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Stable and efficient cubature-based ...

Ballreich, Dominik.

Stable and efficient cubature-based filtering in dynamical systems

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Stable and efficient cubature-based filtering in dynamical systemsby Dominik Ballreich.
作者:	Ballreich, Dominik.
出版者:	Cham :Springer International Publishing :2017.
面頁冊數:	xvii, 160 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Cubature formulas.
電子資源:	http://dx.doi.org/10.1007/978-3-319-62130-2
ISBN:	9783319621302$q(electronic bk.)

Stable and efficient cubature-based filtering in dynamical systems
Ballreich, Dominik.

Stable and efficient cubature-based filtering in dynamical systems[electronic resource] /by Dominik Ballreich. - Cham :Springer International Publishing :2017. - xvii, 160 p. :ill., digital ;24 cm.

Introduction -- Filtering in Dynamical Systems -- Deterministic Numerical Integration -- Optimization and Stabilization of Cubature Rules -- Simulation Studies -- Results -- Appendices -- Index -- Bibliography.

The book addresses the problem of calculation of d-dimensional integrals (conditional expectations) in filter problems. It develops new methods of deterministic numerical integration, which can be used to speed up and stabilize filter algorithms. With the help of these methods, better estimates and predictions of latent variables are made possible in the fields of economics, engineering and physics. The resulting procedures are tested within four detailed simulation studies.

ISBN: 9783319621302$q(electronic bk.)

Standard No.: 10.1007/978-3-319-62130-2doiSubjects--Topical Terms:

791356
Cubature formulas.

LC Class. No.: QA299.4.C83 / B35 2017

Dewey Class. No.: 515.43

Stable and efficient cubature-based filtering in dynamical systems
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505 0 $a Introduction -- Filtering in Dynamical Systems -- Deterministic Numerical Integration -- Optimization and Stabilization of Cubature Rules -- Simulation Studies -- Results -- Appendices -- Index -- Bibliography.
520 $a The book addresses the problem of calculation of d-dimensional integrals (conditional expectations) in filter problems. It develops new methods of deterministic numerical integration, which can be used to speed up and stabilize filter algorithms. With the help of these methods, better estimates and predictions of latent variables are made possible in the fields of economics, engineering and physics. The resulting procedures are tested within four detailed simulation studies.
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