Self-emergence of chaos in the identification of irregular periodic behavior

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Abstract
Various forms of chaotic synchronization have been proposed as ways of realizing associative memories and/or pattern recognizers. To exploit this kind of synchronization phenomena in temporal pattern recognition, 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. The fulfillment of the chaotic condition could be imposed as a constraint. However, it is shown here that, even for a very simple identification algorithm, chaos emerges by itself, allowing us to model the diversity of nearly periodic signals.