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Kalman Filtering Under Information Theoretic Criteria

This book provides several efficient Kalman filters (linear or nonlinear) under information theoretic criteria. They achieve excellent performance in complicated non-Gaussian noises with low computation complexity and have great practical application potential. The book combines all these perspectiv...

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Bibliografski detalji
Glavni autori: Chen, Badong (Autor), Dang, Lujuan (Autor), Zheng, Nanning (Autor), Principe, Jose C. (Autor)
Autor kompanije: SpringerLink (Online service)
Format: Elektronički e-knjiga
Jezik:engleski
Izdano: Cham : Springer International Publishing : Imprint: Springer, 2023.
Izdanje:1st ed. 2023.
Teme:
Signal processing.
Mathematical physics.
Econometrics.
Engineering mathematics.
Engineering > Data processing.
Artificial intelligence.
Signal, Speech and Image Processing.
Mathematical Methods in Physics.
Theoretical, Mathematical and Computational Physics.
Quantitative Economics.
Mathematical and Computational Engineering Applications.
Artificial Intelligence.
Online pristup:https://doi.org/10.1007/978-3-031-33764-2
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Sadržaj:
  • Chapter 1. Introduction
  • Chapter 2. Kalman filtering
  • Chapter 3. Information theoretic criteria
  • Chapter 4. Kalman Filtering Under Information Theoretic Criteria
  • Chapter 5. Extended Kalman Filtering Under Information Theoretic Criteria
  • Chapter 6. Unscented Kalman Filter Under Information Theoretic Criteria
  • Chapter 7. Cubature Kalman Filtering Under Information Theoretic Criteria
  • Chapter 8. Additional Topics in Kalman Filtering Under Information Theoretic Criteria.

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