Self-Emergence of Chaos in Identifying Irregular Periodic Behavior
نویسنده
چکیده
In order to exploit generalized chaotic synchronization phenomena for the solution of temporal pattern recognition problems, a chaotic dynamical system representing the class of signals that are to be recognized must be established. This system can be determined by means of identification techniques. Although the fulfillment of the chaotic condition could appear as a constraint, it is shown here that, for a very simple identification algorithm, chaos self-emerges when a model, fitting unprecise periodic signals, is identified.
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