Permutation Jensen-Shannon distance: A versatile and fast symbolic tool for complex time-series analysis
The main motivation of this paper is to introduce the permutation Jensen-Shannon distance,
a symbolic tool able to quantify the degree of similarity between two arbitrary time series …
a symbolic tool able to quantify the degree of similarity between two arbitrary time series …
A predictive processing model of perception and action for self-other distinction
During interaction with others, we perceive and produce social actions in close temporal
distance or even simultaneously. It has been argued that the motor system is involved in …
distance or even simultaneously. It has been argued that the motor system is involved in …
Monoparametric family of metrics derived from classical Jensen–Shannon divergence
TM Osán, DG Bussandri, PW Lamberti - Physica A: Statistical Mechanics …, 2018 - Elsevier
Jensen–Shannon divergence is a well known multi-purpose measure of dissimilarity
between probability distributions. It has been proven that the square root of this quantity is a …
between probability distributions. It has been proven that the square root of this quantity is a …
Application of the third RIT binary black hole simulations catalog to parameter estimation of gravitational-wave signals from the LIGO-Virgo O1 and O2 observational …
J Healy, CO Lousto, J Lange, R O'Shaughnessy - Physical Review D, 2020 - APS
Using exclusively the 777 full numerical waveforms of the third binary black hole RIT
catalog, we reanalyze the ten black hole merger signals reported in LIGO/Virgo's O1/O2 …
catalog, we reanalyze the ten black hole merger signals reported in LIGO/Virgo's O1/O2 …
[HTML][HTML] Automated parameter tuning with accuracy control for efficient reservoir simulations
EH Sæternes, A Thune, AB Rustad, T Skeie… - Journal of Computational …, 2024 - Elsevier
Computer simulations of complex physical processes typically require sophisticated
numerical schemes that internally involve many parameters. Different choices of such …
numerical schemes that internally involve many parameters. Different choices of such …
Vela pulsar: single pulses analysis with machine learning techniques
We study individual pulses of Vela (PSR B0833− 45/J0835− 4510) from daily observations
of over 3 h (around 120 000 pulses per observation), performed simultaneously with the two …
of over 3 h (around 120 000 pulses per observation), performed simultaneously with the two …
Leak Detection in Natural Gas Pipelines Based on Unsupervised Reconstruction of Healthy Flow Data
Timely detection of leak accidents plays an essential role in the safe operation and risk
assessment of natural gas pipelines. However, the scarce leak data and complex operating …
assessment of natural gas pipelines. However, the scarce leak data and complex operating …
[PDF][PDF] Synthetic Financial Time Series Generation with Regime Clustering
K Zakharov, E Stavinova… - Journal of Advances in …, 2023 - researchgate.net
Methods for synthetic data generation are extremely valuable nowadays since they allow
researchers and practitioners to develop and test their models without the risk and cost …
researchers and practitioners to develop and test their models without the risk and cost …
Granger causality and jensen–shannon divergence to determine dominant atrial area in atrial fibrillation
Atrial fibrillation (AF) is already the most commonly occurring arrhythmia. Catheter
pulmonary vein ablation has emerged as a treatment that is able to make the arrhythmia …
pulmonary vein ablation has emerged as a treatment that is able to make the arrhythmia …
Spike Timing-Dependent Plasticity with Enhanced Long-Term Depression Leads to an Increase of Statistical Complexity
M Pallares Di Nunzio, F Montani - Entropy, 2022 - mdpi.com
Synaptic plasticity is characterized by remodeling of existing synapses caused by
strengthening and/or weakening of connections. This is represented by long-term …
strengthening and/or weakening of connections. This is represented by long-term …