Kalman Filtering Under Information Theoretic Criteria

Badong Chen (), Lujuan Dang (), Nanning Zheng () and Jose C. Principe ()
Additional contact information
Badong Chen: National Engineering Research Center for Visual Information and Applications, and Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, National Key Laboratory of Human-Machine Hybrid Augmented Intelligence
Lujuan Dang: National Engineering Research Center for Visual Information and Applications, and Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, National Key Laboratory of Human-Machine Hybrid Augmented Intelligence
Nanning Zheng: National Engineering Research Center for Visual Information and Applications, and Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, National Key Laboratory of Human-Machine Hybrid Augmented Intelligence
Jose C. Principe: University of Florida, Electrical and Computer Engineering Department

in Springer Books from Springer

Date: 2023
ISBN: 978-3-031-33764-2
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Chapters in this book:

Ch Chapter 1 Introduction

Badong Chen, Lujuan Dang, Nanning Zheng and Jose C. Principe

Ch Chapter 2 Kalman Filtering

Badong Chen, Lujuan Dang, Nanning Zheng and Jose C. Principe

Ch Chapter 3 Information Theoretic Criteria

Badong Chen, Lujuan Dang, Nanning Zheng and Jose C. Principe

Ch Chapter 4 Kalman Filtering Under Information Theoretic Criteria

Badong Chen, Lujuan Dang, Nanning Zheng and Jose C. Principe

Ch Chapter 5 Extended Kalman Filtering Under Information Theoretic Criteria

Badong Chen, Lujuan Dang, Nanning Zheng and Jose C. Principe

Ch Chapter 6 Unscented Kalman Filter Under Information Theoretic Criteria

Badong Chen, Lujuan Dang, Nanning Zheng and Jose C. Principe

Ch Chapter 7 Cubature Kalman Filtering Under Information Theoretic Criteria

Badong Chen, Lujuan Dang, Nanning Zheng and Jose C. Principe

Ch Chapter 8 Additional Topics in Kalman Filtering Under Information Theoretic Criteria

Badong Chen, Lujuan Dang, Nanning Zheng and Jose C. Principe

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DOI: 10.1007/978-3-031-33764-2

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