类比信息传递过程中的一般测不准关系式,引进表征问题复杂性的函数复相关系数R和代表网络结构特性的隐节点数h,揭示了BP网络过拟合现象出现时的网络学习能力与推广能力之间满足的不确定关系式;通过模拟了12种不同类型复杂程度函数的过拟合数值试验,确定出关系式中的过拟合参数p的取值范围已缩小为1×10-5～5×10-4;给出应用BP网络对给定样本集的训练过程中,判断出现过拟合现象的方法.

Based on the analogue of general uncertainty relation in information transmitting processes, by the introduction of multi correlative coefficient R to manifest the complexity of the function and the hidden unit h to manifest the complexity of the network structure, a general uncertainty relation between the learning ability and the generalization ability suited to overfitting of BP neural network was revealed in the modeling of BP neural network. Tests of numerical simulation for 12 kinds of complicated function were carried out to determine the value distribution (1×10 -5 ～5×10 -4 ) of overfitting parameter in the uncertainty relation. Based on the uncertainty relation, the judgement of overfitting in the training process of gived sample sets using BP network was given.