Palestras e Seminários
25/04/2018
14:00
auditório Luiz Antonio Favaro (sala 4-111)
Palestrante: Tiago Pereira da Silva

We consider the inverse problem of obtaining the model of a complex networked system from data to predict the critical transitions the system undergoes. The our results can be applied to systems with weak coupling including networks with heterogeneous structures such as scale-free graphs and hierarchical networks. Using our approach we can create an effective network to make predictions about the critical transitions in the system. As an illustration, we show how to obtain the critical transitions and sensorial areas of the cerebral cortex of the cat only from a single multivariate time-series.

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