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文件名称:DeepLearnToolbox
介绍说明--下载内容来自于网络,使用问题请自行百度
DeepLearnToolbox是Matlab的深度学习工具箱,包含了深度信度网络DBN,卷积网络CNN,SAE(stacked auto-encoders),CAE(Convolutional auto-encoders)和NN深度学习算法的实现。-DeepLearnToolbox is a MATLAB toolbox about depth learning, contains realizations of deep belief network DBN, convolutional networks CNN, SAE (stacked auto-encoders), CAE auto-encoders and NN depth learning algorithm.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
.travis.yml
CAE/
CAE/caeapplygrads.m
CAE/caebbp.m
CAE/caebp.m
CAE/caedown.m
CAE/caeexamples.m
CAE/caenumgradcheck.m
CAE/caesdlm.m
CAE/caetrain.m
CAE/caeup.m
CAE/max3d.m
CAE/scaesetup.m
CAE/scaetrain.m
CNN/
cnn.mat
CNN/cnnapplygrads.m
CNN/cnnbp.m
CNN/cnnff.m
CNN/cnnnumgradcheck.m
CNN/cnnsetup.m
CNN/cnntest.m
CNN/cnntrain.m
CONTRIBUTING.md
create_readme.sh
data/
data/mnist_uint8.mat
DBN/
DBN/dbnsetup.m
DBN/dbntrain.m
DBN/dbnunfoldtonn.m
DBN/rbmdown.m
DBN/rbmtrain.m
DBN/rbmup.m
LICENSE
NN/
NN/nnapplygrads.m
NN/nnbp.m
NN/nnchecknumgrad.m
NN/nneval.m
NN/nnff.m
NN/nnpredict.m
NN/nnsetup.m
NN/nntest.m
NN/nntrain.m
NN/nnupdatefigures.m
README.md
README_header.md
REFS.md
SAE/
SAE/saesetup.m
SAE/saetrain.m
tests/
tests/runalltests.m
tests/test_cnn_gradients_are_numerically_correct.m
tests/test_example_CNN.m
tests/test_example_DBN.m
tests/test_example_NN.m
tests/test_example_SAE.m
tests/test_nn_gradients_are_numerically_correct.m
test_example_CNN.m
util/
util/allcomb.m
util/expand.m
util/flicker.m
util/flipall.m
util/fliplrf.m
util/flipudf.m
util/im2patches.m
util/isOctave.m
util/makeLMfilters.m
util/myOctaveVersion.m
util/normalize.m
util/patches2im.m
util/randcorr.m
util/randp.m
util/rnd.m
util/sigm.m
util/sigmrnd.m
util/softmax.m
util/tanh_opt.m
util/visualize.m
util/whiten.m
util/zscore.m
CAE/
CAE/caeapplygrads.m
CAE/caebbp.m
CAE/caebp.m
CAE/caedown.m
CAE/caeexamples.m
CAE/caenumgradcheck.m
CAE/caesdlm.m
CAE/caetrain.m
CAE/caeup.m
CAE/max3d.m
CAE/scaesetup.m
CAE/scaetrain.m
CNN/
cnn.mat
CNN/cnnapplygrads.m
CNN/cnnbp.m
CNN/cnnff.m
CNN/cnnnumgradcheck.m
CNN/cnnsetup.m
CNN/cnntest.m
CNN/cnntrain.m
CONTRIBUTING.md
create_readme.sh
data/
data/mnist_uint8.mat
DBN/
DBN/dbnsetup.m
DBN/dbntrain.m
DBN/dbnunfoldtonn.m
DBN/rbmdown.m
DBN/rbmtrain.m
DBN/rbmup.m
LICENSE
NN/
NN/nnapplygrads.m
NN/nnbp.m
NN/nnchecknumgrad.m
NN/nneval.m
NN/nnff.m
NN/nnpredict.m
NN/nnsetup.m
NN/nntest.m
NN/nntrain.m
NN/nnupdatefigures.m
README.md
README_header.md
REFS.md
SAE/
SAE/saesetup.m
SAE/saetrain.m
tests/
tests/runalltests.m
tests/test_cnn_gradients_are_numerically_correct.m
tests/test_example_CNN.m
tests/test_example_DBN.m
tests/test_example_NN.m
tests/test_example_SAE.m
tests/test_nn_gradients_are_numerically_correct.m
test_example_CNN.m
util/
util/allcomb.m
util/expand.m
util/flicker.m
util/flipall.m
util/fliplrf.m
util/flipudf.m
util/im2patches.m
util/isOctave.m
util/makeLMfilters.m
util/myOctaveVersion.m
util/normalize.m
util/patches2im.m
util/randcorr.m
util/randp.m
util/rnd.m
util/sigm.m
util/sigmrnd.m
util/softmax.m
util/tanh_opt.m
util/visualize.m
util/whiten.m
util/zscore.m
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