Entropy Measures for Data Analysis: Theory, Algorithms and Applications

• Autore: Keller Karsten
• Pubblicazione: MDPI - Multidisciplinary Digital Publishing Institute, 2019
• Descrizione fisica: 1 online resource (260 p.)
• Soggetto topico: History of engineering and technology
• Soggetto non controllato: algorithmic complexity; analog circuit; auditory attention; auditory attention classifier; automatic learning; belief entropy; center of pressure displacement; Chinese stock sectors; co-evolution; complex fuzzy set; complex vague soft set; conditional entropy of ordinal patterns; cross wavelet transform; cross-entropy method; cross-visibility graphs; data analysis; data transformation; Dempster-Shafer evidence theory; distance; distance induced vague entropy; dual-tasking; effective transfer entropy; electroencephalography (EEG); embedded dimension; empirical mode decomposition; entropy; entropy balance equation; entropy measure; entropy measures; entropy visualization; experiment of design; fault diagnosis; firefly algorithm; geodesic distance; global optimization; image entropy; information; information entropy; information transfer; Kolmogorov-Sinai entropy; learning; learning systems; linear discriminant analysis (LDA); machine learning evaluation; market crash; meta-heuristic; multivariate analysis; non-probabilistic entropy; novelty detection; ordinal patterns; parametric t-distributed stochastic neighbor embedding; particle size distribution; permutation entropy; Permutation entropy; plausibility transformation; relevance analysis; sample entropy; selfsimilar measure; Shannon entropy; Shannon-type relations; short time records; signal analysis; signal classification; similarity indices; simulation; support vector machine; support vector machine (SVM); symbolic analysis; synchronization analysis; system coupling; treadmill walking; Tsallis entropy; uncertainty of basic probability assignment; vague entropy; weighted Hartley 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
• ISBN: 3-03928-033-3
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910367736303321
• Lo trovi qui: Univ. Federico II