9789819905928 - Bayesian Real-Time System Identification: From Centralized to Distributed Approach de Huang, Ke; Yuen, Ka-Veng (10 resultados)

Condición: New.

Condición: New.

Hardcover. Condición: 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.

Buch. Condición: 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.

Hardcover. Condición: Brand New. 288 pages. 9.25x6.10x0.83 inches. In Stock.

Condición: new. Questo è un articolo print on demand.

Condición: 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.

Buch. Condición: 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.

Condición: New. PRINT ON DEMAND.

Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. 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 KG, Sachsenplatz 4-6, 1201 Wien 288 pp. Englisch.