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Kalman filtering = with real-time ap...

Chui, Charles K.

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Kalman filtering = with real-time applications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Kalman filtering/ by Charles K. Chui, Guanrong Chen.
其他題名:	with real-time applications /
作者:	Chui, Charles K.
其他作者:	Chen, Guanrong.
出版者:	Cham :Springer International Publishing : : 2017.,
面頁冊數:	xviii, 247 p. :ill., digital ;24 cm.
內容註:	Preliminaries -- 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.
Contained By:	Springer eBooks
標題:	Kalman filtering. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-47612-4
ISBN:	9783319476124

Kalman filtering = with real-time applications /
Chui, Charles K.

Kalman filteringwith real-time applications /[electronic resource] :by Charles K. Chui, Guanrong Chen. - 5th ed. - Cham :Springer International Publishing :2017. - xviii, 247 p. :ill., digital ;24 cm.

Preliminaries -- 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.

This 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.

ISBN: 9783319476124

Standard No.: 10.1007/978-3-319-47612-4doiSubjects--Topical Terms:

544465
Kalman filtering.

LC Class. No.: QA402.3

Dewey Class. No.: 629.8312

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505 0 $a Preliminaries -- 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.
520 $a This 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.
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