• DocumentCode
    3743298
  • Title

    Identification of network components in presence of unobserved nodes

  • Author

    Donatello Materassi;Murti V. Salapaka

  • Author_Institution
    Department of Electrical Engineering and Computer Science, University of Tennessee, United States
  • fYear
    2015
  • Firstpage
    1563
  • Lastpage
    1568
  • Abstract
    The paper tackles the problem of identifying an individual transfer function in a network of linear dynamical systems in the presence of loops under the assumptions that (i) only a subset of the nodes is observable, and (ii) data are being passively recorded (i.e. it is not possible to intervene on any part of the system by actively injecting an input). Such a scenario is often encountered in the study of many naturally occurring systems and is also motivated by operating networked systems where the injection of an external signal might lead to undesired disruptions. Sufficient conditions on which signals should be observable to guarantee the identifiability of a desired link are provided. The results generalize well-established identification criteria developed in the context of graphical models.
  • Keywords
    "Transfer functions","Graphical models","Random processes","Graph theory","Skeleton","Artificial neural networks","Semantics"
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2015 IEEE 54th Annual Conference on
  • Type

    conf

  • DOI
    10.1109/CDC.2015.7402433
  • Filename
    7402433