deeplearning toolbox matlab,Deep-Learning-Toolbox 深度学习matlab工具箱,包括 belief nets,stacked autoencoder,c...

文件名称: Deep-Learning-Toolbox下载  收藏√  [

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开发工具: matlab

文件大小: 14396 KB

上传时间: 2014-10-20

下载次数: 227

提 供 者: 冯敬伟

详细说明：深度学习matlab工具箱,包括深度deep belief nets,stacked autoencoder,convolutional neural nets等网络。-Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.

文件列表(点击判断是否您需要的文件，如果是垃圾请在下面评价投诉):

DeepLearnToolbox-master

.......................\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

.......................\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

.......................\create_readme.sh

.......................\data

.......................\....\mnist_uint8.mat

.......................\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

.......................\....\makeLMfilters.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

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