Distributed Analytical Graph Identification

Chepuri, Sundeep Prabhakar; Coutino, M.; Marques, Antonio G.; Leus, G.J.T.

doi:10.1109/ICASSP.2018.8461484

Distributed Analytical Graph Identification

Conference paper (2018)

Authors

Sundeep Prabhakar Chepuri Signal Processing Systems -

M. Coutino Signal Processing Systems -

Antonio G. Marques King Juan Carlos University

G.J.T. Leus Signal Processing Systems -

Research Group

Signal Processing Systems () (TU Delft)

DOI: https://doi.org/10.1109/ICASSP.2018.8461484

System identification Graph signal processing Topology identification Spectrum analysis Distributed graph-spectral decomposition

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Published Date

2018

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Microelectronics

Research Group

Signal Processing Systems

Abstract

An analytical algebraic approach for distributed network identification is presented in this paper. The information propagation in the network is modeled using a state-space representation. Using the observations recorded at a single node and a known excitation signal, we present algorithms to compute the eigenfrequencies and eigenmodes of the graph in a distributed manner. The eigenfrequencies of the graph may be computed using a generalized eigenvalue algorithm, while the eigenmodes can be computed using an eigenvalue decomposition. The developed theory is demonstrated using numerical experiments.

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