本程序用资源分配网(Resource_Allocation Network,简称RAN)实现了Hermit多项式在线学习问题。训练样本产生方式如下，样本数400，每个样本输入Xi在区间[-4,4]内随机产生（均匀分布），相关样本输出为F(Xi) = 1.1(1-Xi + Xi2)exp(-Xi2/2),测试样本输入在[-4，+4]内以0.04为间隔等距产生，共201个样本。训练结束后的隐节点为：11个，训练结束后的平均误差可达：0.03

-this program resources distribution network (Resource_Allocation Network , RAN) to achieve the Hermit polynomial online learning problems. Training samples have the following manner, the number of 400 samples, each sample interval in the importation of Xi [-4, 4] within randomly generated (evenly distributed) sample output related to F (Xi) = 1.1 (1-Xi Xi2) exp (-Xi2 / 2), test samples of the imported [-4, 4] to within 0.04 of equidistant spacing have a total of 201 samples. After the training of hidden nodes : 11, after the end of the training error of up to the average : 0.03