Reduced complexity models in the identification of dynamical networks: Links with sparsification problems

Abstract

In many applicative scenarios it is important to derive information about the topology and the internal connections of more dynamical systems interacting together. Examples can be found in fields as diverse as economics, neuroscience and biochemistry. The paper deals with the problem of deriving a descriptive model of a network, collecting the node outputs… (More)
DOI: 10.1109/CDC.2009.5400379
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@article{Materassi2009ReducedCM, title={Reduced complexity models in the identification of dynamical networks: Links with sparsification problems}, author={Donatello Materassi and Giacomo Innocenti and Laura Giarr{\'e}}, journal={Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference}, year={2009}, pages={4796-4801} }