Reference : Robust dynamical network structure reconstruction |
Scientific journals : Article | |||
Engineering, computing & technology : Multidisciplinary, general & others | |||
http://hdl.handle.net/10993/20310 | |||
Robust dynamical network structure reconstruction | |
English | |
Yuan, Ye ![]() | |
Stan, Guy-Bart ![]() | |
Warnick, Stan ![]() | |
Goncalves, Jorge ![]() | |
Jun-2011 | |
Automatica | |
Pergamon Press - An Imprint of Elsevier Science | |
47 | |
6 | |
Yes (verified by ORBilu) | |
0005-1098 | |
Oxford | |
United Kingdom | |
[en] Robust network reconstruction ; Noise and unmodelled dynamics ; Systems biology | |
[en] This paper addresses the problem of network reconstruction from data. Previous work identified
necessary and sufficient conditions for network reconstruction of LTI systems, assuming perfect measurements (no noise) and perfect system identification. This paper assumes that the conditions for network reconstruction have been met but here we additionally take into account noise and unmodelled dynamics (including nonlinearities). In order to identify the network structure that generated the data, we compute the smallest distances between the measured data and the data that would have been generated by particular network structures. We conclude with biologically inspired network reconstruction examples which include noise and nonlinearities. | |
http://hdl.handle.net/10993/20310 |
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