Goncalves, Jorge[University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
2009
The proceedings of the Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference
IEEE
4808 - 4813
Yes
978-1-4244-3872-3
Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference
December 16-18, 2009
Shanghai, China
Shangai
China
[en] Network reconstruction, i.e., obtaining network structure from data, is a central theme in systems biology, economics, and engineering. Previous work introduced dynamical structure functions as a tool for posing and solving the problem of network reconstruction between measured states. While recovering the network structure between hidden states is not possible since they are not measured, in many situations it is important to estimate the number of hidden states in order to understand the complexity of the network under investigation and help identify potential targets for measurements. Estimating the number of hidden states is also crucial to obtain the simplest state-space model that captures the network structure and is coherent with the measured data. This paper characterises minimal order state-space realisations that are consistent with a given dynamical structure function by exploring properties of dynamical structure functions and developing algorithms to explicitly obtain a minimal reconstruction.
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