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100 1 _aHuang, Ke.
_eauthor.
_0(orcid)0000-0002-3625-3937
_1https://orcid.org/0000-0002-3625-3937
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aBayesian Real-Time System Identification
_h[electronic resource] :
_bFrom Centralized to Distributed Approach /
_cby Ke Huang, Ka-Veng Yuen.
250 _a1st ed. 2023.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2023.
300 _aXII, 276 p. 154 illus., 127 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
500 _aAcceso multiusuario
505 0 _aChapter 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.
520 _aThis 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.
541 _fUABC ;
_cPerpetuidad
650 0 _aDynamics.
650 0 _aNonlinear theories.
650 0 _aStatistics .
650 0 _aCivil engineering.
650 1 4 _aApplied Dynamical Systems.
650 2 4 _aBayesian Inference.
650 2 4 _aCivil Engineering.
700 1 _aYuen, Ka-Veng.
_eauthor.
_0(orcid)0000-0002-1755-6668
_1https://orcid.org/0000-0002-1755-6668
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789819905928
776 0 8 _iPrinted edition:
_z9789819905942
776 0 8 _iPrinted edition:
_z9789819905959
856 4 0 _zLibro electrónico
_uhttp://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-981-99-0593-5
912 _aZDB-2-ENG
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