文件名称:CNN
介绍说明－－下载内容均来自于网络，请自行研究使用
这是个卷积神经网络的实现代码，对手写体进行识别，现在正确率可以达到90 -This is a convolution neural network implementation code of conduct handwriting recognition accuracy rate is now 90
(系统自动生成,下载前可以参看下载内容)
下载文件列表
DeepLearnToolbox-master
.......................\.travis.yml
.......................\CAE
.......................\...\caeapplygrads.m
.......................\...\caebbp.m
.......................\...\caebp.m
.......................\...\caedown.m
.......................\...\caeexamples.m
.......................\...\caenumgradcheck.m
.......................\...\caesdlm.m
.......................\...\caetrain.m
.......................\...\caeup.m
.......................\...\max3d.m
.......................\...\scaesetup.m
.......................\...\scaetrain.m
.......................\CNN
.......................\...\cnnapplygrads.m
.......................\...\cnnbp.m
.......................\...\cnnff.m
.......................\...\cnnnumgradcheck.m
.......................\...\cnnsetup.m
.......................\...\cnntest.m
.......................\...\cnntrain.m
.......................\...\test_example_CNN.m
.......................\CONTRIBUTING.md
.......................\create_readme.sh
.......................\data
.......................\....\mnist_uint8.mat
.......................\DBN
.......................\...\dbnsetup.m
.......................\...\dbntrain.m
.......................\...\dbnunfoldtonn.m
.......................\...\rbmdown.m
.......................\...\rbmtrain.m
.......................\...\rbmup.m
.......................\LICENSE
.......................\NN
.......................\..\nnapplygrads.m
.......................\..\nnbp.m
.......................\..\nnchecknumgrad.m
.......................\..\nneval.m
.......................\..\nnff.m
.......................\..\nnpredict.m
.......................\..\nnsetup.m
.......................\..\nntest.m
.......................\..\nntrain.m
.......................\..\nnupdatefigures.m
.......................\README.md
.......................\README_header.md
.......................\REFS.md
.......................\SAE
.......................\...\saesetup.m
.......................\...\saetrain.m
.......................\tests
.......................\.....\runalltests.m
.......................\.....\test_cnn_gradients_are_numerically_correct.m
.......................\.....\test_example_CNN.m
.......................\.....\test_example_DBN.m
.......................\.....\test_example_NN.m
.......................\.....\test_example_SAE.m
.......................\.....\test_nn_gradients_are_numerically_correct.m
.......................\util
.......................\....\allcomb.m
.......................\....\expand.m
.......................\....\flicker.m
.......................\....\flipall.m
.......................\....\fliplrf.m
.......................\....\flipudf.m
.......................\....\im2patches.m
.......................\....\isOctave.m
.......................\....\makeLMfilters.m
.......................\....\myOctaveVersion.m
.......................\....\normalize.m
.......................\....\patches2im.m
.......................\....\randcorr.m
.......................\....\randp.m
.......................\....\rnd.m
.......................\....\sigm.m
.......................\....\sigmrnd.m
.......................\....\softmax.m
.......................\....\tanh_opt.m
.......................\....\visualize.m
.......................\....\whiten.m
.......................\....\zscore.m