In this paper the definition of chaos is described at first, and then experimental rules are presented to declare whether a time series is chaotic. These rules are that time series should have an attractor with a finite dimensions, have a positive Lyapunove exponent at least, and be locally predicted. Neural network's abiltity to restruct phase space of chaotic time series and in the condition of populared by noise is also discussed. Based on the neural network's powerful ability of studying and nonlinear p...
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