Filtrage et lissage statistiques optimaux linéaires / J.-C. Radix

Auteur: Radix, Jean-Claude - AuteurType de document: MonographieCollection: Ecole nationale supérieure de techniques avancées ; 4Langue: françaisPays: FranceÉditeur: Toulouse : Cépaduès, 1984Description: 1 vol. (350 p.) ; 25 cm ISBN: 2854280830 ; br. Note: This course introduces linear filtering and smoothing from an engineering viewpoint. The mathematical knowledge in probability theory and linear algebra which is needed is elementary and is reviewed; on the other hand, several examples are worked out; the equations are clearly written and intuitive explanation of the algorithms and results is emphasized. Firstly, Kalman filtering is studied, both is continuous and discrete time; the various classical generalizations of the initial problem are also discussed (coloured noise, correlated noise, nonlinear systems). Secondly, the different classical formulations of the smoothing problem are stated and solved; examples of algorithms are provided with graphical representations of the results. Finally, after a theoretical study of the factorization of matrices, square root filtering algorithms are derived; in an appendix computer programs are given. (Zentralblatt)Bibliographie: Bibliogr. p. 240-243 et 350. Sujets MSC: 93E11 Systems theory; control -- Stochastic systems and control -- Filtering
93-01 Systems theory; control -- Instructional exposition (textbooks, tutorial papers, etc.)
93E14 Systems theory; control -- Stochastic systems and control -- Data smoothing
93C10 Systems theory; control -- Control systems -- Nonlinear systems
62M20 Statistics -- Inference from stochastic processes -- Prediction; filtering
Location Call Number Status Date Due
Salle E 09831-01 / Manuels RAD (Browse Shelf) Available
Salle E 09831-02 / Manuels RAD (Browse Shelf) Available

This course introduces linear filtering and smoothing from an engineering viewpoint. The mathematical knowledge in probability theory and linear algebra which is needed is elementary and is reviewed; on the other hand, several examples are worked out; the equations are clearly written and intuitive explanation of the algorithms and results is emphasized. Firstly, Kalman filtering is studied, both is continuous and discrete time; the various classical generalizations of the initial problem are also discussed (coloured noise, correlated noise, nonlinear systems). Secondly, the different classical formulations of the smoothing problem are stated and solved; examples of algorithms are provided with graphical representations of the results. Finally, after a theoretical study of the factorization of matrices, square root filtering algorithms are derived; in an appendix computer programs are given. (Zentralblatt)

Bibliogr. p. 240-243 et 350

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