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Kniha Bayesian Real-Time System Identification Ke Huang

Bayesian Real-Time System Identification

From Centralized to Distributed Approach

Autor: Ke Huang, Ka-Veng Yuen
Jazyk: Angličtina
Vazba: Pevná
Vydavatel: Springer, Berlin
Dostupnost: Skladem u dodavatele
Odesíláme za 10-13 dnů
3 882 Kč
This book introduces some recent developments in Bayesian real-time system identification. It contai...

Informace o knize

Autor
Ke Huang, Ka-Veng Yuen
Jazyk
Angličtina
Vazba
Kniha - Pevná
Vydáno
2023
Stránek
290
EAN
9789819905928
Enbook ID
42852618
Vydavatel
Springer, Berlin
Hmotnost
634
Rozměry
155 x 235

Kompletní popis

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 researchers in civil and mechanical engineering. Practitioners can also find useful reference guide for solving engineering problems.

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