Robust chaos generation by a perceptron
无序系统与神经网络
2009-10-31 v1 混沌动力学
摘要
The properties of time series generated by a perceptron with monotonic and non-monotonic transfer function, where the next input vector is determined from past output values, are examined. Analysis of the parameter space reveals the following main finding: a perceptron with a monotonic function can produce fragile chaos only whereas a non-monotonic function can generate robust chaos as well. For non-monotonic functions, the dimension of the attractor can be controlled monotonically by tuning a natural parameter in the model.
关键词
引用
@article{arxiv.cond-mat/0007074,
title = {Robust chaos generation by a perceptron},
author = {A. Priel and I. Kanter},
journal= {arXiv preprint arXiv:cond-mat/0007074},
year = {2009}
}
备注
7 pages, 5 figures (reduced quality), accepted for publication in EuroPhysics Letters