Generation of unpredictable time series by a Neural Network

Details Generation of unpredictable time series by a Neural Network Generation of unpredictable time series by a Neural Network

2000-11-17

arxiv.org/abs/cond-mat/0011302v2

Physics

Condensed Matter

Disordered Systems and Neural Networks

11 pages, 14 figures; slightly expanded and clarified, mistakes corrected; accepted for publication in PRE

Scientific paper

10.1103/PhysRevE.63.056126

A perceptron that learns the opposite of its own output is used to generate a time series. We analyse properties of the weight vector and the generated sequence, like the cycle length and the probability distribution of generated sequences. A remarkable suppression of the autocorrelation function is explained, and connections to the Bernasconi model are discussed. If a continuous transfer function is used, the system displays chaotic and intermittent behaviour, with the product of the learning rate and amplification as a control parameter.

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