文件名称:mycnn
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卷积神经网络算法 里面有一个例子 能扩展到大数据集上-Convolutional neural network algorithm
(系统自动生成,下载前可以参看下载内容)
下载文件列表
license.txt
mycnn/
mycnn/CNN/
mycnn/CNN/@cnn/
mycnn/CNN/@cnn/adapt_dw.m
mycnn/CNN/@cnn/calchx.m
mycnn/CNN/@cnn/calcje.m
mycnn/CNN/@cnn/calcMCR.m
mycnn/CNN/@cnn/check_finit_dif.m
mycnn/CNN/@cnn/cnn.m
mycnn/CNN/@cnn/cnn_size.m
mycnn/CNN/@cnn/cutrain.m
mycnn/CNN/@cnn/init.m
mycnn/CNN/@cnn/rbm.m
mycnn/CNN/@cnn/sim.m
mycnn/CNN/@cnn/subsasgn.m
mycnn/CNN/@cnn/subsref.m
mycnn/CNN/@cnn/train.m
mycnn/CNN/back_conv2.m
mycnn/CNN/back_subsample.m
mycnn/CNN/changelog.txt
mycnn/CNN/cnet.mat
mycnn/CNN/cnet_tool.m
mycnn/CNN/cnn2singlestruct.m
mycnn/CNN/cnn_gui.fig
mycnn/CNN/cnn_gui.m
mycnn/CNN/cucalcMCR.m
mycnn/CNN/cutrain_cnn.m
mycnn/CNN/fastFilter2.m
mycnn/CNN/license.txt
mycnn/CNN/preproc_data.m
mycnn/CNN/preproc_image.m
mycnn/CNN/rand_std.m
mycnn/CNN/readme.txt
mycnn/CNN/readMNIST.m
mycnn/CNN/readMNIST_image.m
mycnn/CNN/rot180.m
mycnn/CNN/singlestruct2cnn.m
mycnn/CNN/subsample.m
mycnn/CNN/tansig_mod.m
mycnn/CNN/test_dgt.m
mycnn/CNN/train_cnn.m
mycnn/CNN/ver 0.8.zip
mycnn/license.txt
ver 0.8/
ver 0.8/@cnn/
ver 0.8/@cnn/adapt_dw.m
ver 0.8/@cnn/calchx.m
ver 0.8/@cnn/calcje.m
ver 0.8/@cnn/calcMCR.m
ver 0.8/@cnn/check_finit_dif.m
ver 0.8/@cnn/cnn.m
ver 0.8/@cnn/cnn_size.m
ver 0.8/@cnn/cutrain.m
ver 0.8/@cnn/init.m
ver 0.8/@cnn/sim.m
ver 0.8/@cnn/subsasgn.m
ver 0.8/@cnn/subsref.m
ver 0.8/@cnn/train.m
ver 0.8/back_conv2.m
ver 0.8/back_subsample.m
ver 0.8/changelog.txt
ver 0.8/cnet.mat
ver 0.8/cnet_tool.m
ver 0.8/cnn2singlestruct.m
ver 0.8/cnn_gui.fig
ver 0.8/cnn_gui.m
ver 0.8/cucalcMCR.m
ver 0.8/cutrain_cnn.m
ver 0.8/fastFilter2.m
ver 0.8/license.txt
ver 0.8/preproc_data.m
ver 0.8/preproc_image.m
ver 0.8/rand_std.m
ver 0.8/readme.txt
ver 0.8/readMNIST.m
ver 0.8/readMNIST_image.m
ver 0.8/rot180.m
ver 0.8/singlestruct2cnn.m
ver 0.8/subsample.m
ver 0.8/tansig_mod.m
ver 0.8/test_dgt.m
ver 0.8/train_cnn.m
ver 0.8/ver 0.8.zip
mycnn/
mycnn/CNN/
mycnn/CNN/@cnn/
mycnn/CNN/@cnn/adapt_dw.m
mycnn/CNN/@cnn/calchx.m
mycnn/CNN/@cnn/calcje.m
mycnn/CNN/@cnn/calcMCR.m
mycnn/CNN/@cnn/check_finit_dif.m
mycnn/CNN/@cnn/cnn.m
mycnn/CNN/@cnn/cnn_size.m
mycnn/CNN/@cnn/cutrain.m
mycnn/CNN/@cnn/init.m
mycnn/CNN/@cnn/rbm.m
mycnn/CNN/@cnn/sim.m
mycnn/CNN/@cnn/subsasgn.m
mycnn/CNN/@cnn/subsref.m
mycnn/CNN/@cnn/train.m
mycnn/CNN/back_conv2.m
mycnn/CNN/back_subsample.m
mycnn/CNN/changelog.txt
mycnn/CNN/cnet.mat
mycnn/CNN/cnet_tool.m
mycnn/CNN/cnn2singlestruct.m
mycnn/CNN/cnn_gui.fig
mycnn/CNN/cnn_gui.m
mycnn/CNN/cucalcMCR.m
mycnn/CNN/cutrain_cnn.m
mycnn/CNN/fastFilter2.m
mycnn/CNN/license.txt
mycnn/CNN/preproc_data.m
mycnn/CNN/preproc_image.m
mycnn/CNN/rand_std.m
mycnn/CNN/readme.txt
mycnn/CNN/readMNIST.m
mycnn/CNN/readMNIST_image.m
mycnn/CNN/rot180.m
mycnn/CNN/singlestruct2cnn.m
mycnn/CNN/subsample.m
mycnn/CNN/tansig_mod.m
mycnn/CNN/test_dgt.m
mycnn/CNN/train_cnn.m
mycnn/CNN/ver 0.8.zip
mycnn/license.txt
ver 0.8/
ver 0.8/@cnn/
ver 0.8/@cnn/adapt_dw.m
ver 0.8/@cnn/calchx.m
ver 0.8/@cnn/calcje.m
ver 0.8/@cnn/calcMCR.m
ver 0.8/@cnn/check_finit_dif.m
ver 0.8/@cnn/cnn.m
ver 0.8/@cnn/cnn_size.m
ver 0.8/@cnn/cutrain.m
ver 0.8/@cnn/init.m
ver 0.8/@cnn/sim.m
ver 0.8/@cnn/subsasgn.m
ver 0.8/@cnn/subsref.m
ver 0.8/@cnn/train.m
ver 0.8/back_conv2.m
ver 0.8/back_subsample.m
ver 0.8/changelog.txt
ver 0.8/cnet.mat
ver 0.8/cnet_tool.m
ver 0.8/cnn2singlestruct.m
ver 0.8/cnn_gui.fig
ver 0.8/cnn_gui.m
ver 0.8/cucalcMCR.m
ver 0.8/cutrain_cnn.m
ver 0.8/fastFilter2.m
ver 0.8/license.txt
ver 0.8/preproc_data.m
ver 0.8/preproc_image.m
ver 0.8/rand_std.m
ver 0.8/readme.txt
ver 0.8/readMNIST.m
ver 0.8/readMNIST_image.m
ver 0.8/rot180.m
ver 0.8/singlestruct2cnn.m
ver 0.8/subsample.m
ver 0.8/tansig_mod.m
ver 0.8/test_dgt.m
ver 0.8/train_cnn.m
ver 0.8/ver 0.8.zip
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