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Cross-Scale Interactions and Information Transfer

Milan Paluš
2014 Entropy  
Paluš and Vejmelka [26] critically assessed this method and compared it to the information-theoretic approach.  ...  Paluš et al. [5] have proposed the conditional mutual information as a tool for the generalization of the GC concept for nonlinear systems.  ... 
doi:10.3390/e16105263 fatcat:a7cwxjn27feufivavxc26zo6s4

Testing for nonlinearity in weather records

Milan Paluš, Dagmar Novotná
1994 Physics Letters A  
Therefore Palus et al. [24] proposed to compare Ln(T) with Rn(T), considered as the functions of the time lag T.  ...  Recently, Palus et al. [24] have demonstrated how the information theoretic functionals -redundancies -can be used for the detection of nonlinearity. A brief overview of the method follows.  ... 
doi:10.1016/0375-9601(94)91002-2 fatcat:bmrbesrqpves5mdygjsfk3ct3e

Entropies, Partitionings and Heart Rate Variability

Milan Palus, Jan J. Zebrowski
2009 Activitas Nervosa Superior  
Milan Palus was supported by the Institutional Research Plan AV0Z10300504.  ...  (Palus, 1995) , (Palus, 1996) , and references therein.  ...  (Cover & Thomas, 1991) , (Fraser, 1989) , (Sinai, 1976) , (Petersen, 1983) , (Palus, 1993) and references therein.The concept of coarse-grained entropy rates has been introduced in (Palus, 1996)  ... 
doi:10.1007/bf03380037 fatcat:4q24kjzjvnfeti5yugg2znnpsq

Partitioning networks into clusters and residuals with average association

Martin Vejmelka, Milan Paluš
2010 Chaos  
We investigate the problem of detecting clusters exhibiting higher-than-average internal connectivity in networks of interacting systems. We show how the average association objective formulated in the context of spectral graph clustering leads naturally to a clustering strategy where each system is assigned to at most one cluster. A residual set is formed of the systems that are not members of any cluster. Maximization of the average association objective leads to a discrete optimization
more » ... m, which is difficult to solve, but a relaxed version can be solved using an eigendecomposition of the connectivity matrix. A simple approach to extracting clusters from a relaxed solution is described and developed by applying a variance maximizing solution to the relaxed solution, which leads to a method with increased accuracy and sensitivity. Numerical studies of theoretical connectivity models and of synchronization clusters in a lattice of coupled Lorenz oscillators are conducted to show the efficiency of the proposed approach. The method is applied to an experimentally obtained human resting state functional magnetic resonance imaging dataset and the results are discussed. The proliferation of high-dimensional datasets in many areas of science has created a need for methods that help in the investigation of large sets of data. Relationships in such datasets are often modeled as networks of interacting or related elements. This paper proposes a method of finding cohesive functional units of elements in weighted undirected networks using a clustering approach. An investigated network is partitioned into a set of clusters representing these units and a residual set. The residual set contains elements which do not relate well to any of the identified clusters. This approach enables a concise characterization of functional units even in the presence of unrelated or confounding elements. a͒ Electronic mail:
doi:10.1063/1.3460360 pmid:20887043 fatcat:fiwb4h4hsbh43nmwyps2x2zkri

Cross-Scale Causality and Information Transfer in Simulated Epileptic Seizures

Kajari Gupta, Milan Paluš
2021 Entropy  
The equivalence of the two functionals was shown by Paluš and Vejmelka [19] .  ...  Searching for a generalization of the Granger causality concept using information theory, Paluš et al.  ... 
doi:10.3390/e23050526 pmid:33923035 fatcat:fy4bfgrg3nfhrggcvjnyjulrwe

Fractal rock slope dynamics anticipating a collapse

Milan Paluš, Dagmar Novotná, Jiří Zvelebil
2004 Physical Review E  
Time series of dilatometric measurements of relative displacements on rock cracks on stable and unstable sandstone slopes were analysed. The inherent dynamics of rock slopes lack any significant nonlinearity. However, the residuals obtained by removing meteorological influences are fat-tailed non-Gaussian fluctuations, with short-range correlations in the case of stable slopes. The fluctuations of unstable slopes exhibit self-affine dynamics of fractional Brownian motions with power-law
more » ... e correlations and are characterized by asymptotic power-law probability distribution with decay coefficient outside the range of stable Lévy distributions.
doi:10.1103/physreve.70.036212 pmid:15524617 fatcat:5y26czy74nd6fiqdtyrcwsgpau

Inferring the directionality of coupling with conditional mutual information

Martin Vejmelka, Milan Paluš
2008 Physical Review E  
This method has been previously applied by Paluš ͓4, 11, 12, 21, 22, 31, 32, 42, 43͔.  ... 
doi:10.1103/physreve.77.026214 pmid:18352110 fatcat:6s3l5vxwmnd7hjfnagflm4fqve

Information theoretic test for nonlinearity in time series

Milan Paluš, Vladimír Albrecht, Ivan Dvořák
1993 Physics Letters A  
A diagnostic test for identifying nonlinear dynamical relationships in time series, based on mutual information and redundancy, functionals introduced in information theory, is proposed. Its ability to distinguish (noised) multiperiodic and random time series from time series generated by chaotic dynamical systems is demonstrated. The latter arecharacterized by specificbehaviour of marginal redundancies reflecting the increase of uncertainty in time due to positive information production rate.
doi:10.1016/0375-9601(93)90827-m fatcat:vl6q4rjh4zhnjly3kt7g6xz24i

Detecting nonlinearity in multivariate time series

Milan Paluš
1996 Physics Letters A  
We propose an extension to time series with several simultaneously measured variables of the nonlinearity test, which combines the redundancy -- linear redundancy approach with the surrogate data technique. For several variables various types of the redundancies can be defined, in order to test specific dependence structures between/among (groups of) variables. The null hypothesis of a multivariate linear stochastic process is tested using the multivariate surrogate data. The linear
more » ... are used in order to avoid spurious results due to imperfect surrogates. The method is demonstrated using two types of numerically generated multivariate series (linear and nonlinear) and experimental multivariate data from meteorology and physiology.
doi:10.1016/0375-9601(96)00116-8 fatcat:wzsoehwh2vcofnuehhuupnytdy

Compression-Complexity with Ordinal Patterns for Robust Causal Inference in Irregularly-Sampled Time Series [article]

Aditi Kathpalia, Pouya Manshour, Milan Paluš
2022 arXiv   pre-print
Paluš.  ...  In order to detect the coupling direction among two dynamical variables of X and Y , Paluš et al.  ...  Paluš et al. [21] introduced a causality measure based on mutual information, called Conditional Mutual Information (CMI). CMI has been shown to be equivalent to TE [22] .  ... 
arXiv:2204.11731v1 fatcat:kmt3opahqvgl5juuif3n32zvai

Smooth information flow in temperature climate network reflects mass transport

Jaroslav Hlinka, Nikola Jajcay, David Hartman, Milan Paluš
2017 Chaos  
Paluš et al. 24 proposed information-theoretic formulation of the Granger causality for nonlinear processes using conditional mutual information.  ...  The equivalence of the two is shown by Palus and Vejmelka 26 . Barnett et al. 27 have shown analytically that the transfer entropy is equivalent to Granger causality for Gaussian processes.  ... 
doi:10.1063/1.4978028 pmid:28364752 fatcat:qffnlnpmvzho5ecbhe52mbdbum

Linked by dynamics: wavelet--based mutual information rate as a connectivity measure and scale-specific networks [article]

Milan Palus
2017 arXiv   pre-print
Paluš et al.  ...  Due to this behavior Paluš et al. [58] described the route to synchronization as an adjustment of information rates.  ... 
arXiv:1706.10159v1 fatcat:fxrltoqsffaftg3xc3joer27wm

Comparison of coherence and phase synchronization of the human sleep electroencephalogram

Kristína Mezeiová, Milan Paluš
2012 Clinical Neurophysiology  
Objective: Potential differences between coherence and phase synchronization analyses of human sleep electroencephalogram (EEG) are assessed and occurrences of phase vs. complete synchronization between EEG signals from different locations during different sleep stages are investigated. Methods: Linear spectral coherence, mean phase coherence (MPC) z-score and Pearson's correlation coefficient of analytic amplitudes were evaluated for different spectral bands of whole-night EEG recordings from
more » ... 5 healthy subjects. Results: Coherence and MPC z-score demonstrated practically the same statistical differences between vigilance stages, confirming the findings of previous coherence-based studies. MPC z-score and amplitude correlations were most correlated (>0.5) between homologous interhemispheric positions and least correlated between nonhomologous interhemispheric positions and between fronto-occipital positions. Conclusions: Coherence and phase synchronization provided essentially the same information. Complete synchronization was manifested by highly coherent phases and correlated amplitudes, as well as by correlated changes of phase synchronization, coherence and amplitude correlations between vigilance states. In cases of weaker coupling, phase synchronization and coherence change in agreement, while behaviour of amplitude correlations differs. Significance: Phase synchronization analysis is not superior to coherence analysis, although the coupling between EEG signals is dominated by phase synchronization which turns into complete synchronization in the most strongly coupled EEG signals.
doi:10.1016/j.clinph.2012.01.016 pmid:22361266 fatcat:olwxd45qxvfjppbpnlmgpb55ay

Multiscale Atmospheric Dynamics: Cross-Frequency Phase-Amplitude Coupling in the Air Temperature

Milan Paluš
2014 Physical Review Letters  
Paluš & Stefanovska  ...  Paluš & Novotná [6] even found the air temperature data wellexplained by a linear stochastic process, when the dependence between a temperature time series {x(t)} and its lagged twin {x(t+τ )} was considered  ... 
doi:10.1103/physrevlett.112.078702 pmid:24579641 fatcat:wkympcfsknaubasyeyx7dnksbm

Singular-value decomposition in attractor reconstruction: Pitfalls and precautions

Milan Paluš, Ivan Dvořák
1992 Physica D : Non-linear phenomena  
Palu.?, Fig. 3 . 3 The normalized singular spectra obtained from 4096 data points generated by the x-component of the Lorenz system in chaotic state with integration step 0.0025.  ... 
doi:10.1016/0167-2789(92)90198-v fatcat:zqgkqqleuzartiwy6kab3tts4y
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