Synchronization learning of coupled chaotic maps
Adaptation and Self-Organizing Systems
2009-10-31 v1 Statistical Mechanics
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.
Cite
@article{arxiv.nlin/0010007,
title = {Synchronization learning of coupled chaotic maps},
author = {Luis G. Moyano and Guillermo Abramson and Damian H. Zanette},
journal= {arXiv preprint arXiv:nlin/0010007},
year = {2009}
}