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.
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Cannas, B., Montisci, A., Pisano, F. (2013). Identification of Chaotic Systems by Neural Networks. In: Stavrinides, S., Banerjee, S., Caglar, S., Ozer, M. (eds) Chaos and Complex Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33914-1_61
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DOI: https://doi.org/10.1007/978-3-642-33914-1_61
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