Kalman Filtering: with Real-Time Applications

Chui, Charles K. K.; Chen, Guanrong

ISBN 10: 3642099661 / ISBN 13: 9783642099663

Verlag: Springer, 2010

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In. Bestandsnummer des Verkäufers ria9783642099663_new

Bibliografische Details

Titel: Kalman Filtering: with Real-Time Applications

Verlag: Springer

Erscheinungsdatum: 2010

Einband: Softcover

Zustand: New

Über diesen Titel

Inhaltsangabe:

Book by Chui Charles K Chen Guanrong

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From the reviews:

“To summarize, the authors have succeeded in bringing together the mathematical theory and the needs of practitioners. The newly added chapters, in particular the one on wavelets, give the book a proper finish. For a book of this size, it leaves little to be desired. It presents a wealth of details while at the same time avoiding unnecessary abstraction.” (Andreas Ruppin, Berlin, Germany (SSN Stat. Software News, 2000, 34,3-4)

"A rigorous and concise introduction to Kalman filtering is presented in this well-written book. It is suitable for graduate studies, as well as refresher courses and self-study. ... One of the strong features of the book is that Kalman filtering is presented from a few different viewpoints. ... The many end-of-chapters exercises--and the section at the end of the book with solutions and hints to several of them--are another strong feature of the book." (Vladimir Botchev, ACM Computing Reviews, July, 2009)

From the reviews of the third edition:

“The proofs and derivations in the third edition of Kalman Filtering with Real-Time Applications lead to a deep understanding of the linear Kalman filter algorithm as an optimal estimator for the state sequence in a system with stochastic dynamics and measurements. It is a good book for researchers with a strong mathematical background who will be building Kalman filters and smoothers. It is also a good text for teaching a course on linear Kalman filtering and some of its extensions.” (Bradley M. Bell, SIAM Review, Vol. 52 (2), 2010)

From the reviews of the fourth edition:

“It is written not only for self-study but also for use in a one-quarter or one-semester introductory course on Kalman filtering theory for upper-division undergraduate or first-year graduate to applied mathematics or engineering students. In addition, it is hoped that it will become a valuable reference to any industrial or government engineer.” (George S. Stavrakakis, Zentralblatt MATH, Vol. 1206, 2011)