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Data-driven identification of networks of dynamic systems /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Data-driven identification of networks of dynamic systems // Michel Verhaegen, Chengpu Yu, Baptiste Sinquin.
Author:	Verhaegen, M.
other author:	Yu, Chengpu,
Published:	Cambridge :Cambridge University Press, : 2022.,
Description:	xviii, 267 p. :ill. ; : 26 cm.;
Subject:	System analysis - Mathematics. -
ISBN:	9781316515709 (hbk.) :

Data-driven identification of networks of dynamic systems /
Verhaegen, M.

Data-driven identification of networks of dynamic systems /Michel Verhaegen, Chengpu Yu, Baptiste Sinquin. - Cambridge :Cambridge University Press,2022. - xviii, 267 p. :ill. ;26 cm.

Includes bibliographical references and index.

This comprehensive text provides an excellent introduction to the state of the art in the identification of network-connected systems. It covers models and methods in detail, includes a case study showing how many of these methods are applied in adaptive optics and addresses open research questions. Specific models covered include generic modelling for MIMO LTI systems, signal flow models of dynamic networks and models of networks of local LTI systems. A variety of different identification methods are discussed, including identification of signal flow dynamics networks, subspace-like identification of multi-dimensional systems and subspace identification of local systems in an NDS. Researchers working in system identification and/or networked systems will appreciate the comprehensive overview provided, and the emphasis on algorithm design will interest those wishing to test the theory on real-life applications. This is the ideal text for researchers and graduate students interested in system identification for networked systems.

ISBN: 9781316515709 (hbk.) :NT4094Subjects--Topical Terms:

997150
System analysis
--Mathematics.

LC Class. No.: QA402 / .V468 2022

Dewey Class. No.: 003/.85

Data-driven identification of networks of dynamic systems /
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020 $a 9781316515709 (hbk.) : $c NT4094
020 $z 9781009026338 (ebk.)
040 $a UkCbUP $b eng $e aacr2 $c UkCbUP
050 0 0 $a QA402 $b .V468 2022
082 0 0 $a 003/.85 $2 23/eng/20220118
100 1 $a Verhaegen, M. $q (Michel) $3 1376471
245 1 0 $a Data-driven identification of networks of dynamic systems / $c Michel Verhaegen, Chengpu Yu, Baptiste Sinquin.
260 # $a Cambridge : $b Cambridge University Press, $c 2022.
300 $a xviii, 267 p. : $b ill. ; $c 26 cm.
504 $a Includes bibliographical references and index.
520 # $a This comprehensive text provides an excellent introduction to the state of the art in the identification of network-connected systems. It covers models and methods in detail, includes a case study showing how many of these methods are applied in adaptive optics and addresses open research questions. Specific models covered include generic modelling for MIMO LTI systems, signal flow models of dynamic networks and models of networks of local LTI systems. A variety of different identification methods are discussed, including identification of signal flow dynamics networks, subspace-like identification of multi-dimensional systems and subspace identification of local systems in an NDS. Researchers working in system identification and/or networked systems will appreciate the comprehensive overview provided, and the emphasis on algorithm design will interest those wishing to test the theory on real-life applications. This is the ideal text for researchers and graduate students interested in system identification for networked systems.
650 # 0 $a System analysis $x Mathematics. $3 997150
700 1 # $a Yu, Chengpu, $d 1984- $3 1384067
700 1 # $a Sinquin, Baptiste, $d 1991- $3 1384068