.

0 (hodnocen0 x )

EB

ONLINE

1st ed.

Link\xE8oping : Linkopings Universitet, 2013

1 online resource (65 pages)

ISBN 9789175195599 (electronic bk.)

Link\xE8oping Studies in Science and Technology. Dissertations Series ; v.1530

Print version: Lindsten, Fredrik Particle Filters and Markov Chains for Learning of Dynamical Systems Link\xE8oping : Linkopings Universitet,c2013

Intro -- Abstract -- Popul\xE8arvetenskaplig sammanfattning -- Acknowledgments -- Contents -- Notation -- I Background -- 1 Introduction -- 1.1 Models of dynamical systems -- 1.2 Inference and learning -- 1.3 Contributions -- 1.4 Publications -- 1.5 Thesis outline -- 1.5.1 Outline of Part I -- 1.5.2 Outline of Part II -- 2 Learning of dynamical systems -- 2.1 Modeling -- 2.2 Maximum likelihood -- 2.3 Bayesian learning -- 2.4 Data augmentation -- 2.5 Online learning -- 3 Monte Carlo methods -- 3.1 The Monte Carlo idea -- 3.2 Rejection Sampling -- 3.3 Importance sampling -- 3.4 Particle filters and Markov chains -- 3.5 Rao-Blackwellization -- 4 Concluding remarks -- 4.1 Conclusions and future work -- 4.2 Further reading -- Bibliography.

001967106

express

(Au-PeEL)EBL3328047

(CaPaEBR)ebr10783627

(MiAaPQ)EBC3328047

(OCoLC)927227343