Reconstructed dynamics and chaotic signal modeling
A nonlinear AR model is derived from the reconstructed dynamics of a signal. The underlying system is assumed to be nonlinear, autonomous, and deterministic. In this formulation, the output error scheme is shown to be more suitable than the equation error scheme in training a network as a nonlinear AR model of the signal. A method to incorporate the information of the dynamical invariants in signal modeling is proposed.<<ETX>>