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Robust chaos generation by a perceptron

A. Priel·I. Kanter
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Abstract

The properties of time series generated by a perceptron with monotonic and non-monotonic transfer function, where the next input vector is determined from past output values, are examined. Analysis of the parameter space reveals the following main finding: a perceptron with a monotonic function can produce fragile chaos only whereas a non-monotonic function can generate robust chaos as well. For non-monotonic functions, the dimension of the attractor can be controlled monotonically by tuning a natural parameter in the model.

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A. Priel, I. Kanter. 2000-07-05. Robust chaos generation by a perceptron. https://doi.org/10.1209/epl%2Fi2000-00521-4

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