Spectral network identification with generalized diffusive coupling

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

8 Downloads (Pure)

Abstract

Spectral network identification aims at inferring the eigenvalues of the Laplacian matrix of a network from measurement data.
This allows to capture global information on the network structure from local measurements at a few number of nodes.
In this paper, we consider the spectral network identification problem in the generalized setting of a vector-valued diffusive coupling.
The feasibility of this problem is investigated and theoretical results on the properties of the associated generalized eigenvalue problem are obtained.
Finally, we propose a numerical method to solve the generalized network identification problem, which relies on dynamic mode decomposition and leverages the above theoretical results.
Original languageEnglish
Title of host publication41st Benelux Meeting on Systems and Control
Subtitle of host publicationBook of Abstract
EditorsAlain Vande Wouwer, Michel Kinnaert, Emmanuele Garone, Laurent Dewasme, Guilherme A. Pimentel
PublisherPresses universitaires de Mons
Number of pages1
Publication statusPublished - 5 Jul 2022
Event41th Benelux Meeting on Systems and Control - Université Libre de Bruxelles, Bruxelles, Belgium
Duration: 5 Jul 20227 Jul 2022
https://www.beneluxmeeting.eu/2022/

Conference

Conference41th Benelux Meeting on Systems and Control
Abbreviated titleBMSC 2022
Country/TerritoryBelgium
CityBruxelles
Period5/07/227/07/22
Internet address

Fingerprint

Dive into the research topics of 'Spectral network identification with generalized diffusive coupling'. Together they form a unique fingerprint.

Cite this