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Detecting Generalized Synchronization Between Chaotic Signals: A Kernel-based Approach
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.Comment: 20 pages, 15 figures. massively revised as a full paper; issues on
the choice of parameters by cross validation, tests by surrogated data, etc.
are added as well as additional examples and figure
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