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100   $a20130130d1999      u|             0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt
182   $cc
183   $acr
200 10$aKalman Filtering$b[electronic resource] $ewith Real-Time Applications /$fby Charles K. Chui, Guanrong Chen
205   $a3rd ed. 1999.
210  1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d1999.
215   $a1 online resource (XIV, 230 p.) 
225 1 $aSpringer Series in Information Sciences,$x0720-678X ;$v17
300   $aBibliographic Level Mode of Issuance: Monograph
311   $a3-540-64611-6 
320   $aIncludes bibliographical references and index.
327   $a1. Preliminaries -- 2. Kalman Filter: An Elementary Approach -- 3. Orthogonal Projection and Kalman Filter -- 4. Correlated System and Measurement Noise Processes -- 5. Colored Noise -- 6. Limiting Kalman Filter -- 7. Sequential and Square-Root Algorithms -- 8. Extended Kalman Filter and System Identification -- 9. Decoupling of Filtering Equations -- 10. Kalman Filtering for Interval Systems -- 11. Wavelet Kalman Filtering -- 12. Notes -- References -- Answers and Hints to Exercises.
330   $aKalman Filtering with Real-Time Applications presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering algorithms are derived via different approaches, including a direct method consisting of a series of elementary steps, and an indirect method based on innovation projection. Other topics include Kalman filtering for systems with correlated noise or colored noise, limiting Kalman filtering for time-invariant systems, extended Kalman filtering for nonlinear systems, interval Kalman filtering for uncertain systems, and wavelet Kalman filtering for multiresolution analysis of random signals. The last two topics are new additions to this third edition. Most filtering algorithms are illustrated by using simplified radar tracking examples. The style of the book is informal, and the mathematics is elementary but rigorous. The text is self-contained, suitable for self-study, and accessible to all readers with a minimum knowledge of linear algebra, probability theory, and system engineering.
410  0$aSpringer Series in Information Sciences,$x0720-678X ;$v17
606   $aPhysics
606   $aEconomic theory
606   $aApplied mathematics
606   $aEngineering mathematics
606   $aElectrical engineering
606   $aArtificial intelligence
606   $aMathematical Methods in Physics$3https://scigraph.springernature.com/ontologies/product-market-codes/P19013
606   $aNumerical and Computational Physics, Simulation$3https://scigraph.springernature.com/ontologies/product-market-codes/P19021
606   $aEconomic Theory/Quantitative Economics/Mathematical Methods$3https://scigraph.springernature.com/ontologies/product-market-codes/W29000
606   $aMathematical and Computational Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T11006
606   $aCommunications Engineering, Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/T24035
606   $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000
615  0$aPhysics.
615  0$aEconomic theory.
615  0$aApplied mathematics.
615  0$aEngineering mathematics.
615  0$aElectrical engineering.
615  0$aArtificial intelligence.
615 14$aMathematical Methods in Physics.
615 24$aNumerical and Computational Physics, Simulation.
615 24$aEconomic Theory/Quantitative Economics/Mathematical Methods.
615 24$aMathematical and Computational Engineering.
615 24$aCommunications Engineering, Networks.
615 24$aArtificial Intelligence.
676   $a629.8/312
700   $aChui$b Charles K$4aut$4http://id.loc.gov/vocabulary/relators/aut$022718
702   $aChen$b Guanrong$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910480363203321
996   $aKalman Filtering$92182298
997   $aUNINA