Reference : Network Reconstruction from Intrinsic Noise
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Multidisciplinary, general & others
Network Reconstruction from Intrinsic Noise
Hayden, David mailto []
Yuan, Ye mailto []
Goncalves, Jorge mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
The proceedings of the American Control Conference
American Control Conference
June 4-6, 2014
Portland, Oregon
[en] This paper considers the problem of inferring the structure and dynamics of an unknown network driven by unknown noise inputs. Equivalently we seek to identify direct causal dependencies among manifest variables only from observations of these variables. We consider linear, time-invariant systems of minimal order and with one noise source per measured state. If the transfer matrix from the inputs to manifest states is known to be minimum phase, this problem is shown to have a unique solution irrespective of the network topology. This is equivalent to there being only one spectral factor (up to a choice of signs of the inputs) of the output spectral density that satisfies these assumptions. Hence for this significant class of systems, the network reconstruction problem is well posed.

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