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Data driven identification of networks of dynamic systems

Record Type:	Electronic resources : Monograph/item
Title/Author:	Data driven identification of networks of dynamic systemsMichel Verhaegen, Chengpu Yu, Baptiste Sinquin.
Author:	Verhaegen, Michel.
other author:	Yu, Chengpu.
Published:	Cambridge :Cambridge University Press,2022.
Description:	xviii, 267 p. :ill., digital ;25 cm.
Notes:	Title from publisher's bibliographic system (viewed on 07 Apr 2022).
Subject:	System analysisMathematics.
Online resource:	https://doi.org/10.1017/9781009026338
ISBN:	9781009026338$q(electronic bk.)

Data driven identification of networks of dynamic systems
Verhaegen, Michel.

Data driven identification of networks of dynamic systems[electronic resource] /Michel Verhaegen, Chengpu Yu, Baptiste Sinquin. - Cambridge :Cambridge University Press,2022. - xviii, 267 p. :ill., digital ;25 cm.

Title from publisher's bibliographic system (viewed on 07 Apr 2022).

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: 9781009026338$q(electronic bk.)Subjects--Topical Terms:

239362
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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245 1 0 $a Data driven identification of networks of dynamic systems $h [electronic resource] / $c Michel Verhaegen, Chengpu Yu, Baptiste Sinquin.
260 $a Cambridge : $b Cambridge University Press, $c 2022.
300 $a xviii, 267 p. : $b ill., digital ; $c 25 cm.
500 $a Title from publisher's bibliographic system (viewed on 07 Apr 2022).
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 239362
700 1 $a Yu, Chengpu. $3 917830
700 1 $a Sinquin, Baptiste. $3 930639
856 4 0 $u https://doi.org/10.1017/9781009026338