Nonlinear Sciences – Chaotic Dynamics
Scientific paper
2005-07-04
J. Phys. A: Math. Gen. 39 (2006) 10723-10742
Nonlinear Sciences
Chaotic Dynamics
20 pages, 15 figures. massively revised as a full paper; issues on the choice of parameters by cross validation, tests by surr
Scientific paper
10.1088/0305-4470/39/34/009
A unified framework for analyzing generalized synchronization in coupled chaotic systems from data is proposed. The key of the proposed approach is the use of the kernel methods recently developed in the field of machine learning. Several successful applications are presented, which show the capability of the kernel-based approach for detecting generalized synchronization. It is also shown that the dynamical change of the coupling coefficient between two chaotic systems can be captured by the proposed approach.
Aihara Kazuyuki
Iba Yukito
Suetani Hiromichi
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