PREDICTING LOW-DIMENSIONAL CHAOTIC TIME SERIES USING VOLTERRA ADAPTIVE FILERS

Volterra adaptive filter is used to predict low\|dimensional chaotic time series based on the state space reconstruction of delay\|coordinate embedding of dynamic system.It is shown,through experiments of predicting eight kinds of low\|dimensional chaotic series using second\|order Volterra adaptive filters,that Volterra adaptive filters can accurately predict these chaotic series when the length N l of the Volterra filter is long enough,and the choice of N l is related to D 2 and smoothness of chaotic map.