Entropy Measures for Data Analysis
Theory, Algorithms and Applications
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Beschreibung
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.
Autor*in
Karsten Keller
Themen in »Entropy Measures for Data Analysis«
experiment of design empirical mode decomposition signal analysis similarity indices synchronization analysis auditory attention entropy measure linear discriminant analysis (LDA) support vector machine (SVM) auditory attention classifier electroencephalography (EEG) vague entropy distance induced vague entropy distance complex fuzzy set