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
Link To Document :
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