Bayesian Real-time System Identification: From Centralized to Distributed Approach - Couverture rigide
Synopsis
This book introduces some recent developments in Bayesian real-time system identification. 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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Ke 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.
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Bayesian Real-Time System Identification: From Centralized to Distributed Approach
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Bayesian Real-Time System Identification (Hardcover)
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Hardcover. Etat : new. Hardcover. 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. This book introduces some recent developments in Bayesian real-time system identification. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9789819905928
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Bayesian Real-Time System Identification
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 fram. N° de réf. du vendeur 803182829
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Bayesian Real-Time System Identification
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ISBN 13 : 9789819905928
Neuf
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 288 pp. Englisch. N° de réf. du vendeur 9789819905928
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Bayesian Real-Time System Identification: From Centralized to Distributed Approach
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Bayesian Real-Time System Identification: From Centralized to Distributed Approach
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Bayesian Real-Time System Identification | From Centralized to Distributed Approach
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Buch. Etat : Neu. Bayesian Real-Time System Identification | From Centralized to Distributed Approach | Ke Huang (u. a.) | Buch | xii | Englisch | 2023 | Springer | EAN 9789819905928 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. N° de réf. du vendeur 126494024
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Bayesian Real-Time System Identification
Edité par
Springer Nature Singapore, Springer Nature Singapore Mär 2023, 2023
ISBN 10 : 9819905923
ISBN 13 : 9789819905928
Neuf
Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Buch. Etat : Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 288 pp. Englisch. N° de réf. du vendeur 9789819905928
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Bayesian Real-Time System Identification : From Centralized to Distributed Approach
Edité par
Springer, Springer Nature Singapore, 2023
ISBN 10 : 9819905923
ISBN 13 : 9789819905928
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. N° de réf. du vendeur 9789819905928
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BAYESIAN REAL TIME SYSTEM IDENTIFICATION FROM CENTRALIZED TO DISTRIBUTED APPROACH (HB 2023)
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