文件名称:DeepLearning
- 所属分类：
- 人工智能/神经网络/遗传算法
- 资源属性：
- [Matlab] [源码]
- 上传时间：
- 2015-10-11
- 文件大小：
- 14.07mb
- 下载次数：
- 0次
- 提 供 者：
- 姜**
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
关于深度学习的详细的各种源代码，可以更好的理解深度学习的原理。-Depth study on the various sources of detailed, we can better understand the principle of the depth of learning.
(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
.......................\.NN\cnnapplygrads.m
.......................\...\cnnbp.m
.......................\...\cnnff.m
.......................\...\cnnnumgradcheck.m
.......................\...\cnnsetup.m
.......................\...\cnntest.m
.......................\...\cnntrain.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
.......................\CAE
.......................\CNN
.......................\data
.......................\DBN
.......................\NN
.......................\SAE
.......................\tests
.......................\util
DeepLearnToolbox-master