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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Information encoding in homoclinic chaotic systems.
TL;DR: A simple method for real-time encoding of information in the interspike intervals of a homoclinic chaotic system that is experimentally tested on a CO2 laser with feedback displaying Sil'nikov chaos and synchronized with an external pulsed signal.
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Computation Emerges from Adaptive Synchronization of Networking Neurons
TL;DR: This work shows that computation can be seen as a feature emerging from the collective dynamics of an ensemble of networking neurons, which interact by means of adaptive dynamical connections, and shows how the usual Boolean logics can be fully recovered, and a universal Turing machine can be constructed.
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Adaptive recognition and filtering of noise using wavelets
TL;DR: Wavelet transform and adaptive recognition techniques are used to introduce a filtering process able to analyze, categorize, and remove additive noise from experimental time series, without previous information either on the correlation properties of noise or on the dimension of the deterministic signal.
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Recovering Network Structures Based on Evolutionary Game Dynamics via Secure Dimensional Reduction
TL;DR: This work develops a general strategy for dimensional reduction using iteratively thresholded ridge regression screener, one statistical method aiming to resolve the problem of variable selection, and employs the lasso method, a convex optimization method, to recover the network structure.
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Synchronization in networks of spatially extended systems.
TL;DR: This work analytically assesses the stability of the synchronous spatio-temporal state for a generic network by means of an extension of the master stability function approach and finds an excellent agreement between the theoretical predictions and the data obtained by Means of numerical calculations.