Abstractions of linear dynamic networks for input selection in local module identification

@article{Weerts2020AbstractionsOL,
  title={Abstractions of linear dynamic networks for input selection in local module identification},
  author={Harm H. M. Weerts and Jonas Linder and Martin Enqvist and Paul M. J. Van den Hof},
  journal={Autom.},
  year={2020},
  volume={117},
  pages={108975}
}
  • Harm H. M. Weerts, Jonas Linder, +1 author Paul M. J. Van den Hof
  • Published 2020
  • Mathematics, Computer Science
  • Autom.
  • In abstractions of linear dynamic networks, selected node signals are removed from the network, while keeping the remaining node signals invariant. The topology and link dynamics, or modules, of an abstracted network will generally be changed compared to the original network. Abstractions of dynamic networks can be used to select an appropriate set of node signals that are to be measured, on the basis of which a particular local module can be estimated. A method is introduced for network… CONTINUE READING

    Figures and Topics from this paper.

    Citations

    Publications citing this paper.

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 39 REFERENCES

    Identification of network components in presence of unobserved nodes

    VIEW 2 EXCERPTS

    Identifiability of dynamical networks: Which nodes need be measured?

    VIEW 7 EXCERPTS
    HIGHLY INFLUENTIAL

    Identifiability of Dynamical Networks With Partial Node Measurements

    VIEW 6 EXCERPTS
    HIGHLY INFLUENTIAL