Research output per year
Research output per year
Research output: Contribution to journal › Article › peer-review
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 language | English |
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Pages (from-to) | 492-497 |
Number of pages | 6 |
Journal | IFAC-PapersOnLine |
Volume | 55 |
Issue number | 30 |
DOIs | |
Publication status | Published - 2022 |
Event | 25th IFAC Symposium on Mathematical Theory of Networks and Systems, MTNS 2022 - Bayreuthl, Germany Duration: 12 Sept 2022 → 16 Sept 2022 |
Research output: Contribution in Book/Catalog/Report/Conference proceeding › Conference contribution
Research output: Contribution in Book/Catalog/Report/Conference proceeding › Conference contribution