S
Stefano Boccaletti
Researcher at Moscow Institute of Physics and Technology
Publications - 361
Citations - 29686
Stefano Boccaletti is an academic researcher from Moscow Institute of Physics and Technology. The author has contributed to research in topics: Complex network & Synchronization (computer science). The author has an hindex of 60, co-authored 348 publications receiving 25776 citations. Previous affiliations of Stefano Boccaletti include King Juan Carlos University & Istituto Nazionale di Fisica Nucleare.
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Journal ArticleDOI
Controlling transient dynamics to communicate with homoclinic chaos
TL;DR: It is shown that the controlled signal that encodes the source contains more information than the source, and this property is advantageously used to correct possible errors in the transmission, or to increase the ratio of information per transmitted spike.
Journal ArticleDOI
Topological stability criteria for networking dynamical systems with Hermitian Jacobian
TL;DR: In this article, the authors present an analytical approach for deriving necessary conditions that an interaction network has to obey in order to support a given type of macroscopic behaviour. But the approach is based on a graphical notation, which allows rewriting Jacobi's signature criterion in an interpretable form and which can be applied to many systems of symmetrically coupled units.
Journal ArticleDOI
Explosive synchronization dependence on initial conditions: The minimal Kuramoto model
Atiyeh Bayani,Sajad Jafari,Hamed Azarnoush,Fahimeh Nazarimehr,Stefano Boccaletti,Matjaž Perc +5 more
TL;DR: In this article , the authors considered the minimal network of Kuramoto oscillator that may display explosive synchronization, and they showed that the nature of the transition changes from continuous to discontinuous as phases are differently initialized.
Proceedings ArticleDOI
Modules identification by a Dynamical Clustering algorithm based on chaotic Rössler oscillators
TL;DR: In this article, a modified version of dynamical clustering based on chaotic Rossler oscillators is presented, which is tested on real and computer generated networks with a well known modular structure.
Proceedings ArticleDOI
Modules identification by a Dynamical Clustering algorithm based on chaotic R\"ossler oscillators
TL;DR: A modified version of this dynamical clustering algorithm for the identification of modules in complex networks based on a system of chaotic Rossler oscillators is presented and its sensitivity is tested on real and computer generated networks with well known modular structure.