Search results for "Linear system"

showing 10 items of 1558 documents

Efficient High-Order Iterative Methods for Solving Nonlinear Systems and Their Application on Heat Conduction Problems

2017

[EN] For solving nonlinear systems of big size, such as those obtained by applying finite differences for approximating the solution of diffusion problem and heat conduction equations, three-step iterative methods with eighth-order local convergence are presented. The computational efficiency of the new methods is compared with those of some known ones, obtaining good conclusions, due to the particular structure of the iterative expression of the proposed methods. Numerical comparisons are made with the same existing methods, on standard nonlinear systems and a nonlinear one-dimensional heat conduction equation by transforming it in a nonlinear system by using finite differences. From these…

MultidisciplinaryArticle SubjectGeneral Computer ScienceIterative methodMathematical analysisFinite differenceRelaxation (iterative method)010103 numerical & computational mathematics02 engineering and technologyThermal conduction01 natural sciencesExpression (mathematics)lcsh:QA75.5-76.95Local convergenceNonlinear system0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingHeat equationlcsh:Electronic computers. Computer science0101 mathematicsMATEMATICA APLICADAMathematicsComplexity
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On Discovering Low Order Models in Biochemical Reaction Kinetics

2007

We develop a method by which a large number of differential equations representing biochemical reaction kinetics may be represented by a smaller number of differential equations. The basis of our technique is a conjecture that the high dimension equations of biochemical kinetics, which involve reaction terms of specific forms, are actually implementing a low dimension system whose behavior requires right hand sides that can not be biochemically implemented. For systems that satisfy this conjecture, we develop a simple approximation scheme based on multilinear algebra that extracts the low dimensional system from simulations of the high dimension system. We demonstrate this technique on a st…

Multilinear algebraNonlinear systemBasis (linear algebra)Dimension (vector space)Settore ING-INF/04 - AutomaticaSimple (abstract algebra)Differential equationMathematical analysisChaoticApplied mathematicsDimensional modelingKinetic theory Nonlinear equations Polynomials Differential equationsMathematics
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Cyclic response of masonry infilled RC frames: Experimental results and simplified modeling

2014

The recent large interest in nonlinear seismic analysis methods, static and dynamic, has required proper strategies of modeling based on reliable, and at the same time easy to use, constitutive laws for the structural elements. Regarding the behavior of framed structures, special attention has to be devoted to infills because of the key role they play in modifying overall stiffness, strength and ductility under seismic excitation. Pointing out the attention on this topic the paper discusses a criteria for modeling the structural behavior of infills based on a macromodeling approach, that is to say on the substitution of infills with diagonal pin jointed struts. Is here shown how multilinear…

Multilinear mapEngineeringInfilled framesMasonry infillsbusiness.industryInfilled frames; Masonry infills; Cyclic behavior; Pivot hysteretic model; Equivalent strut.DiagonalSoil ScienceStiffnessStructural engineeringInfilled frames Masonry infills Cyclic behavior Pivot hysteretic model Equivalent strut.MasonryGeotechnical Engineering and Engineering GeologyFinite element methodSeismic analysisCyclic behaviorSettore ICAR/09 - Tecnica Delle CostruzioniNonlinear systemmedicineEquivalent strutPivot hysteretic modelmedicine.symptombusinessDuctilityCivil and Structural Engineering
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Nonlinear analysis of classical phase-locked loops in signal's phase space

2014

Abstract Discovery of undesirable hidden oscillations, which cannot be found by the standard simulation, in phase-locked loop (PLL) showed the importance of consideration of nonlinear models and development of rigorous analytical methods for their analysis. In this paper for various signal waveforms, analytical computation of multiplier/mixer phase-detector characteristics is demonstrated, and nonlinear dynamical model of classical analog PLL is derived. Approaches to the rigorous nonlinear analysis of classical analog PLL are discussed.

Multiplier (Fourier analysis)Phase-locked loopNonlinear systemControl theoryPhase spaceComputationHardware_INTEGRATEDCIRCUITSWaveformPhase detector characteristicHardware_PERFORMANCEANDRELIABILITYMultistabilityMathematicsIFAC Proceedings Volumes
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Multiset Kernel CCA for multitemporal image classification

2013

The analysis of multitemporal remote sensing images is becoming an increasingly important problem because of the upcoming scenario of multispectral satellite constellations monitoring our Planet. Algorithms that can analyze such amount of heterogeneous information are necessary. While linear techniques have been extensively deployed, this work considers a kernel method that finds nonlinear correlations between all image sources and the class labels. We introduce in this context the Kernel Canonical Correlation Analysis (KCCA) to exploit the wealth of temporal image information and to handle nonlinear relations in a natural way via kernels. To achieve this goal, we use the generalization of …

MultisetContextual image classificationbusiness.industryMultispectral imagePattern recognitionSupport vector machineNonlinear systemKernel methodKernel (image processing)Artificial intelligenceTime seriesbusinessMathematicsRemote sensingMultiTemp 2013: 7th International Workshop on the Analysis of Multi-temporal Remote Sensing Images
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On the interplay between multiscaling and stocks dependence

2019

We find a nonlinear dependence between an indicator of the degree of multiscaling of log-price time series of a stock and the average correlation of the stock with respect to the other stocks traded in the same market. This result is a robust stylized fact holding for different financial markets. We investigate this result conditional on the stocks' capitalization and on the kurtosis of stocks' log-returns in order to search for possible confounding effects. We show that a linear dependence with the logarithm of the capitalization and the logarithm of kurtosis does not explain the observed stylized fact, which we interpret as being originated from a deeper relationship.

Multivariate propertiePhysics::Physics and SocietyStatistical Finance (q-fin.ST)050208 financeUnivariate properties05 social sciencesQuantitative Finance - Statistical FinanceFOS: Economics and businessMultiscalingNonlinear systemUnivariate propertieComputer Science::Computational Engineering Finance and Science0502 economics and businessEconometrics050207 economicsDependenceGeneral Economics Econometrics and FinanceFinanceStock (geology)Mathematics
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MuTE: a MATLAB toolbox to compare established and novel estimators of the multivariate transfer entropy.

2014

A challenge for physiologists and neuroscientists is to map information transfer between components of the systems that they study at different scales, in order to derive important knowledge on structure and function from the analysis of the recorded dynamics. The components of physiological networks often interact in a nonlinear way and through mechanisms which are in general not completely known. It is then safer that the method of choice for analyzing these interactions does not rely on any model or assumption on the nature of the data and their interactions. Transfer entropy has emerged as a powerful tool to quantify directed dynamical interactions. In this paper we compare different ap…

Multivariate statisticsInformation transferTheoretical computer scienceComputer scienceEntropyInformation TheorySocial SciencesCAUSALITYMedicine (all); Biochemistry Genetics and Molecular Biology (all); Agricultural and Biological Sciences (all)BioinformaticsMedicine and Health SciencesEntropy (energy dispersal)MultidisciplinaryEntropy (statistical thermodynamics)Medicine (all)QSoftware DevelopmentREstimatorSoftware EngineeringElectroencephalographyCausalityNeurologyCardiovascular DiseasesProbability distributionMedicineAlgorithmsResearch ArticleComputer ModelingComputer and Information SciencesScienceCardiologyProbability density functionEntropy (classical thermodynamics)Artificial IntelligenceLinear regressionEntropy (information theory)HumansComputer SimulationEntropy (arrow of time)Conditional entropyBiochemistry Genetics and Molecular Biology (all)EpilepsyBiology and Life SciencesModels TheoreticalMODELNonlinear systemAgricultural and Biological Sciences (all)ROC CurveINFORMATION-TRANSFERSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaCognitive ScienceTransfer entropySoftwareEntropy (order and disorder)NeurosciencePLoS ONE
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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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Non-uniform multivariate embedding to assess the information transfer in cardiovascular and cardiorespiratory variability series

2012

The complexity of the short-term cardiovascular control prompts for the introduction of multivariate (MV) nonlinear time series analysis methods to assess directional interactions reflecting the underlying regulatory mechanisms. This study introduces a new approach for the detection of nonlinear Granger causality in MV time series, based on embedding the series by a sequential, non-uniform procedure, and on estimating the information flow from one series to another by means of the corrected conditional entropy. The approach is validated on short realizations of linear stochastic and nonlinear deterministic processes, and then evaluated on heart period, systolic arterial pressure and respira…

Multivariate statisticsSupine positionMultivariate analysisQuantitative Biology::Tissues and OrgansTime delay embeddingPhysics::Medical PhysicsPostureBlood PressureHealth InformaticsCardiovascular Physiological PhenomenaGranger causalityPosition (vector)StatisticsHumansCardiovascular interactionMathematicsConditional entropySeries (mathematics)RespirationModels CardiovascularReproducibility of ResultsSignal Processing Computer-AssistedComputer Science Applications1707 Computer Vision and Pattern RecognitionComputer Science ApplicationsNonlinear systemNonlinear DynamicsMultivariate AnalysisSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaGranger causalityMultivariate time serieConditional entropyAlgorithmAlgorithms
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Detecting nonlinear causal interactions between dynamical systems by non-uniform embedding of multiple time series.

2010

This study introduces a new approach for the detection of nonlinear Granger causality between dynamical systems. The approach is based on embedding the multivariate (MV) time series measured from the systems X and Y by means of a sequential, non-uniform procedure, and on using the corrected conditional entropy (CCE) as unpredictability measure. The causal coupling from X to Y is quantified as the relative decrease of CCE measured after allowing the series of X to enter the embedding procedure for the description of Y. The ability of the approach to quantify nonlinear causality is assessed on MV time series measured from simulated dynamical systems with unidirectional coupling (the Rössler-…

Multivariate statisticsTime FactorsDynamical systems theoryEntropyBiomedical EngineeringMachine learningcomputer.software_genreHumansStatistical physicsTime seriesMathematicsVisual CortexConditional entropyCouplingSignal processingbusiness.industryMagnetoencephalographyReproducibility of ResultsSignal Processing Computer-AssistedSomatosensory CortexNonlinear systemNonlinear DynamicsSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaMultivariate AnalysisEmbeddingArtificial intelligencebusinesscomputer
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