Search results for "Nonlinear dynamic"

showing 10 items of 158 documents

Upport vector machines for nonlinear kernel ARMA system identification.

2006

Nonlinear system identification based on support vector machines (SVM) has been usually addressed by means of the standard SVM regression (SVR), which can be seen as an implicit nonlinear autoregressive and moving average (ARMA) model in some reproducing kernel Hilbert space (RKHS). The proposal of this letter is twofold. First, the explicit consideration of an ARMA model in an RKHS (SVM-ARMA 2k) is proposed. We show that stating the ARMA equations in an RKHS leads to solving the regularized normal equations in that RKHS, in terms of the autocorrelation and cross correlation of the (nonlinearly) transformed input and output discrete time processes. Second, a general class of SVM-based syste…

Computer Science::Machine LearningStatistics::TheoryComputer Networks and CommunicationsBiomedical signal processingInformation Storage and RetrievalMachine learningcomputer.software_genrePattern Recognition AutomatedStatistics::Machine LearningArtificial IntelligenceApplied mathematicsStatistics::MethodologyAutoregressive–moving-average modelComputer SimulationMathematicsTelecomunicacionesHardware_MEMORYSTRUCTURESSupport vector machinesModels StatisticalNonlinear system identificationbusiness.industryAutocorrelationSystem identificationSignal Processing Computer-AssistedGeneral MedicineComputer Science ApplicationsSupport vector machineNonlinear systemKernelAutoregressive modelNonlinear DynamicsARMA modelling3325 Tecnología de las TelecomunicacionesArtificial intelligenceNeural Networks ComputerbusinesscomputerSoftwareAlgorithmsReproducing kernel Hilbert spaceIEEE transactions on neural networks
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Estimation of confidence limits for descriptive indexes derived from autoregressive analysis of time series: Methods and application to heart rate va…

2017

The growing interest in personalized medicine requires making inferences from descriptive indexes estimated from individual recordings of physiological signals, with statistical analyses focused on individual differences between/within subjects, rather than comparing supposedly homogeneous cohorts. To this end, methods to compute confidence limits of individual estimates of descriptive indexes are needed. This study introduces numerical methods to compute such confidence limits and perform statistical comparisons between indexes derived from autoregressive (AR) modeling of individual time series. Analytical approaches are generally not viable, because the indexes are usually nonlinear funct…

Computer and Information SciencesStatistical methodsConfidence Intervals; Humans; Monte Carlo Method; Regression Analysis; Heart Rate; Biochemistry Genetics and Molecular Biology (all); Agricultural and Biological Sciences (all)EntropyCardiologylcsh:MedicineResearch and Analysis MethodsSystems ScienceRegression AnalysiHeart RateConfidence IntervalsMedicine and Health SciencesHumanslcsh:ScienceBiochemistry Genetics and Molecular Biology (all)Simulation and ModelingPhysicslcsh:RProbability TheoryMonte Carlo methodAgricultural and Biological Sciences (all)Nonlinear DynamicsWhite NoiseSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaPhysical SciencesSignal ProcessingMathematical and statistical techniquesThermodynamicsEngineering and TechnologyRegression Analysislcsh:QConfidence IntervalMathematicsStatistics (Mathematics)HumanResearch ArticleStatistical DistributionsPLoS ONE
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Are nonlinear model-free conditional entropy approaches for the assessment of cardiac control complexity superior to the linear model-based one?

2016

Objective : We test the hypothesis that the linear model-based (MB) approach for the estimation of conditional entropy (CE) can be utilized to assess the complexity of the cardiac control in healthy individuals. Methods : An MB estimate of CE was tested in an experimental protocol (i.e., the graded head-up tilt) known to produce a gradual decrease of cardiac control complexity as a result of the progressive vagal withdrawal and concomitant sympathetic activation. The MB approach was compared with traditionally exploited nonlinear model-free (MF) techniques such as corrected approximate entropy, sample entropy, corrected CE, two k -nearest-neighbor CE procedures and permutation CE. Electroca…

Computer scienceEntropyBiomedical EngineeringSensitivity and Specificity01 natural sciencesApproximate entropy03 medical and health sciencesEntropy (classical thermodynamics)0302 clinical medicineHeart RateHeart Rate Determination0103 physical sciencesStatisticsHumansEntropy (information theory)Autonomic nervous systemComputer SimulationEntropy (energy dispersal)010306 general physicsEntropy (arrow of time)Heart rate variabilityFeedback PhysiologicalConditional entropyEntropy (statistical thermodynamics)Head-up tiltModels CardiovascularLinear modelCardiovascular regulationReproducibility of ResultsHeartStatistical modelMutual informationSample entropyMutual informationNonlinear DynamicsConcomitantSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaLinear ModelsAlgorithmRandom variableAlgorithms030217 neurology & neurosurgeryEntropy (order and disorder)
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Advanced computation in cardiovascular physiology: New challenges and opportunities

2021

Recent developments in computational physiology have successfully exploited advanced signal processing and artificial intelligence tools for predicting or uncovering characteristic features of physiological and pathological states in humans. While these advanced tools have demonstrated excellent diagnostic capabilities, the high complexity of these computational 'black boxes’ may severely limit scientific inference, especially in terms of biological insight about both physiology and pathological aberrations. This theme issue highlights current challenges and opportunities of advanced computational tools for processing dynamical data reflecting autonomic nervous system dynamics, with a speci…

Computer scienceGeneral MathematicsComputationGeneral Physics and AstronomyelectrocardiogramMachine learningcomputer.software_genreComputer-AssistedHeart RateArtificial IntelligenceHumansInterpretabilitySignal processingbusiness.industryDeep learningGeneral Engineeringheart rate variabilitydeep learningSignal Processing Computer-Assistedcardiology; deep learning; electrocardiogram; heart rate variability; interpretability; respiration; Heart Rate; Humans; Nonlinear Dynamics; Signal Processing Computer-Assisted; Algorithms; Artificial IntelligenceCardiovascular physiologyComputational physiologyNonlinear DynamicscardiologySignal ProcessingArtificial intelligencebusinessinterpretabilitycomputerrespirationAlgorithms
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Statistical geometric affinity in human brain electric activity

2007

10 pages, 9 figures.-- PACS nrs.: 87.19.La; 05.45.Tp.-- ISI Article Identifier: 000246890100105

Computer scienceModels NeurologicalNeurophysiologyElectroencephalographyInterpretation (model theory)[PACS] Time series analysis (nonlinear dynamical systems)LacunaritymedicineHumansComputer SimulationDiagnosis Computer-AssistedWakefulnessRepresentation (mathematics)ScalingEvoked PotentialsModels Statisticalmedicine.diagnostic_testbusiness.industry[PACS] Neuroscience (higher organisms)BrainPattern recognitionElectroencephalographyNeurophysiologyAmplitudeStatistical analysisData Interpretation StatisticalBioelectric phenomenaLacunarityAffine transformationArtificial intelligenceSleep StagesbusinessSleep
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Information-based detection of nonlinear Granger causality in multivariate processes via a nonuniform embedding technique

2010

We present an approach, framed in information theory, to assess nonlinear causality between the subsystems of a whole stochastic or deterministic dynamical system. The approach follows a sequential procedure for nonuniform embedding of multivariate time series, whereby embedding vectors are built progressively on the basis of a minimization criterion applied to the entropy of the present state of the system conditioned to its past states. A corrected conditional entropy estimator compensating for the biasing effect of single points in the quantized hyperspace is used to guarantee the existence of a minimum entropy rate at which to terminate the procedure. The causal coupling is detected acc…

Conditional entropyStatistics and ProbabilityStochastic ProcessesInformation transferEntropyInformation TheoryEstimatorElectroencephalographyCondensed Matter PhysicInformation theoryCardiovascular Physiological PhenomenaNonlinear DynamicsMultivariate AnalysisStatisticsSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaRespiratory Physiological PhenomenaEntropy (information theory)Applied mathematicsEmbeddingPredictabilityTime seriesMathematicsStatistical and Nonlinear Physic
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Spike train statistics for consonant and dissonant musical accords in a simple auditory sensory model

2010

The phenomena of dissonance and consonance in a simple auditory sensory model composed of three neurons are considered. Two of them, here so-called sensory neurons, are driven by noise and subthreshold periodic signals with different ratio of frequencies, and its outputs plus noise are applied synaptically to a third neuron, so-called interneuron. We present a theoretical analysis with a probabilistic approach to investigate the interspike intervals statistics of the spike train generated by the interneuron. We find that tones with frequency ratios that are considered consonant by musicians produce at the third neuron inter-firing intervals statistics densities that are very distinctive fro…

ConsonantNoise in the nervous system; Analytical theories; Sensor auditory systemStochastic ProcessesQuantitative Biology::Neurons and CognitionInterneuronSensory Receptor CellsSpike trainProbabilistic logicSensor auditory systemSensory systemNoise in the nervous systemConsonance and dissonanceModels BiologicalSettore FIS/03 - Fisica Della MateriaNoiseAnalytical theoriemedicine.anatomical_structureNonlinear DynamicsComputer Science::SoundStatisticsmedicineAuditory PerceptionSpike (software development)MathematicsProbability
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Stochastic linearization critically re-examined

1997

Abstract The stochastic linearization technique, widely used for the analysis of nonlinear dynamic systems subjected to random excitations, is revisited. It is shown that the standard procedure universally adopted for determining the so-called effective stiffness of the equivalent linear system is erroneous in all previous publications. Two error-free stochastic linearization techniques are elucidated, namely those based on (1) the force linearization and (2) energy linearization.

Control theoryLinearizationGeneral MathematicsApplied MathematicsLinear systemNonlinear dynamic systemsGeneral Physics and AstronomyStatistical and Nonlinear PhysicsFeedback linearizationEffective stiffnessEnergy (signal processing)Standard procedureMathematics
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Connectivity Influences on Nonlinear Dynamics in Weakly-Synchronized Networks: Insights from Rössler Systems, Electronic Chaotic Oscillators, Model a…

2019

Natural and engineered networks, such as interconnected neurons, ecological and social networks, coupled oscillators, wireless terminals and power loads, are characterized by an appreciable heterogeneity in the local connectivity around each node. For instance, in both elementary structures such as stars and complex graphs having scale-free topology, a minority of elements are linked to the rest of the network disproportionately strongly. While the effect of the arrangement of structural connections on the emergent synchronization pattern has been studied extensively, considerably less is known about its influence on the temporal dynamics unfolding within each node. Here, we present a compr…

Correlation dimensionCollective behaviornonlinear dynamicGeneral Computer ScienceComputer scienceNetwork topologyTopology01 natural sciencesnetwork topology010305 fluids & plasmasnode degreeRössler systemEntropy (classical thermodynamics)nonlinear dynamicschaotic transition0103 physical sciencesEntropy (information theory)Attractor dimensionGeneral Materials Sciencestructural connectivity010306 general physicsprediction errorstochastic dynamicsGeneral EngineeringSaito oscillatorelectronic chaotic oscillatorComplex networkNonlinear systemneuronal culturestochastic dynamicnodal strengthChaotic oscillatorscomplexityentropysynchronizationEntropy (order and disorder)
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Non-linear dynamics of alpha and theta rhythm: correlation dimensions and Lyapunov exponents from healthy subject's spontaneous EEG.

1997

The aim of the present paper was to analyze some non-linear dynamic properties of the resting EEG from healthy subjects under eyes closed conditions. For this purpose we digitally filtered the spontaneous EEG in the theta (3-8 Hz) and alpha frequency range (8-13 Hz) and considered these independent rhythms as signals from a deterministic system. Under certain conditions non-linear dynamic systems are able to generate deterministic chaos, which means that similar causes do not produce similar effects. This phenomenon is called sensitive dependence on initial conditions. From different lead positions (F3, F4, Cz, P3, P4, O1 and O2) we calculated the so-called correlation dimension D2, which i…

Correlation dimensionDegrees of freedom (physics and chemistry)Alpha (ethology)Lyapunov exponentElectroencephalographysymbols.namesakeRhythmReference ValuesPhysiology (medical)medicineHumansStatistical physicsTheta RhythmMathematicsCommunicationmedicine.diagnostic_testbusiness.industryGeneral NeuroscienceElectroencephalographyNonlinear systemAlpha RhythmNeuropsychology and Physiological PsychologyNonlinear DynamicssymbolsbusinessAlgorithmsDeterministic systemInternational journal of psychophysiology : official journal of the International Organization of Psychophysiology
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