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The Harmonic Balance (HB) method is exploited for addressing the possible existence of period-doubling bifurcations, and complex dynamics, in a class of almost symmetric Cellular Neural Networks (CNNs). In particular, sets of CNNs parameters close to symmetry, for which period-doubling bifurcations are predicted by the HB method, are singled out. The reliability and accuracy of these predictions are shown by means of computer simulations.

DI MARCO, M., Forti, M., Tesi, A. (2003). On the prediction of period-doubling bifurcations in almost reciprocal neural networks. In PROCEEDINGS OF THE 2003 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOL III: GENERAL & NONLINEAR CIRCUITS AND SYSTEMS (pp.574-577). New York : IEEE [10.1109/ISCAS.2003.1205084].

On the prediction of period-doubling bifurcations in almost reciprocal neural networks

DI MARCO, MAURO;FORTI, MAURO;
2003-01-01

Abstract

The Harmonic Balance (HB) method is exploited for addressing the possible existence of period-doubling bifurcations, and complex dynamics, in a class of almost symmetric Cellular Neural Networks (CNNs). In particular, sets of CNNs parameters close to symmetry, for which period-doubling bifurcations are predicted by the HB method, are singled out. The reliability and accuracy of these predictions are shown by means of computer simulations.
2003
0-7803-7761-3
DI MARCO, M., Forti, M., Tesi, A. (2003). On the prediction of period-doubling bifurcations in almost reciprocal neural networks. In PROCEEDINGS OF THE 2003 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOL III: GENERAL & NONLINEAR CIRCUITS AND SYSTEMS (pp.574-577). New York : IEEE [10.1109/ISCAS.2003.1205084].
4.1 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/24682