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Bayesian Real-Time System Identification From Centralized to Distributed Approach /

This book introduces some recent developments in Bayesian real-time system identification. It contains two different perspectives on data processing for system identification, namely centralized and distributed. A centralized Bayesian identification framework is presented to address challenging prob...

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Opis bibliograficzny
Główni autorzy: Huang, Ke (Autor), Yuen, Ka-Veng (Autor)
Korporacja: SpringerLink (Online service)
Format: Elektroniczne E-book
Język:angielski
Wydane: Singapore : Springer Nature Singapore : Imprint: Springer, 2023.
Wydanie:1st ed. 2023.
Hasła przedmiotowe:
Dynamics.
Nonlinear theories.
Statistics .
Civil engineering.
Applied Dynamical Systems.
Bayesian Inference.
Civil Engineering.
Dostęp online:https://doi.org/10.1007/978-981-99-0593-5
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Spis treści:
  • Chapter 1. Introduction
  • Chapter 2. System identification by Kalman filter and extended Kalman filter
  • Chapter 3. Outlier detection for real-time system identification
  • Chapter 4. Real-time updating of noise parameters for structural identification
  • Chapter 5. Bayesian model class selection for real-time system identification
  • Chapter 6. Online distributed identification for wireless sensor networks
  • Chapter 7. Online distributed identification handling asynchronous data and multiple outlier-corrupted data.

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