LEADER 01238nam0 22003131i 450 001 RML0286837 005 20231121125733.0 010 $a8470394290 100 $a20121121d1984 ||||0itac50 ba 101 | $aspa 102 $aes 181 1$6z01$ai $bxxxe 182 1$6z01$an 200 1 $aCalila e Dimna$aedición, introducción y notas de de Juan Manuel Cacho Blecua y María Jesús Lacarra 210 $aMadrid $cCastalia $dc1984 215 $a407 p.$d18 cm 225 | $aClasicos Castalia$c- Madrid $eCastalia 410 0$1001RML0329331$12001 $aClasicos Castalia$c- Madrid $eCastalia 702 1$aCacho Blecua$b, Juan Manuel$3RMLV180068 702 1$aLacarra$b, María Jesús$3RMLV185221 801 3$aIT$bIT-01$c20121121 850 $aIT-FR0017 899 $aBiblioteca umanistica Giorgio Aprea$bFR0017 912 $aRML0286837 950 0$aBiblioteca umanistica Giorgio Aprea$d 52CIS 5 COLL E 133$e 52VM 0000566115 VM barcode:00055775. - Inventario:1252 LLCVM$fA $h20050630$i20121204 977 $a 52 996 $aEdición, introducción y notas de de Juan Manuel Cacho Blecua y María Jesús Lacarra$93627302 996 $aCalila e Dimna$999806 997 $aUNICAS LEADER 04631nam 2201237z- 450 001 9910367736303321 005 20210211 010 $a3-03928-033-3 035 $a(CKB)4100000010106354 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/46559 035 $a(oapen)doab46559 035 $a(EXLCZ)994100000010106354 100 $a20202102d2019 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aEntropy Measures for Data Analysis: Theory, Algorithms and Applications 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2019 215 $a1 online resource (260 p.) 311 08$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 606 $aHistory of engineering and technology$2bicssc 610 $aalgorithmic complexity 610 $aanalog circuit 610 $aauditory attention 610 $aauditory attention classifier 610 $aautomatic learning 610 $abelief entropy 610 $acenter of pressure displacement 610 $aChinese stock sectors 610 $aco-evolution 610 $acomplex fuzzy set 610 $acomplex vague soft set 610 $aconditional entropy of ordinal patterns 610 $across wavelet transform 610 $across-entropy method 610 $across-visibility graphs 610 $adata analysis 610 $adata transformation 610 $aDempster-Shafer evidence theory 610 $adistance 610 $adistance induced vague entropy 610 $adual-tasking 610 $aeffective transfer entropy 610 $aelectroencephalography (EEG) 610 $aembedded dimension 610 $aempirical mode decomposition 610 $aentropy 610 $aentropy balance equation 610 $aentropy measure 610 $aentropy measures 610 $aentropy visualization 610 $aexperiment of design 610 $afault diagnosis 610 $afirefly algorithm 610 $ageodesic distance 610 $aglobal optimization 610 $aimage entropy 610 $ainformation 610 $ainformation entropy 610 $ainformation transfer 610 $aKolmogorov-Sinai entropy 610 $alearning 610 $alearning systems 610 $alinear discriminant analysis (LDA) 610 $amachine learning evaluation 610 $amarket crash 610 $ameta-heuristic 610 $amultivariate analysis 610 $anon-probabilistic entropy 610 $anovelty detection 610 $aordinal patterns 610 $aparametric t-distributed stochastic neighbor embedding 610 $aparticle size distribution 610 $apermutation entropy 610 $aPermutation entropy 610 $aplausibility transformation 610 $arelevance analysis 610 $asample entropy 610 $aselfsimilar measure 610 $aShannon entropy 610 $aShannon-type relations 610 $ashort time records 610 $asignal analysis 610 $asignal classification 610 $asimilarity indices 610 $asimulation 610 $asupport vector machine 610 $asupport vector machine (SVM) 610 $asymbolic analysis 610 $asynchronization analysis 610 $asystem coupling 610 $atreadmill walking 610 $aTsallis entropy 610 $auncertainty of basic probability assignment 610 $avague entropy 610 $aweighted Hartley entropy 615 7$aHistory of engineering and technology 700 $aKeller$b Karsten$4auth$062627 906 $aBOOK 912 $a9910367736303321 996 $aEntropy Measures for Data Analysis: Theory, Algorithms and Applications$93025759 997 $aUNINA LEADER 01469nam0 2200337 i 450 001 BVE0041427 005 20251003044052.0 010 $a8820480727 100 $a20080908d1993 ||||0itac50 ba 101 | $aita 102 $ait 181 1$6z01$ai $bxxxe 182 1$6z01$an 200 1 $aˆIl ‰merito della spesa pubblica$ela natura e l'offerta dei beni non di mercato$fa cura di Aldo Chiancone, Franco Osculati$gscritti di A. Bariletti ... [et al.] 210 $aMilano$cF. Angeli$d©1993 215 $a263 p.$d22 cm. 225 | $aEconomia e finanza pubblica$v17 410 0$1001BVE0041428$12001 $aEconomia e finanza pubblica$v17 676 $a336.39$9SPESA PUBBLICA$v21 676 $a336.39$9SPESA PUBBLICA$v23 702 1$aBariletti$b, Antonio$3CFIV062978 702 1$aChiancone$b, Aldo$3CFIV089488 702 1$aOsculati$b, Franco$3CFIV111185 801 3$aIT$bIT-000000$c20080908 850 $aIT-BN0095 901 $bNAP 01$cPOZZO LIB.$nVi sono collocati fondi di economia, periodici di ingegneria e scienze, periodici di economia e statistica e altri fondi comprendenti documenti di economia pervenuti in dono. 912 $aBVE0041427 950 0$aBiblioteca Centralizzata di Ateneo$c1 v.$d 01POZZO LIB.F. PARRAVICINI 238$e 0101 0600160615E VMA 1 v. (Precedente collocazione P 206)$fB $h20220908$i20220908 977 $a 01 996 $aMerito della spesa pubblica$9635917 997 $aUNISANNIO