LEADER 02364nam0 2200517 i 450 001 VAN0123799 005 20230704114142.979 017 70$2N$a9783319621302 100 $a20191002d2017 |0itac50 ba 101 $aeng 102 $aCH 105 $a|||| ||||| 200 1 $aStable and Efficient Cubature-based Filtering in Dynamical Systems$fDominik Ballreich 210 $aCham$cSpringer$d2017 215 $axvii, 160 p.$cill.$d24 cm 500 1$3VAN0235988$aStable and Efficient Cubature-based Filtering in Dynamical Systems$91562280 606 $a65-XX$xNumerical analysis [MSC 2020]$3VANC019772$2MF 606 $a65D30$xNumerical integration [MSC 2020]$3VANC023175$2MF 606 $a62F15$xBayesian inference [MSC 2020]$3VANC024528$2MF 606 $a62-08$xComputational methods for problems pertaining to statistics [MSC 2020]$3VANC035191$2MF 610 $aCubature Kalman filter$9KW:K 610 $aDeterministic numerical integration$9KW:K 610 $aFiltering in dynamical systems$9KW:K 610 $aGinzburg-Landau model$9KW:K 610 $aKalman Filter$9KW:K 610 $aLorenz model$9KW:K 610 $aMaximum likelihood estimation$9KW:K 610 $aNumerical integration$9KW:K 610 $aOptimization and stabilization of cubature rules$9KW:K 610 $aRecursive Bayesian estimation$9KW:K 610 $aSix-dimentional coordinated turn model$9KW:K 610 $aSmolyak cubature$9KW:K 610 $aSmolyak cubature rules with an approximate degree of exactness$9KW:K 610 $aState-space models$9KW:K 610 $aUnivariate non-stationary growth model$9KW:K 620 $aCH$dCham$3VANL001889 700 1$aBallreich$bDominik$3VANV095257$0767384 712 $aSpringer $3VANV108073$4650 801 $aIT$bSOL$c20240614$gRICA 856 4 $uhttp://doi.org/10.1007/978-3-319-62130-2$zE-book ? Accesso al full-text attraverso riconoscimento IP di Ateneo, proxy e/o Shibboleth 899 $aBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$1IT-CE0120$2VAN08 912 $fN 912 $aVAN0123799 950 $aBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$d08CONS e-book 0907 $e08eMF907 20191002 996 $aStable and Efficient Cubature-based Filtering in Dynamical Systems$91562280 997 $aUNICAMPANIA