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Event-based state estimation = a sto...

Shi, Dawei.

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Event-based state estimation = a stochastic perspective /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Event-based state estimation/ by Dawei Shi, Ling Shi, Tongwen Chen.
Reminder of title:	a stochastic perspective /
Author:	Shi, Dawei.
other author:	Shi, Ling.
Published:	Cham :Springer International Publishing : : 2016.,
Description:	xiii, 208 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Linear Gaussian Systems and Event-Based State Estimation -- Event-Triggered Sampling -- Approximate Optimal Filtering Approaches -- Constrained Optimization Approach -- Set-Valued Filtering Approach -- Probabilistic Approach -- Communications Rate Analysis -- Open Problems -- Appendices: Brief Review of Probability Theory; Linear Estimation Theory.
Contained By:	Springer eBooks
Subject:	Discrete-time systems. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-26606-0
ISBN:	9783319266060$q(electronic bk.)

Event-based state estimation = a stochastic perspective /
Shi, Dawei.

Event-based state estimationa stochastic perspective /[electronic resource] :by Dawei Shi, Ling Shi, Tongwen Chen. - Cham :Springer International Publishing :2016. - xiii, 208 p. :ill., digital ;24 cm. - Studies in systems, decision and control,v.412198-4182 ;. - Studies in systems, decision and control ;v.3..

Introduction -- Linear Gaussian Systems and Event-Based State Estimation -- Event-Triggered Sampling -- Approximate Optimal Filtering Approaches -- Constrained Optimization Approach -- Set-Valued Filtering Approach -- Probabilistic Approach -- Communications Rate Analysis -- Open Problems -- Appendices: Brief Review of Probability Theory; Linear Estimation Theory.

This book explores event-based estimation problems. It shows how several stochastic approaches are developed to maintain estimation performance when sensors perform their updates at slower rates only when needed. The self-contained presentation makes this book suitable for readers with no more than a basic knowledge of probability analysis, matrix algebra and linear systems. The introduction and literature review provide information, while the main content deals with estimation problems from four distinct angles in a stochastic setting, using numerous illustrative examples and comparisons. The text elucidates both theoretical developments and their applications, and is rounded out by a review of open problems. This book is a valuable resource for researchers and students who wish to expand their knowledge and work in the area of event-triggered systems. At the same time, engineers and practitioners in industrial process control will benefit from the event-triggering technique that reduces communication costs and improves energy efficiency in wireless automation applications.

ISBN: 9783319266060$q(electronic bk.)

Standard No.: 10.1007/978-3-319-26606-0doiSubjects--Topical Terms:

646550
Discrete-time systems.

LC Class. No.: TJ223.M53

Dewey Class. No.: 629.89

Event-based state estimation = a stochastic perspective /
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245 1 0 $a Event-based state estimation $h [electronic resource] : $b a stochastic perspective / $c by Dawei Shi, Ling Shi, Tongwen Chen.
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300 $a xiii, 208 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in systems, decision and control, $x 2198-4182 ; $v v.41
505 0 $a Introduction -- Linear Gaussian Systems and Event-Based State Estimation -- Event-Triggered Sampling -- Approximate Optimal Filtering Approaches -- Constrained Optimization Approach -- Set-Valued Filtering Approach -- Probabilistic Approach -- Communications Rate Analysis -- Open Problems -- Appendices: Brief Review of Probability Theory; Linear Estimation Theory.
520 $a This book explores event-based estimation problems. It shows how several stochastic approaches are developed to maintain estimation performance when sensors perform their updates at slower rates only when needed. The self-contained presentation makes this book suitable for readers with no more than a basic knowledge of probability analysis, matrix algebra and linear systems. The introduction and literature review provide information, while the main content deals with estimation problems from four distinct angles in a stochastic setting, using numerous illustrative examples and comparisons. The text elucidates both theoretical developments and their applications, and is rounded out by a review of open problems. This book is a valuable resource for researchers and students who wish to expand their knowledge and work in the area of event-triggered systems. At the same time, engineers and practitioners in industrial process control will benefit from the event-triggering technique that reduces communication costs and improves energy efficiency in wireless automation applications.
650 0 $a Discrete-time systems. $3 646550
650 1 4 $a Engineering. $3 586835
650 2 4 $a Control. $3 1006321
650 2 4 $a Probability Theory and Stochastic Processes. $3 891080
650 2 4 $a Power Electronics, Electrical Machines and Networks. $3 1001796
650 2 4 $a Systems Theory, Control. $3 893834
700 1 $a Shi, Ling. $3 1279356
700 1 $a Chen, Tongwen. $3 2062759
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Studies in systems, decision and control ; $v v.3. $3 2058249
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-26606-0
950 $a Engineering (Springer-11647)