Results 11 to 20 of about 314,467 (275)
Urban Transfer Entropy across Scales. [PDF]
PLoS ONE, 2015 The morphology of urban agglomeration is studied here in the context of information exchange between different spatio-temporal scales. Urban migration to and from cities is characterised as non-random and following non-random pathways.
Roberto Murcio +3 more
doaj +6 more sources
Transfer Entropy for Coupled Autoregressive Processes [PDF]
Entropy, 2013 A method is shown for computing transfer entropy over multiple time lags for coupled autoregressive processes using formulas for the differential entropy of multivariate Gaussian processes.
Shawn D. Pethel, Daniel W. Hahs
doaj +2 more sources
Transfer Entropy as a Log-likelihood Ratio [PDF]
Physical Review Letters, 2012 Transfer entropy, an information-theoretic measure of time-directed information transfer between joint processes, has steadily gained popularity in the analysis of complex stochastic dynamics in diverse fields, including the neurosciences, ecology ...
A. D. R. McQuarrie +7 more
core +3 more sources
Assessing transfer entropy from biochemical data [PDF]
Physical Review E, 2022 30 pages, 11 ...
Takuya Imaizumi +5 more
openaire +3 more sources
Accurate QT correction method from transfer entropy. [PDF]
Cardiovasc Digit Health J, 2023 The QT interval in the electrocardiogram (ECG) is a fundamental risk measure for arrhythmic adverse cardiac events. However, the QT interval depends on the heart rate and must be corrected accordingly. The present QT correction (QTc) methods are either simple models leading to under- or overcorrection, or impractical in requiring long-term empirical ...
Räsänen E +8 more
europepmc +6 more sources
Transfer entropy rate through Lempel-Ziv complexity [PDF]
Physical Review E, 2020 In this article we present a methodology to estimate the Transfer Entropy Rate between two systems through the Lempel-Ziv complexity. This methodology carries a set of practical advantages: it can be estimated from two single discrete series of measures, it is not computationally expensive and it does not assume any model for the data.
Juan F. Restrepo +2 more
openaire +4 more sources
SoftwareX, 2019 This paper shows how to quantify and test for the information flow between two time series with Shannon transfer entropy and Rényi transfer entropy using the R package RTransferEntropy. We discuss the methodology, the bias correction applied to calculate
Simon Behrendt +3 more
doaj +1 more source
Inferring information flow in spike-train data sets using a trial-shuffle method. [PDF]
PLoS ONE, 2018 Understanding information processing in the brain requires the ability to determine the functional connectivity between the different regions of the brain.
Benjamin L Walker, Katherine A Newhall
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Xibei Gongye Daxue Xuebao, 2023 In view of the problem that the generalization ability of traditional data-driven fault diagnosis model declines or even fails in mechanical system diagnosis, a fault diagnosis method based on multi-scale transfer symbolic dynamic entropy and support ...
YU Guangwei, YAN Li
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Contribution to Transfer Entropy Estimation via the k-Nearest-Neighbors Approach
Entropy, 2015 This paper deals with the estimation of transfer entropy based on the k-nearest neighbors (k-NN) method. To this end, we first investigate the estimation of Shannon entropy involving a rectangular neighboring region, as suggested in already existing ...
Jie Zhu +3 more
doaj +1 more source