PARALLEL IMPLEMENTATION OF A GENERAL-PURPOSE FUNCTIONAL PREDICTOR FOR CHAOTIC TIME-SERIES

A general purpose predictor for complex and chaotic deterministic dynamics is proposed. This consists of a functional reconstructor whose base functions are the polynomials orthonormal to the invariant measure associated to the time series, and of a preprocessing unit providing the necessary reconstruction parameters (the optimal time delay and the reconstructed phase space dimension). The proposed criterion for the estimation of these parameters is independent of the reconstruction method and is grounded on the results of chaotic signal analysis. A parallel implementation of reconstruction is discussed on the basis of a VME architecture. The applicability of the proposed method is tested by means of numerical simulations on low-dimensional time series.