LEADER 04498nam 2201201z- 450 001 9910367736303321 005 20231214133130.0 010 $a3-03928-033-3 035 $a(CKB)4100000010106354 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/46559 035 $a(EXLCZ)994100000010106354 100 $a20202102d2019 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aEntropy Measures for Data Analysis: Theory, Algorithms and Applications 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2019 215 $a1 electronic resource (260 p.) 311 $a3-03928-032-5 330 $aEntropies 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. 517 $aEntropy Measures for Data Analysis 610 $afault diagnosis 610 $aempirical mode decomposition 610 $aauditory attention 610 $aDempster-Shafer evidence theory 610 $asimulation 610 $auncertainty of basic probability assignment 610 $acenter of pressure displacement 610 $aparticle size distribution 610 $amultivariate analysis 610 $asymbolic analysis 610 $apermutation entropy 610 $ashort time records 610 $aco-evolution 610 $aplausibility transformation 610 $aexperiment of design 610 $across-entropy method 610 $aweighted Hartley entropy 610 $afirefly algorithm 610 $aembedded dimension 610 $aentropy measure 610 $aeffective transfer entropy 610 $atreadmill walking 610 $aordinal patterns 610 $acomplex fuzzy set 610 $aentropy visualization 610 $abelief entropy 610 $asignal classification 610 $amachine learning evaluation 610 $anovelty detection 610 $aselfsimilar measure 610 $aPermutation entropy 610 $aautomatic learning 610 $across wavelet transform 610 $across-visibility graphs 610 $aKolmogorov-Sinai entropy 610 $adistance 610 $aShannon-type relations 610 $aTsallis entropy 610 $amarket crash 610 $asupport vector machine (SVM) 610 $aconditional entropy of ordinal patterns 610 $asample entropy 610 $alearning 610 $aelectroencephalography (EEG) 610 $ameta-heuristic 610 $aentropy 610 $adata transformation 610 $ainformation entropy 610 $asignal analysis 610 $asynchronization analysis 610 $asimilarity indices 610 $adata analysis 610 $ageodesic distance 610 $aauditory attention classifier 610 $aentropy measures 610 $adistance induced vague entropy 610 $aanalog circuit 610 $avague entropy 610 $acomplex vague soft set 610 $aentropy balance equation 610 $aparametric t-distributed stochastic neighbor embedding 610 $aglobal optimization 610 $alearning systems 610 $aimage entropy 610 $aalgorithmic complexity 610 $asupport vector machine 610 $asystem coupling 610 $arelevance analysis 610 $aChinese stock sectors 610 $aShannon entropy 610 $alinear discriminant analysis (LDA) 610 $ainformation 610 $ainformation transfer 610 $adual-tasking 610 $anon-probabilistic entropy 700 $aKeller$b Karsten$4auth$062627 906 $aBOOK 912 $a9910367736303321 996 $aEntropy Measures for Data Analysis: Theory, Algorithms and Applications$93025759 997 $aUNINA