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000780623 019__ $$a981847036$$a981985813$$a982008248$$a984847330
000780623 020__ $$a9783319476124$$q(electronic book)
000780623 020__ $$a3319476122$$q(electronic book)
000780623 020__ $$z9783319476100
000780623 020__ $$z3319476106
000780623 0247_ $$a10.1007/978-3-319-47612-4$$2doi
000780623 035__ $$aSP(OCoLC)ocn981460736
000780623 035__ $$aSP(OCoLC)981460736$$z(OCoLC)981847036$$z(OCoLC)981985813$$z(OCoLC)982008248$$z(OCoLC)984847330
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000780623 049__ $$aISEA
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000780623 08204 $$a629.8/312$$223
000780623 1001_ $$aChui, C. K.,$$eauthor.
000780623 24510 $$aKalman filtering :$$bwith real-time applications /$$cCharles K. Chui, Guanrong Chen.
000780623 250__ $$aFifth edition.
000780623 264_1 $$aCham, Switzerland :$$bSpringer,$$c2017.
000780623 300__ $$a1 online resource (xviii, 247 pages) :$$billustrations
000780623 336__ $$atext$$btxt$$2rdacontent
000780623 337__ $$acomputer$$bc$$2rdamedia
000780623 338__ $$aonline resource$$bcr$$2rdacarrier
000780623 347__ $$atext file$$bPDF$$2rda
000780623 504__ $$aIncludes bibliographical references and index.
000780623 5050_ $$aPreliminaries -- Kalman Filter: An Elementary Approach -- Orthogonal Projection and Kalman Filter -- Correlated System and Measurement Noise Processes -- Colored Noise -- Limiting Kalman Filter -- Sequential and Square-Root Algorithms -- Extended Kalman Filter and System Identification -- Decoupling of Filtering Equations -- Kalman Filtering for Interval Systems -- Wavelet Kalman Filtering -- Distributed Estimation on Sensor Networks -- Notes -- Answers and Hints to Exercises.
000780623 506__ $$aAccess limited to authorized users.
000780623 520__ $$aThis new edition 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. 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. Over 100 exercises and problems with solutions help deepen the knowledge. This new edition has a new chapter on filtering communication networks and data processing, together with new exercises and new real-time applications.
000780623 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed April 5, 2017).
000780623 650_0 $$aKalman filtering.
000780623 7001_ $$aChen, G.$$q(Guanrong),$$eauthor.
000780623 77608 $$iPrint version:$$z3319476106$$z9783319476100$$w(OCoLC)958355715
000780623 852__ $$bebk
000780623 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-47612-4$$zOnline Access$$91397441.1
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000780623 980__ $$aEBOOK
000780623 980__ $$aBIB
000780623 982__ $$aEbook
000780623 983__ $$aOnline
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