Identification of chaotic systems by neural networks

CANNAS, BARBARA;MONTISCI, AUGUSTO;PISANO, FABIO

2013-01-01

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Abstract

In this paper a traditional Multi Layer Perceptron with a tapped delay line as input is trained to identify the parameters of the Chua’s circuit when fed with a sequence of values of a scalar state variable. The analysis of the a priori identifiability of the system, performed resorting to differential algebra, allows one to choose a suitable observable and the minimum number of taps. The results confirm the appropriateness of the proposed approach.