In this paper it is shown that, with slight modifications, State Controlled CNNs (SC-CNNs) are able to approximate the behaviour of a class of complex ...

In this paper it is shown that, with slight modifications,. State Controlled CNNs (SC-CNNs) are able to approxi- mate the behaviour of a class of complex ...

In this study, a different approach to imitating the multivariable nonlinearities in complex dynamical systems by switching the states of SC-CNN is given. For ...

Apr 30, 2024 · In this study, a different approach to imitating the multivariable nonlinearities in complex dynamical systems by switching the states of SC-CNN ...

Extending the CNN Paradigm to Approximate Chaotic Systems with Multivariable Nonlinearities. 2000-01-01 Arena, P.; Fortuna, L.; Rizzo, A.; Xibilia, M. G. · An ...

Also differing from general neural networks, our CNN cells (some of them are totally unrelated to the many ideal neuron models) capture the geometric, nonlinear ...

In this paper, a discrete-time CNN using 1-dimensional chaos circuits with controllable nonlinear functions is proposed. The proposed CNN consists of p×q ...

In this study, switched State Controlled-Cellular Neural Network is used to design a chaotic system with quadratic nonlinearities. By using bipolar voltage ...

Rizzo, M.G. Xibilia, “Extending the CNN Paradigm to Approximate Chaotic Systems with Multivariable Nonlinearities”, ISCAS2000, IEEE International Symposium ...

In this paper, we propose a methodology based on chaos and dynamical systems theory for non-linear time series forecasting and investment strategy development.