Multisensor Fusion Estimation Theory and Application (Record no. 75262)

000 -LEADER
fixed length control field 04170nam a22005895i 4500
001 - CONTROL NUMBER
control field 978-981-15-9426-7
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801213517.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 201111s2021 si | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9789811594267
-- 978-981-15-9426-7
082 04 - CLASSIFICATION NUMBER
Call Number 621.382
100 1# - AUTHOR NAME
Author Yan, Liping.
245 10 - TITLE STATEMENT
Title Multisensor Fusion Estimation Theory and Application
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2021.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XVII, 227 p. 59 illus., 46 illus. in color.
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction to Optimal Fusion Estimation and Kalman Filtering: Preliminaries -- Kalman Filtering of Discrete Dynamic Systems -- Optimal Kalman filtering Fusion for Linear Dynamic Systems with Cross-Correlated Sensor Noises -- Distributed Data Fusion for Multirate Sensor Networks -- Optimal Estimation for Multirate Systems with Unreliable Measurements and Correlated Noise -- Fusion Estimation for Asynchronous Multirate Multisensor Systems with Unreliable Measurements and Coupled Noises -- Multi-sensor Distributed Fusion Estimation for Systems with Network Delays, Uncertainties and Correlated Noises -- Event-triggered Centralized Fusion Estimation for Dynamic Systems with Correlated Noises -- Event-triggered Distributed Fusion Estimation for WSN Systems -- Event-triggered Sequential Fusion Estimation for Dynamic Systems with Correlated Noises -- Distributed Fusion Estimation for Multisensor Systems with Heavy-tailed Noises -- Sequential Fusion Estimation for Multisensor Systems with Heavy-tailed Noises.
520 ## - SUMMARY, ETC.
Summary, etc This book focuses on the basic theory and methods of multisensor data fusion state estimation and its application. It consists of four parts with 12 chapters. In Part I, the basic framework and methods of multisensor optimal estimation and the basic concepts of Kalman filtering are briefly and systematically introduced. In Part II, the data fusion state estimation algorithms under networked environment are introduced. Part III consists of three chapters, in which the fusion estimation algorithms under event-triggered mechanisms are introduced. Part IV consists of two chapters, in which fusion estimation for systems with non-Gaussian but heavy-tailed noises are introduced. The book is primarily intended for researchers and engineers in the field of data fusion and state estimation. It also benefits for both graduate and undergraduate students who are interested in target tracking, navigation, networked control, etc.
700 1# - AUTHOR 2
Author 2 Jiang, Lu.
700 1# - AUTHOR 2
Author 2 Xia, Yuanqing.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-981-15-9426-7
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Singapore :
-- Springer Nature Singapore :
-- Imprint: Springer,
-- 2021.
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-- text
-- txt
-- rdacontent
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-- computer
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-- rdamedia
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-- online resource
-- cr
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-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Telecommunication.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Control engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal processing.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering—Data processing.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Communications Engineering, Networks.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Control and Systems Theory.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal, Speech and Image Processing .
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data Engineering.
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-- ZDB-2-ENG
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-- ZDB-2-SXE

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