| Reference : Network structure preserving model reduction with weak a priori structural information |
| Scientific congresses, symposiums and conference proceedings : Paper published in a book | |||
| Engineering, computing & technology : Multidisciplinary, general & others | |||
| http://hdl.handle.net/10993/20360 | |||
| Network structure preserving model reduction with weak a priori structural information | |
| English | |
Yeung, E.  [> >] | |
| Goncalves, Jorge [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >] | |
| Sandberg, H. [> >] | |
| Warnick, S. [> >] | |
| 2009 | |
| The proceedings of the Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference | |
| IEEE | |
| 3256-3263 | |
| Yes | |
| 978-1-4244-3872-3 | |
| Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference | |
| December 16-18, 2009 | |
| Shangai | |
| China | |
| [en] This paper extends a state projection method for structure preserving model reduction to situations where only a weaker notion of system structure is available. This weaker notion of structure, identifying the causal relationship between manifest variables of the system, is especially relevant is settings such as systems biology, where a clear partition of state variables into distinct subsystems may be unknown, or not even exist. The resulting technique, like similar approaches, does not provide theoretical performance guarantees, so an extensive computational study is conducted, and it is observed to work fairly well in practice. Moreover, conditions characterizing structurally minimal realizations and sufficient conditions characterizing edge loss resulting from the reduction process, are presented. | |
| http://hdl.handle.net/10993/20360 | |
| 10.1109/CDC.2009.5400375 |
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