Pattern recognition by means of convolutional neural networks

ver 0.83\@cnn\adapt_dw.m
ver 0.83\@cnn\calchx.m
ver 0.83\@cnn\calcje.m
ver 0.83\@cnn\calcMCR.m
ver 0.83\@cnn\check_finit_dif.m
ver 0.83\@cnn\cnn.m
ver 0.83\@cnn\cnn_size.m
ver 0.83\@cnn\cutrain.m
ver 0.83\@cnn\init.m
ver 0.83\@cnn\sim.m
ver 0.83\@cnn\subsasgn.m
ver 0.83\@cnn\subsref.m
ver 0.83\@cnn\train.m
ver 0.83\back_conv2.m
ver 0.83\back_subsample.m
ver 0.83\changelog.txt~
ver 0.83\cnet.mat
ver 0.83\cnet_tool.m
ver 0.83\cnn2singlestruct.m
ver 0.83\cnn_gui.fig
ver 0.83\cnn_gui.m
ver 0.83\cucalcMCR.m
ver 0.83\cutrain_cnn.m
ver 0.83\fastFilter2.m
ver 0.83\license.txt~
ver 0.83\mse.m
ver 0.83\preproc_data.m
ver 0.83\preproc_image.m
ver 0.83\purelin.m
ver 0.83\rand_std.m
ver 0.83\readme.txt
ver 0.83\readMNIST.m
ver 0.83\readMNIST_image.m
ver 0.83\rot180.m
ver 0.83\singlestruct2cnn.m
ver 0.83\subsample.m
ver 0.83\tansig_mod.m
ver 0.83\test_dgt.m
ver 0.83\train_cnn.m
ver 0.83\changelog.txt
license.txt

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