On the prediction of period-doubling bifurcations in almost reciprocal cellular neural networks
Mauro Di Marco, Mauro Forti, Alberto Tesi · 2003
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.