|
![]() |
|||
|
||||
OverviewThis 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. Full Product DetailsAuthor: Ke Huang , Ka-Veng YuenPublisher: Springer Verlag, Singapore Imprint: Springer Verlag, Singapore Edition: 1st ed. 2023 ISBN: 9789819905959ISBN 10: 9819905958 Pages: 276 Publication Date: 22 March 2024 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand ![]() We will order this item for you from a manufactured on demand supplier. Table of ContentsChapter 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.ReviewsAuthor InformationKe Huang received her Ph.D. in civil engineering from the University of Macau. She is currently Assistant Professor of the School of Civil Engineering at the Changsha University of Science and Technology. Her research expertise includes substructural identification, distributed identification, and online estimation. Ka-Veng Yuen received his Ph.D. in civil engineering from the California Institute of Technology. He is Distinguished Professor of Civil and Environmental Engineering at the University of Macau. The research expertise of Prof. KV Yuen includes Bayesian inference, uncertainty quantification, system identification, structural health monitoring, reliability analysis, and analysis of dynamical systems. He is Single Author of the book “Bayesian Methods for Structural Dynamics and Civil Engineering” published by John Wiley and Sons. He is also Recipient of the Young Investigator Award of the International Chinese Association on Computational Mechanics in 2011. He is Editorial Board Member of Computer-Aided Civil and Infrastructure Engineering, Structural Control and Health Monitoring, and International Journal for Uncertainty Quantification, etc. Tab Content 6Author Website:Countries AvailableAll regions |