Efficient computation of multiscale entropy over short biomedical time series based on linear state-space models

DOI10.1155/2017/1768264zbMath1380.93228OpenAlexW2773861965WikidataQ58859875 ScholiaQ58859875MaRDI QIDQ1694175

Alberto Porta, Michal Javorka, Luca Faes, Giandomenico Nollo

Publication date: 1 February 2018

Published in: Complexity (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2017/1768264

zbMATH Keywords

time seriesdynamical complexityautoregressive stochastic processescomputational reliabilitylinear state-space (SS) modelsmultiple temporal scalesmultiscale entropy (MSE)refined MSE (RMSE) measures

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Time-scale analysis and singular perturbations in control/observation systems (93C70) Stochastic systems in control theory (general) (93E03)

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Cites Work

• Measuring connectivity in linear multivariate processes: definitions, interpretation, and practical analysis
• Time series analysis using composite multiscale entropy
• Cardiovascular and cardiorespiratory coupling analyses: a review
• State space modeling of multiple time series
• On Fractionally Integrated Autoregressive Moving-Average Time Series Models With Conditional Heteroscedasticity
• State-Space Analysis of Granger-Geweke Causality Measures with Application to fMRI
• Discrete-time signal processing. An algebraic approach

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