An introduction to Kalman filtering with MATLAB examples /

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The Kalman filter is the Bayesian optimum solution to the problem of sequentially estimating the states of a dynamical system in which the state evolution and measurement processes are both linear and Gaussian. Given the ubiquity of such systems, the Kalman filter finds use in a variety of applicati...

Mô tả đầy đủ

Chi tiết về thư mục
Những tác giả chính: Kovvali, Narayan V. S. K. (Tác giả), Banavar, Mahesh K. (Tác giả), Spanias, Andreas (Tác giả)
Định dạng: eBook
Ngôn ngữ:English
Được phát hành: San Rafael, California (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool, 2014.
Loạt:Synthesis digital library of engineering and computer science.
Synthesis lectures on signal processing ; # 12.
Những chủ đề:
MATLAB.
Kalman filtering.
Bayesian estimation
dynamical system
Gaussian noise
Kalman filter
linearity
parameter estimation
sequential
state space model
tracking
Truy cập trực tuyến:Abstract with links to full text
Miêu tả
Tóm tắt:The Kalman filter is the Bayesian optimum solution to the problem of sequentially estimating the states of a dynamical system in which the state evolution and measurement processes are both linear and Gaussian. Given the ubiquity of such systems, the Kalman filter finds use in a variety of applications, e.g., target tracking, guidance and navigation, and communications systems. The purpose of this book is to present a brief introduction to Kalman filtering. The theoretical framework of the Kalman filter is first presented, followed by examples showing its use in practical applications. Extensions of the method to nonlinear problems and distributed applications are discussed. A software implementation of the algorithm in the MATLAB programming language is provided, as well as MATLAB code for several example applications discussed in the manuscript.
Mô tả sách:Part of: Synthesis digital library of engineering and computer science.
Series from website.
Mô tả vật lý:1 PDF (ix, 71 pages) : illustrations.
Also available in print.
Định dạng:Mode of access: World Wide Web.
System requirements: Adobe Acrobat Reader.
Thư mục:Includes bibliographical references (pages 67-70).
số ISBN:9781627051408
số ISSN:1932-1694 ;
Truy cập:Abstract freely available; full-text restricted to subscribers or individual document purchasers.

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