文件名称:SAE_DBN_CNNToolbox
介绍说明－－下载内容均来自于网络，请自行研究使用
多种深度学习框架，主要包括堆栈稀疏自动编码器，深信度网络，卷积神经网络等。对于灰度图像和高维图像，展现非常强大的学习性能。-A variety of deep learning fr a mework, including automatic stack sparse encoder, is convinced of the network, convolution neural networks. For grayscale images and high-dimensional image, showing a very powerful learning performance.
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下载文件列表
SAE_DBN_CNNToolbox\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
..................\.......................\.NN\cnnapplygrads.m
..................\.......................\...\cnnbp.m
..................\.......................\...\cnnff.m
..................\.......................\...\cnnnumgradcheck.m
..................\.......................\...\cnnsetup.m
..................\.......................\...\cnntest.m
..................\.......................\...\cnntrain.m
..................\.......................\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
..................\.......................\..\nnff.m
..................\.......................\..\nnsetup.m
..................\.......................\..\nntest.m
..................\.......................\..\nntrain.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
..................\.......................\....\makeLMfilters.m
..................\.......................\....\patches2im.m
..................\.......................\....\randcorr.m
..................\.......................\....\randp.m
..................\.......................\....\rnd.m
..................\.......................\....\sigm.m
..................\.......................\....\sigmrnd.m
..................\.......................\....\softmax.m
..................\.......................\....\visualize.m
..................\.......................\....\whiten.m
..................\.......................\....\xunit\+xunit\+utils\arrayToString.m
..................\.......................\....\.....\......\......\compareFloats.m
..................\.......................\....\.....\......\......\comparisonMessage.m
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