Bayesian estimation and tracking : | a practical guide / (Record no. 104018)

MARC details
000 -LEADER
fixed length control field 02737cam a2200241 a 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 111201s2012 njua b 001 0 eng
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780470621707
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 0470621702
040 ## - CATALOGING SOURCE
Original cataloging agency SDU
050 00 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA279.5
Item number H371 B 2012
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Haug, Anton J.,
245 10 - TITLE STATEMENT
Title Bayesian estimation and tracking :
Remainder of title a practical guide /
Statement of responsibility, etc. Anton J. Haug.
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Hoboken, N.J. :
Name of publisher, distributor, etc. Wiley,
Date of publication, distribution, etc. 2012.
300 ## - PHYSICAL DESCRIPTION
Extent 369 p. :
Other physical details ill.
505 ## - Formatted Contents Note
Formatted contents note HKBU library
518 ## - DATE/TIME AND PLACE OF AN EVENT NOTE
DATE/TIME AND PLACE OF AN EVENT NOTE YT2025 M10
520 ## - SUMMARY
Summary "This book presents a practical approach to estimation methods that are designed to provide a clear path to programming all algorithms. Readers are provided with a firm understanding of Bayesian estimation methods and their interrelatedness. Starting with fundamental principles of Bayesian theory, the book shows how each tracking filter is derived from a slight modification to a previous filter. Such a development gives readers a broader understanding of the hierarchy of Bayesian estimation and tracking. Following the discussions about each tracking filter, the filter is put into block diagram form for ease in future recall and reference. The book presents a completely unified approach to Bayesian estimation and tracking, and this is accomplished by showing that the current posterior density for a state vector can be linked to its previous posterior density through the use of Bayes' Law and the Chapman-Kolmogorov integral. Predictive point estimates are then shown to be density-weighted integrals of nonlinear functions. The book also presents a methodology that makes implementation of the estimation methods simple (or, rather, simpler than they have been in the past). Each algorithm is accompanied by a block diagram that illustrates how all parts of the tracking filter are linked in a never-ending chain, from initialization to the loss of track. These filter block diagrams provide a ready picture for implementing the algorithms into programmable code. In addition, four completely worked out case studies give readers examples of implementation, from simulation models that generate noisy observations to worked-out applications for all tracking algorithms. This book also presents the development and application of track performance metrics, including how to generate error ellipses when implementing in real-world applications, how to calculate RMS errors in simulation environments, and how to calculate Cramer-Rao lower bounds for the RMS errors. These are also illustrated in the case study presentations"--
650 #0 - SUBJECT
Topical term Bayesian statistical decision theory.
650 #0 - SUBJECT
Topical term Automatic tracking
General subdivision Mathematics.
650 #0 - SUBJECT
Topical term Estimation theory.
900 ## - Accession Number
Accession Number = C.1 SDU
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type English Books
Source of classification or shelving scheme Library of Congress Classification
100 1# - MAIN ENTRY--PERSONAL NAME
-- 193292
650 #0 - SUBJECT
-- 193293
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Shelving location Date acquired Source of acquisition Total Checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
    Library of Congress Classification   Available for Loans General Books MATRIX Library MATRIX Library General Eng/FL.3 03/10/2025 Donation   QA279.5 H371 B 2012 1000386001 03/10/2025 C.1 03/10/2025 English Books
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