The chaos generation neural network model and synaptic weights database have been built to generate many chaotic sequences trained by the evolutionary programming ( ep ) algorithm with various discrete chaotic time series 该模型利用神经网络权值调整的灵活性，能够在同一网络结构中产生的多种混沌序列。
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At the same time the author discusses how to speed the training and avoid the process trapping into local minimal as well as expounds the virtues and the shortcomings of this arithmetic . in the end the training is done with two modes to get the synaptic weights 论文对bp算法的优点和缺陷作了阐述，并对如何加快训练和避免陷入局部最小做了一些讨论。最后使用两种蛋品模型进行学习及利用所得权值实现分类。
