Testing for nonlinearity in time series: the method of surrogate data
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Granger causality and information flow in multivariate processesImproved false nearest neighbor method to detect determinism in time series dataTransforming Clinical Data into Actionable Prognosis Models: Machine-Learning Framework and Field-Deployable App to Predict Outcome of Ebola PatientsMulti-Variate EEG Analysis as a Novel Tool to Examine Brain Responses to Naturalistic Music Stimuli.Illusions of visual motion elicited by electrical stimulation of human MT complexConstrained surrogate time series with preservation of the mean and variance structureTesting for nonlinearity in irregular fluctuations with long-term trendsImprovements to surrogate data methods for nonstationary time seriesMeasuring Global Economic Interdependence: A Hierarchical Network ApproachEEG-based automatic classification of 'awake' versus 'anesthetized' state in general anesthesia using Granger causalityA comprehensive study of the delay vector variance method for quantification of nonlinearity in dynamical systems.Bursting Neurons in the Hippocampal Formation Encode Features of LFP RhythmsECoG high gamma activity reveals distinct cortical representations of lyrics passages, harmonic and timbre-related changes in a rock song.Dynamic response signatures of a scaled model platform for floating wind turbines in an ocean wave basin.Temporal scaling of neural responses to compressed and dilated natural speech.Spectral convergence in tapping and physiological fluctuations: coupling and independence of 1/f noise in the central and autonomic nervous systems.Characterizing chaotic dynamics from simulations of large strain behavior of a granular material under biaxial compression.Modeling Individual Damped Linear Oscillator Processes with Differential Equations: Using Surrogate Data Analysis to Estimate the Smoothing ParameterA nonrandom dynamic component in the synaptic noise of a central neuronTracking time-varying causality and directionality of information flow using an error reduction ratio test with applications to electroencephalography data.Evaluation of physiologic complexity in time series using generalized sample entropy and surrogate data analysis.Integrated approach to the assessment of long range correlation in time series dataSurrogate data test for nonlinearity including nonmonotonic transformsGlobal cortical activity predicts shape of hand during grasping.Low-dimensional attractor for neural activity from local field potentials in optogenetic miceNonlinear phase desynchronization in human electroencephalographic data.Surrogate analysis of coherent multichannel data.Reconstructing embedding spaces of coupled dynamical systems from multivariate data.Surrogates for finding unstable periodic orbits in noisy data sets.Test your surrogate data before you test for nonlinearity.Statically transformed autoregressive process and surrogate data test for nonlinearity.Beamformer source analysis and connectivity on concurrent EEG and MEG data during voluntary movements.Don't bleach chaotic data.Dimension estimates and physiological data.Ocean rogue waves and their phase space dynamics in the limit of a linear interference modelWavelets and statistical analysis of functional magnetic resonance images of the human brain.Power-law dynamics in neuronal and behavioral data introduce spurious correlations.Change of the nature of a test when surrogate data are applied.Effects of data windows on the methods of surrogate data.Small-shuffle surrogate data: testing for dynamics in fluctuating data with trends.
P2860
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P2860
Testing for nonlinearity in time series: the method of surrogate data
description
im September 1992 veröffentlicher wissenschaftlicher Artikel
@de
wetenschappelijk artikel
@nl
наукова стаття, опублікована у вересні 1992
@uk
name
Testing for nonlinearity in time series: the method of surrogate data
@en
Testing for nonlinearity in time series: the method of surrogate data
@nl
type
label
Testing for nonlinearity in time series: the method of surrogate data
@en
Testing for nonlinearity in time series: the method of surrogate data
@nl
prefLabel
Testing for nonlinearity in time series: the method of surrogate data
@en
Testing for nonlinearity in time series: the method of surrogate data
@nl
P2093
P1433
P1476
Testing for nonlinearity in time series: the method of surrogate data
@en
P2093
André Longtin
Bryan Galdrikian
James Theiler
P356
10.1016/0167-2789(92)90102-S
P577
1992-09-01T00:00:00Z