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Multiscale Entropy Approaches and Their Applications
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Multiscale entropy (MSE) measures to evaluate the complexity of time series by taking into account the multiple time scales in physical systems were proposed in the early 2000s. Since then, these approaches have received a great deal of attention and have been used in a wide range of applications. Multivariate approaches have also been developed. The algorithms for an MSE approach are composed of two main steps: (i) a coarse-graining procedure to represent the system’s dynamics on different scales and (ii) the entropy computation for the original signal and for the coarse-grained time series to evaluate the irregularity for each scale. Moreover, different entropy measures have been associated with the coarse-graining approach, each one having its advantages and drawbacks. In this Special Issue, we gathered 24 papers focusing on either the theory or applications of MSE approaches. These papers can be divided into two groups: papers that propose new developments in entropy-based measures or improve the understanding of existing ones (9 papers) and papers that propose new applications of existing entropy-based measures (14 papers). Moreover, one paper presents a review of cross-entropy methods and their multiscale approaches.
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Keywords
- Aging
- Alzheimer Disease
- ambient temperature
- approximate entropy
- asynchrony
- bearing fault diagnosis
- biometric characterization
- brain complexity
- cardiac autonomic neuropathy
- cardiac risk stratification
- center of pressure
- clock drawing test
- complexity
- composite cross-sample entropy
- consolidation
- copula density
- corsi block tapping test
- coupling
- CPD
- Cramer–Rao lower bound
- cross-approximate entropy
- cross-conditional entropy
- cross-distribution entropy
- cross-entropy
- cross-fuzzy entropy
- cross-sample entropy
- Default Mode Network
- dependency structures
- diabetes
- digit span test
- dynamic functional connectivity
- edge complexity
- EEG
- electrocardiogram
- Electroencephalogram
- embodied media
- Ensemble empirical mode decomposition
- Entropy
- entropy rate
- episodic memory
- estimator variance
- eye movement events detection
- falls
- fault diagnosis
- financial time series
- finite-length signals
- Fisher ratio
- fluid intelligence
- fMRI
- functional near infra-red spectroscopy
- fuzzy entropy
- Gait
- Heart rate variability
- heart rate variability (HRV)
- heart sound
- History of engineering & technology
- HMSVM
- Holter
- HRV
- Human behavior
- humanoid
- ICEEMDAN
- local robust principal component analysis
- long term monitoring
- magnetoencephalogram
- medical information
- memory effect
- mental workload
- missing values
- motif
- multi-component signal
- multi-scale
- multi-scale dispersion entropy
- multi-scale entropy
- multi-scale entropy (MSE)
- multi-scale permutation entropy
- multifractal spectrum
- multilevel entropy map
- multiscale analysis
- multiscale cross-entropy
- multiscale distribution entropy
- multiscale entropy
- multiscale indices
- Multiscale Permutation Entropy
- multiscale time irreversibility
- Multivariate data
- multivariate multiscale dispersion entropy
- multivariate time series
- network complexity
- node complexity
- nonlinear analysis time series analysis
- nonlinear dynamics
- ordinal patterns
- page view
- PD
- permutation entropy
- physiological data
- postural control
- postural stability index
- predictability
- Prefrontal Cortex
- preterm neonate
- pulse interval
- RCMDE
- resting state
- resting-state functional magnetic resonance imaging
- RR interval
- sample entropy
- short-term inter-beat interval
- signal complexity
- sleep staging
- stability states
- Structural health monitoring
- SVM
- systolic arterial pressure (SAP)
- systolic blood pressure
- Technology, engineering, agriculture
- Technology: general issues
- tele-communication
- telemetry
- tensor decomposition
- thermoregulation
- time-scale decomposition
- variational mode decomposition
- vasopressin
- vector autoregressive fractionally integrated (VARFI) models
- Voronoi decomposition
- weak fault
- Wikipedia