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DeepLearnToolbox-master

于 2020-10-12 发布 文件大小:14406KB
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代码说明：

  基于matlab的深度学习算法，可用于深度学习入门(Based on the depth of learning matlab algorithm can be used for deep learning, such as doors)

文件列表：

DeepLearnToolbox-master
.......................\.travis.yml,249,2015-12-01
.......................\CAE
.......................\...\caeapplygrads.m,1219,2015-12-01
.......................\...\caebbp.m,917,2015-12-01
.......................\...\caebp.m,1011,2015-12-01
.......................\...\caedown.m,259,2015-12-01
.......................\...\caeexamples.m,754,2015-12-01
.......................\...\caenumgradcheck.m,3618,2015-12-01
.......................\...\caesdlm.m,845,2015-12-01
.......................\...\caetrain.m,1148,2015-12-01
.......................\...\caeup.m,489,2015-12-01
.......................\...\max3d.m,173,2015-12-01
.......................\...\scaesetup.m,1937,2015-12-01
.......................\...\scaetrain.m,270,2015-12-01
.......................\CNN
.......................\...\cnnapplygrads.m,575,2015-12-01
.......................\...\cnnbp.m,2141,2015-12-01
.......................\...\cnnff.m,1774,2015-12-01
.......................\...\cnnnumgradcheck.m,3430,2015-12-01
.......................\...\cnnsetup.m,2020,2015-12-01
.......................\...\cnntest.m,193,2015-12-01
.......................\...\cnntrain.m,845,2015-12-01
.......................\CONTRIBUTING.md,544,2015-12-01
.......................\create_readme.sh,744,2015-12-01
.......................\data
.......................\....\mnist_uint8.mat,14735220,2015-12-01
.......................\DBN
.......................\...\dbnsetup.m,557,2015-12-01
.......................\...\dbntrain.m,232,2015-12-01
.......................\...\dbnunfoldtonn.m,425,2015-12-01
.......................\...\rbmdown.m,90,2015-12-01
.......................\...\rbmtrain.m,1401,2015-12-01
.......................\...\rbmup.m,89,2015-12-01
.......................\htm" target=_blank>LICENSE,1313,2015-12-01
.......................\NN
.......................\..\nnapplygrads.m,628,2015-12-01
.......................\..\nnbp.m,1638,2015-12-01
.......................\..\nnchecknumgrad.m,704,2015-12-01
.......................\..\nneval.m,811,2015-12-01
.......................\..\nnff.m,1849,2015-12-01
.......................\..\nnpredict.m,192,2015-12-01
.......................\..\nnsetup.m,1844,2015-12-01
.......................\..\nntest.m,184,2015-12-01
.......................\..\nntrain.m,2414,2015-12-01
.......................\..\nnupdatefigures.m,1858,2015-12-01
.......................\README.md,8861,2015-12-01
.......................\README_header.md,2244,2015-12-01
.......................\REFS.md,950,2015-12-01
.......................\SAE
.......................\...\saesetup.m,132,2015-12-01
.......................\...\saetrain.m,308,2015-12-01
.......................\tests
.......................\.....\runalltests.m,165,2015-12-01
.......................\.....\test_cnn_gradients_are_numerically_correct.m,552,2015-12-01
.......................\.....\test_example_CNN.m,981,2015-12-01
.......................\.....\test_example_DBN.m,1031,2015-12-01
.......................\.....\test_example_NN.m,3247,2015-12-01
.......................\.....\test_example_SAE.m,934,2015-12-01
.......................\.....\test_nn_gradients_are_numerically_correct.m,749,2015-12-01
.......................\util
.......................\....\allcomb.m,2618,2015-12-01
.......................\....\expand.m,1958,2015-12-01
.......................\....\flicker.m,208,2015-12-01
.......................\....\flipall.m,80,2015-12-01
.......................\....\fliplrf.m,543,2015-12-01
.......................\....\flipudf.m,576,2015-12-01
.......................\....\im2patches.m,313,2015-12-01
.......................\....\isOctave.m,108,2015-12-01
.......................\....\makeLMfilters.m,1895,2015-12-01
.......................\....\myOctaveVersion.m,169,2015-12-01
.......................\....\normalize.m,97,2015-12-01
.......................\....\patches2im.m,242,2015-12-01
.......................\....\randcorr.m,283,2015-12-01
.......................\....\randp.m,2083,2015-12-01
.......................\....\rnd.m,49,2015-12-01
.......................\....\sigm.m,48,2015-12-01
.......................\....\sigmrnd.m,126,2015-12-01
.......................\....\softmax.m,256,2015-12-01
.......................\....\tanh_opt.m,54,2015-12-01
.......................\....\visualize.m,1072,2015-12-01
.......................\....\whiten.m,183,2015-12-01
.......................\....\zscore.m,137,2015-12-01

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    积分：1
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    2010-08-21 21:11:40下载
    积分：1
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    2008-07-26 14:16:59下载
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    Artificial Neural Network (ANN) and Fuzzy
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    matlab下的数字图象处理例程,其中有关图片文件只要随便找个图片就可以了(matlab under the digital image processing routines, including the relevant picture file as long as you can not find a picture of the)
    2007-11-06 21:38:49下载
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    利用keyset进行遍历，它的优点在于可以根据你所想要的key值得到你想要的 values，更具灵活性！！ (Use keyset traversal of its advantages is that worth to the values ​ ​ you want the key you want more flexibility! !)
    2012-06-07 11:19:48下载
    积分：1
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