LEADER 01109nam0-22003491i-450 001 990001096410403321 005 20190521153502.0 010 $a3-540-51617-4 035 $a000109641 035 $aFED01000109641 035 $a(Aleph)000109641FED01 035 $a000109641 100 $a20020001d1989----km-y0itay50------ba 101 0 $aeng 200 1 $aPDEs and Continuum Models of Phase Transitions$eProceedings of an NSF-CNRS Joint Seminar held in Nice, France, January 18-22, 1988$fM. Rascle, D. Serre, M. Slemrod (Eds.) 210 $aBerlin [etc.]$cSpringer-Verlag$d1989 215 $aV, 229 p.$d25 cm 225 1 $aLecture notes in physics$v344 610 0 $aMeccanica statistica 676 $a530.13 700 1$aRascle,$bMichel$042658 702 1$aSerre,$bDenis$f<1954- > 702 1$aSlemrod,$bMarshall 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990001096410403321 952 $a21-170F$b16921$fFI1 952 $a02 56 B 12$b6161$fFINBN 959 $aFINBN 959 $aFI1 996 $aPDEs and Continuum Models of Phase Transitions$9335415 997 $aUNINA LEADER 01957nam 2200421z- 450 001 9910346783603321 005 20210211 010 $a1000045491 035 $a(CKB)4920000000100687 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/54758 035 $a(oapen)doab54758 035 $a(EXLCZ)994920000000100687 100 $a20202102d2015 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aNonlinear Gaussian Filtering : Theory, Algorithms, and Applications 210 $cKIT Scientific Publishing$d2015 215 $a1 online resource (V, 270 p. p.) 225 1 $aKarlsruher Schriften zur Anthropomatik / Lehrstuhl für Interaktive Echtzeitsysteme, Karlsruher Institut für Technologie ; Fraunhofer-Inst. für Optronik, Systemtechnik und Bildauswertung IOSB Karlsruhe 311 08$a3-7315-0338-7 330 $aBy restricting to Gaussian distributions, the optimal Bayesian filtering problem can be transformed into an algebraically simple form, which allows for computationally efficient algorithms. Three problem settings are discussed in this thesis: (1) filtering with Gaussians only, (2) Gaussian mixture filtering for strong nonlinearities, (3) Gaussian process filtering for purely data-driven scenarios. For each setting, efficient algorithms are derived and applied to real-world problems. 517 $aNonlinear Gaussian Filtering 610 $aBayes'sche Statistik 610 $afiltering 610 $aGaussian processes 610 $aGaußprozesseBayesian statistics 610 $aKalman filter 610 $aKalman-Filter 610 $astate estimation 610 $aZustandsscha?tzung 700 $aHuber$b Marco$4auth$01302254 906 $aBOOK 912 $a9910346783603321 996 $aNonlinear Gaussian Filtering : Theory, Algorithms, and Applications$93031361 997 $aUNINA