Synchronization learning of coupled chaotic maps View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2001-07

AUTHORS

L.G. Moyano, G. Abramson, D.H. Zanette

ABSTRACT

We study the dynamics of an ensemble of globally coupled chaotic logistic maps under the action of a learning algorithm aimed at driving the system from incoherent collective evolution to a state of spontaneous full synchronization. Numerical calculations reveal a sharp transition between regimes of unsuccessful and successful learning as the algorithm stiffness grows. In the regime of successful learning, an optimal value of the stiffness is found for which the learning time is minimal. More... »

PAGES

223-228

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s100510170130

DOI

http://dx.doi.org/10.1007/s100510170130

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1041630801


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