Bayesian Real-Time System Identification : From Centralized to Distributed Approach Paperback / softback
by Ke Huang, Ka-Veng Yuen
Paperback / softback
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Description
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.
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Out of StockMore expected soonContact us for further information
- Format:Paperback / softback
- Pages:276 pages, 127 Illustrations, color; 27 Illustrations, black and white; XII, 276 p. 154 illus., 127
- Publisher:Springer Verlag, Singapore
- Publication Date:22/03/2024
- Category:
- ISBN:9789819905959
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£96.42
Information
-
Out of StockMore expected soonContact us for further information
- Format:Paperback / softback
- Pages:276 pages, 127 Illustrations, color; 27 Illustrations, black and white; XII, 276 p. 154 illus., 127
- Publisher:Springer Verlag, Singapore
- Publication Date:22/03/2024
- Category:
- ISBN:9789819905959