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Entropy Measures for Data Analysis: Theory, Algorithms and Applications



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Autore: Keller Karsten Visualizza persona
Titolo: Entropy Measures for Data Analysis: Theory, Algorithms and Applications Visualizza cluster
Pubblicazione: MDPI - Multidisciplinary Digital Publishing Institute, 2019
Descrizione fisica: 1 electronic resource (260 p.)
Soggetto non controllato: fault diagnosis
empirical mode decomposition
auditory attention
Dempster-Shafer evidence theory
simulation
uncertainty of basic probability assignment
center of pressure displacement
particle size distribution
multivariate analysis
symbolic analysis
permutation entropy
short time records
co-evolution
plausibility transformation
experiment of design
cross-entropy method
weighted Hartley entropy
firefly algorithm
embedded dimension
entropy measure
effective transfer entropy
treadmill walking
ordinal patterns
complex fuzzy set
entropy visualization
belief entropy
signal classification
machine learning evaluation
novelty detection
selfsimilar measure
Permutation entropy
automatic learning
cross wavelet transform
cross-visibility graphs
Kolmogorov-Sinai entropy
distance
Shannon-type relations
Tsallis entropy
market crash
support vector machine (SVM)
conditional entropy of ordinal patterns
sample entropy
learning
electroencephalography (EEG)
meta-heuristic
entropy
data transformation
information entropy
signal analysis
synchronization analysis
similarity indices
data analysis
geodesic distance
auditory attention classifier
entropy measures
distance induced vague entropy
analog circuit
vague entropy
complex vague soft set
entropy balance equation
parametric t-distributed stochastic neighbor embedding
global optimization
learning systems
image entropy
algorithmic complexity
support vector machine
system coupling
relevance analysis
Chinese stock sectors
Shannon entropy
linear discriminant analysis (LDA)
information
information transfer
dual-tasking
non-probabilistic entropy
Sommario/riassunto: Entropies and entropy-like quantities play an increasing role in modern non-linear data analysis. Fields that benefit from this application range from biosignal analysis to econophysics and engineering. This issue is a collection of papers touching on different aspects of entropy measures in data analysis, as well as theoretical and computational analyses. The relevant topics include the difficulty to achieve adequate application of entropy measures and the acceptable parameter choices for those entropy measures, entropy-based coupling, and similarity analysis, along with the utilization of entropy measures as features in automatic learning and classification. Various real data applications are given.
Altri titoli varianti: Entropy Measures for Data Analysis
Titolo autorizzato: Entropy Measures for Data Analysis: Theory, Algorithms and Applications  Visualizza cluster
ISBN: 3-03928-033-3
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910367736303321
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