LEADER 03381nam 2200733 450 001 9910461108103321 005 20210209115900.0 010 $a1-78160-809-1 010 $a1-283-95539-3 010 $a1-283-95543-1 010 $a1-78042-674-7 035 $a(CKB)2670000000170796 035 $a(EBL)887062 035 $a(OCoLC)784886897 035 $a(SSID)ssj0001099821 035 $a(PQKBManifestationID)11608961 035 $a(PQKBTitleCode)TC0001099821 035 $a(PQKBWorkID)11054620 035 $a(PQKB)10125314 035 $a(SSID)ssj0001573426 035 $a(PQKBManifestationID)16227024 035 $a(PQKBTitleCode)TC0001573426 035 $a(PQKBWorkID)14840769 035 $a(PQKB)10359328 035 $a(MiAaPQ)EBC887062 035 $a(MiAaPQ)EBC1707349 035 $a(PPN)187497524 035 $a(Au-PeEL)EBL1707349 035 $a(CaONFJC)MIL426789 035 $a(OCoLC)843047243 035 $a(EXLCZ)992670000000170796 100 $a20160128h20112011 uy 0 101 0 $afre 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aEgon Schiele 205 $a1st ed. 210 1$aNew York :$cParkstone International,$d2011. 210 4$d©[2011] 215 $a1 online resource (82 p.) 225 1 $aPerfect Square 300 $aDescription based upon print version of record. 311 $a1-84484-125-1 311 $a1-84484-026-3 320 $aIncludes bibliographical references and index. 327 $aSchieles kindertijd; Zijn lievelingszuster Gerti; Wenen en het fin de sie?cle; Gustave Klimt, de vaderlijke vriend; Schieles modellen; Het radicalisme van Schiele; Een werkwijze eigen aan expressieve kunst; Ontmoeting met het spiegelbeeld; De eerste tentoonstellingen; 'Nieuwe kunstenaars'; Het Weense artistieke milieu; Schieles vrienden; Wally, zijn eerste levensgezellin; Het naakte zelfportret; Schiele, de getormenteerde man; De fascinatie voor de dood; Schetsmatige schepsels; De ruimtelijke weergave van het lichaam; Het vampierachtige van de seksualiteit; Afkeer en aantrekkingskracht 327 $aDe pornografische fotografie wordt een industrieDe aanhouding van Schiele; De internationale kunstenaar; Een tactische sociale zet; Schiele, de bourgeois; Schiele, een bewierookte kunstenaar; BIOGRAFIE; INHOUDSTAFEL 330 $aEgon Schiele werd geboren in Tulln op 12 juni 1890 en stierf in Wenen op 31 oktober 1918. Hij was een Oostenrijks expressionistisch kunstschilder. Zowel zijn grootvader als zijn vader werkten bij de spoorwegen. Een loopbaan bij de spoorwegen had voor de hand gelegen, maar Schiele ging tegen de oorspronkelijke wens van zijn moeder en zijn voogd naar de kunstacademie, waar hij overigens matige resultaten behaalde. De werken van Egon Schiele zijn expressionistisch en behoren tot de schilderstijl Sezession. De tekeningen en schilderijen van Schiele zijn voornamelijk afbeeldingen van mensen. In be 410 0$aPerfect Square 606 $aExpressionism (Art)$zAustria 606 $aArt, Austrian$y20th century 608 $aElectronic books. 615 0$aExpressionism (Art) 615 0$aArt, Austrian 676 $a759.36 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910461108103321 996 $aEgon Schiele$91084174 997 $aUNINA LEADER 01552nam a2200229 a 4500 001 991001625159707536 008 120120s1997 it 000 0 ita d 035 $ab14043944-39ule_inst 040 $aDip.to Studi Giuridici$bita 082 $a328.45 110 $aItalia :$bMinistero per la solidarietà sociale$00 245 10$aRelazione sull'attuazione delle norme urgenti in materia di asilo politico, di ingresso e soggiorno di cittadini extracomunitari e di regolarizzazione dei cittadini extracomunitari... :$banno 1996 : (articolo 11, comma 2 del decreto-legge 30 dicembre1989, n. 416, convertito con modificazioni, dalla legge 28 febbraio 1990, n. 39) /$cpresentata dal Ministro per la solidarietà sociale (Turco) ; comunicata alla Presidenza il 12 novembre 1997 260 $a[Roma] :$bStab. Tip. Carlo Colombo,$c[1997] 300 $a199 p. ;$c30 cm. 440 0$aDisegni di legge e relazioni.$pDocumenti / Camera dei Deputati, Senato della Repubblica ;$n13. legislatura 500 $aIn testa al front.: Senato della Repubblica, Camera dei deputati; 13. legislatura, doc. 72., n. 1 907 $a.b14043944$b02-04-14$c05-03-12 912 $a991001625159707536 945 $aLE027 328.45 SEN01.11$g1$lle027$og$pE5.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i15387756$z05-03-12 996 $aRelazione sull'attuazione delle norme urgenti in materia di asilo politico, di ingresso e soggiorno di cittadini extracomunitari e di regolarizzazione dei cittadini extracomunitari...$9244938 997 $aUNISALENTO 998 $ale027$b20-01-12$cm$da $e-$fita$git $h0$i0 LEADER 05515nam 2200649 450 001 9910797934303321 005 20230125213806.0 010 $a1-60807-799-3 035 $a(CKB)3710000000570295 035 $a(EBL)1770467 035 $a(SSID)ssj0001457354 035 $a(PQKBManifestationID)12560297 035 $a(PQKBTitleCode)TC0001457354 035 $a(PQKBWorkID)11441739 035 $a(PQKB)10137626 035 $a(Au-PeEL)EBL1770467 035 $a(OCoLC)949847062 035 $a(CaBNVSL)mat09100086 035 $a(IEEE)9100086 035 $a(MiAaPQ)EBC1770467 035 $a(EXLCZ)993710000000570295 100 $a20200729d2014 uy 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aAdvances in statistical multisource-multitarget information fusion /$fRonald P.S. Mahler 210 1$aBoston :$cArtech House,$d©2014. 210 2$a[Piscataqay, New Jersey] :$cIEEE Xplore,$d[2014] 215 $a1 online resource (1167 p.) 225 1 $aArtech House electronic warfare library 300 $aDescription based upon print version of record. 311 $a1-60807-798-5 320 $aIncludes bibliographical references (pages 1089-1108) and index. 327 $aPreface; Acknowledgments; Chapter 1 Introduction to the Book; 1.1 OVERVIEW OF FINITE-SET STATISTICS; 1.2 RECENT ADVANCES IN FINITE-SET STATISTICS; 1.3 ORGANIZATION OF THE BOOK; Part I Elements of Finite-Set Statistics; Chapter 2 Random Finite Sets; 2.1 INTRODUCTION; 2.2 SINGLE-SENSOR, SINGLE-TARGET STATISTICS; 2.3 RANDOM FINITE SETS (RFSs); 2.4 MULTIOBJECT STATISTICS IN A NUTSHELL; Chapter 3 Multiobject Calculus; 3.1 INTRODUCTION; 3.2 BASIC CONCEPTS; 3.3 SET INTEGRALS; 3.4 MULTIOBJECT DIFFERENTIAL CALCULUS; 3.5 KEY FORMULAS OF MULTIOBJECT CALCULUS. 327 $aChapter 4 Multiobject Statistics4.1 INTRODUCTION; 4.2 BASIC MULTIOBJECT STATISTICAL DESCRIPTORS; 4.3 IMPORTANT MULTIOBJECT PROCESSES; 4.4 BASIC DERIVED RFSs; Chapter 5 Multiobject Modeling and Filtering; 5.1 INTRODUCTION; 5.2 THE MULTISENSOR-MULTITARGET BAYES FILTER; 5.3 MULTITARGET BAYES OPTIMALITY; 5.4 RFS MULTITARGET MOTION MODELS; 5.5 RFS MULTITARGET MEASUREMENT MODELS; 5.6 MULTITARGET MARKOV DENSITIES; 5.7 MULTISENSOR-MULTITARGET LIKELIHOOD FUNCTIONS; 5.8 THE MULTITARGET BAYES FILTER IN p.g.fl -- FORM; 5.9 THE FACTORED MULTITARGET BAYES FILTER; 5.10 APPROXIMATE MULTITARGET FILTERS. 327 $aChapter 6 Multiobject Metrology6.1 INTRODUCTION; 6.2 MULTIOBJECT MISS DISTANCE; 6.3 MULTIOBJECT INFORMATION FUNCTIONALS; Part II RFS Filters: StandardMeasurement Model; Chapter 7 Introduction to Part II; 7.1 SUMMARY OF MAJOR LESSONS LEARNED; 7.2 STANDARD MULTITARGET MEASUREMENT MODEL; 7.3 AN APPROXIMATE STANDARD LIKELIHOOD FUNCTION; 7.4 STANDARD MULTITARGET MOTION MODEL; 7.5 STANDARD MOTION MODEL WITH TARGET SPAWNING; 7.6 ORGANIZATION OF PART II; Chapter 8 Classical PHD and CPHD Filters; 8.1 INTRODUCTION; 8.2 A GENERAL PHD FILTER; 8.3 ARBITRARY-CLUTTER PHD FILTER; 8.4 CLASSICAL PHD FILTER. 327 $a8.5 CLASSICAL CARDINALIZED PHD (CPHD) FILTER8.6 ZERO FALSE ALARMS (ZFA) CPHD FILTER; 8.7 PHD FILTER FOR STATE-DEPENDENT POISSON CLUTTER; Chapter 9 Implementing Classical PHD/CPHDFilters; 9.1 INTRODUCTION; 9.2 "SPOOKY ACTION AT A DISTANCE"; 9.3 MERGING AND SPLITTING FOR PHD FILTERS; 9.4 MERGING AND SPLITTING FOR CPHD FILTERS; 9.5 GAUSSIAN MIXTURE (GM) IMPLEMENTATION; 9.6 SEQUENTIAL MONTE CARLO (SMC) IMPLEMENTATION; Chapter 10 Multisensor PHD and CPHD Filters; 10.1 INTRODUCTION; 10.2 THE MULTISENSOR-MULTITARGET BAYES FILTER; 10.3 THE GENERAL MULTISENSOR PHD FILTER. 327 $a10.4 THE MULTISENSOR CLASSICAL PHD FILTER10.5 ITERATED-CORRECTOR MULTISENSOR PHD/CPHD FILTERS; 10.6 PARALLEL COMBINATION MULTISENSOR PHD AND CPHD FILTERS; 10.7 AN ERRONEOUS "AVERAGED" MULTISENSOR PHD FILTER; 10.8 PERFORMANCE COMPARISONS; Chapter 11 Jump-Markov PHD/CPHD Filters; 11.1 INTRODUCTION; 11.2 JUMP-MARKOV FILTERS: A REVIEW; 11.3 MULTITARGET JUMP-MARKOV SYSTEMS; 11.4 JUMP-MARKOV PHD FILTER; 11.5 JUMP-MARKOV CPHD FILTER; 11.6 VARIABLE STATE SPACE JUMP-MARKOV CPHD FILTERS; 11.7 IMPLEMENTING JUMP-MARKOV PHD/CPHD FILTERS; 11.8 IMPLEMENTED JUMP-MARKOV PHD/CPHD FILTERS. 330 $aThis is the sequel to the 2007 Artech House bestselling title, Statistical Multisource-Multitarget Information Fusion. That earlier book was a comprehensive resource for an in-depth understanding of finite-set statistics (FISST), a unified, systematic, and Bayesian approach to information fusion. The cardinalized probability hypothesis density (CPHD) filter, which was first systematically described in the earlier book, has since become a standard multitarget detection and tracking technique, especially in research and development. Since 2007, FISST has inspired a considerable amount of research. 410 0$aArtech House electronic warfare library. 606 $aExpert systems (Computer science) 606 $aMultisensor data fusion$xMathematics 606 $aBayesian statistical decision theory 615 0$aExpert systems (Computer science) 615 0$aMultisensor data fusion$xMathematics. 615 0$aBayesian statistical decision theory. 676 $a006.33 700 $aMahler$b Ronald P. S.$0117425 801 0$bCaBNVSL 801 1$bCaBNVSL 801 2$bCaBNVSL 906 $aBOOK 912 $a9910797934303321 996 $aAdvances in statistical multisource-multitarget information fusion$93792040 997 $aUNINA