On dynamic network modeling of stationary multivariate processes

Giulio Bottegal, Alessandro Chiuso, Paul M.J. Van den Hof

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)
52 Downloads (Pure)


We study the modeling of a stationary multivariate stochastic process as the output of a dynamic network driven by white noise. When this noise corresponds to the innovation, i.e. the unpredictable part of the process, we show that the network satisfies certain stability conditions. Restricting the network model to having diagonal noise structure, we show that the innovation-driven representation is unique and internally stable. We provide a one-to-one correspondence between this representation and the spectral factor associated with the innovation model. For two-node networks, we show that a representation with diagonal noise model can be obtained from a generic one through an explicit map.

Original languageEnglish
Pages (from-to)850-855
Number of pages6
Issue number15
Publication statusPublished - 8 Oct 2018
Event18th IFAC Symposium on System Identification (SYSID 2018) - Stockholm, Sweden
Duration: 9 Jul 201811 Jul 2018


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