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Bayesian Real-Time System Identification : From Centralized to Distributed Approach / / by Ke Huang, Ka-Veng Yuen



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Autore: Huang Ke Visualizza persona
Titolo: Bayesian Real-Time System Identification : From Centralized to Distributed Approach / / by Ke Huang, Ka-Veng Yuen Visualizza cluster
Pubblicazione: Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Edizione: 1st ed. 2023.
Descrizione fisica: 1 online resource (286 pages)
Disciplina: 519.542
Soggetto topico: Dynamics
Nonlinear theories
Statistics
Civil engineering
Applied Dynamical Systems
Bayesian Inference
Civil Engineering
Persona (resp. second.): YuenKa-Veng
Nota di bibliografia: Includes bibliographical references.
Nota di contenuto: 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.
Sommario/riassunto: 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 problems of real-time parameter estimation, which covers outlier detection, system, and noise parameters tracking. Besides, real-time Bayesian model class selection is introduced to tackle model misspecification problem. On the other hand, a distributed Bayesian identification framework is presented to handle asynchronous data and multiple outlier corrupted data. This book provides sufficient background to follow Bayesian methods for solving real-time system identification problems in civil and other engineering disciplines. The illustrative examples allow the readers to quickly understand the algorithms and associated applications. This book is intended for graduate students and researchersin civil and mechanical engineering. Practitioners can also find useful reference guide for solving engineering problems.
Titolo autorizzato: Bayesian real-time system identification  Visualizza cluster
ISBN: 9789819905935
9819905931
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910682562103321
Lo trovi qui: Univ. Federico II
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