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.
Identification of chaotic systems by neural networks
CANNAS, BARBARA;MONTISCI, AUGUSTO;PISANO, FABIO
2013-01-01
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.
File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
