从给定的很多张自然图片中截取出大小为8*8的小patches图片共10000张，现在需要用sparse autoencoder的方法训练出一个隐含层网络所学习到的特征。该网络共有3层，输入层是64个节点，隐含层是25个节点，输出层当然也是64个节点了。这里只是上传了训练的部分代码，后续继续(A total of 10000 small patches pictures with size 8*8 are extracted from a lot of natural pictures. Now we need to use sparse autoencoder to train a hidden layer network to learn the characteristics. The network has 3 layers, the input layer is 64 nodes, the hidden layer is 25 nodes, and the output layer is, of course, 64 nodes. Here's only part of the training code, followed by)相关搜索： 自编码
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