixed quantum states can be a useful resource in an information-processing task called parity-oblivious multiplexing. Here, we introduce a new class of information processing tasks, namely d-level parity oblivious random access codes and obtain bounds on the success probabilities of performing such task…

FOS: Computer and information sciencesExistential quantificationComputer Science - Information TheoryFOS: Physical sciences01 natural sciences010305 fluids & plasmasTheoretical Computer ScienceQuantum state0103 physical sciencesElectrical and Electronic Engineering010306 general physicsQuantumMathematicsQuantum computerDiscrete mathematicsQuantum PhysicsInformation Theory (cs.IT)Statistical and Nonlinear PhysicsParity (physics)Electronic Optical and Magnetic MaterialsKochen–Specker theoremModeling and SimulationSignal ProcessingOnticQuantum Physics (quant-ph)Random access
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Fractional generalized cumulative entropy and its dynamic version

2021

Following the theory of information measures based on the cumulative distribution function, we propose the fractional generalized cumulative entropy, and its dynamic version. These entropies are particularly suitable to deal with distributions satisfying the proportional reversed hazard model. We study the connection with fractional integrals, and some bounds and comparisons based on stochastic orderings, that allow to show that the proposed measure is actually a variability measure. The investigation also involves various notions of reliability theory, since the considered dynamic measure is a suitable extension of the mean inactivity time. We also introduce the empirical generalized fract…

FOS: Computer and information sciencesExponential distributionComputer Science - Information TheoryMathematics - Statistics TheoryStatistics Theory (math.ST)01 natural sciencesMeasure (mathematics)010305 fluids & plasmas0103 physical sciencesFOS: MathematicsApplied mathematicsAlmost surelyCumulative entropy; Fractional calculus; Stochastic orderings; EstimationEntropy (energy dispersal)010306 general physicsStochastic orderingsMathematicsCentral limit theoremNumerical AnalysisInformation Theory (cs.IT)Applied MathematicsCumulative distribution functionProbability (math.PR)Fractional calculusEmpirical measureFractional calculusModeling and SimulationEstimationCumulative entropyMathematics - ProbabilityCommunications in Nonlinear Science and Numerical Simulation
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