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(Ebook) Bayesian Real-Time System Identification: From Centralized to Distributed Approach by Ke Huang, Ka-Veng Yuen ISBN 9789819905928, 9789819905935, 9819905923, 9819905931

  • SKU: EBN-48270250
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Instant download (eBook) Bayesian Real-Time System Identification: From Centralized to Distributed Approach after payment.
Authors:Ke Huang, Ka-Veng Yuen
Pages:286 pages.
Year:2023
Editon:1
Publisher:Springer, Springer Nature Singapore
Language:english
File Size:13.48 MB
Format:pdf
ISBNS:9789819905928, 9789819905935, 9819905923, 9819905931
Categories: Ebooks

Product desciption

(Ebook) Bayesian Real-Time System Identification: From Centralized to Distributed Approach by Ke Huang, Ka-Veng Yuen ISBN 9789819905928, 9789819905935, 9819905923, 9819905931

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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