LEADER 01149nam--2200373---450- 001 990001076820203316 005 20060217111658.0 035 $a000107682 035 $aUSA01000107682 035 $a(ALEPH)000107682USA01 035 $a000107682 100 $a20020507d2001----km-y0itaa0103----ba 105 $ay|||z|||001yy 200 1 $aBenvenuto Cellini$ela protesta di un irregolare$fVittorio Gatto 210 $aNapoli$cLguori$dcopyr.2001 215 $a66 p.$d24 cm 225 2 $aDomini 410 0$12001$aCritica e letteratura$v29 410 0$12001$aCritica e letteratura 604 $aBenvenuto, Cellini La vita 676 $a858.403 700 1$aGATTO,$bVittorio$0135291 801 0$aIT$bsalbc$gISBD 912 $a990001076820203316 951 $aVI.3.B. 1416(V B 1106)$b162405 L.M.$cV B$d00081899 959 $aBK 969 $aUMA 979 $aSTELLA$b10$c20020507$lUSA01$h1208 979 $aPAOLA$b90$c20020522$lUSA01$h1652 979 $aPAOLA$b90$c20020522$lUSA01$h1653 979 $aPATRY$b90$c20040406$lUSA01$h1715 979 $aCOPAT7$b90$c20060217$lUSA01$h1116 996 $aBenvenuto Cellini$9979252 997 $aUNISA LEADER 00929nam a2200253 i 4500 001 991002111669707536 005 20020503161233.0 008 010104s1983 fr ||| | fre 035 $ab10318197-39ule_inst 035 $aEXGIL97632$9ExL 040 $aBiblioteca Interfacoltà$bita 082 0 $a741.60924 100 1 $aRoque, Georges$0466625 245 10$aCeci n'est pas un Magritte :$bessai sur Magritte et la publicité /$cGeorges Roque 260 $aParis :$bFlammarion,$cc1983 300 $a206 p. :$bill. (alcune color.) ;$c24 cm. 650 4$aMagritte, René 650 4$aOpere d'arte - Commercio 907 $a.b10318197$b02-04-14$c27-06-02 912 $a991002111669707536 945 $aLE002 Lett. II F 3$g1$i2002000507587$lle002$o-$pE0.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i10375247$z27-06-02 996 $aCeci n'est pas un Magritte$9200841 997 $aUNISALENTO 998 $ale002$b01-01-01$cm$da $e-$ffre$gfr $h0$i1 LEADER 05515nam 2200649 450 001 9910816058003321 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 $a9910816058003321 996 $aAdvances in statistical multisource-multitarget information fusion$94093349 997 $aUNINA