deeplearing.zip

deeplearing.zip

function cae = caeapplygrads（cae）
    cae.sv = 0;
    for j = 1 : numel（cae.a）
        for i = 1 : numel（cae.i）
%             cae.vik{i}{j} = cae.momentum * cae.vik{i}{j} + cae.alpha ./ （cae.sigma + cae.ddik{i}{j}） .* cae.dik{i}{j};
%             cae.vok{i}{j} = cae.momentum * cae.vok{i}{j} + cae.alpha ./ （cae.sigma + cae.ddok{i}{j}） .* cae.dok{i}{j};
            cae.vik{i}{j} = cae.alpha * cae.dik{i}{j};
            cae.vok{i}{j} = cae.alpha * cae.dok{i}{j};
            cae.sv = cae.sv + sum（cae.vik{i}{j}（:） .^ 2）;
            cae.sv = cae.sv + sum（cae.vok{i}{j}（:） .^ 2）;

            cae.ik{i}{j} = cae.ik{i}{j} - cae.vik{i}{j};
            cae.ok{i}{j} = cae.ok{i}{j} - cae.vok{i}{j};
        end
%         cae.vb{j} = cae.momentum * cae.vb{j} + cae.alpha / （cae.sigma + cae.ddb{j}） * cae.db{j};
        cae.vb{j} = cae.alpha * cae.db{j};
        cae.sv = cae.sv + sum（cae.vb{j} .^ 2）;

        cae.b{j} = cae.b{j} - cae.vb{j};
    end

    for i = 1 : numel（cae.o）
%         cae.vc{i} = cae.momentum * cae.vc{i} + cae.alpha / （cae.sigma + cae.ddc{i}） * cae.dc{i};
        cae.vc{i} = cae.alpha * cae.dc{i};
        cae.sv = cae.sv + sum（cae.vc{i} .^ 2）;

        cae.c{i} = cae.c{i} - cae.vc{i};
    end
end

 属性            大小     日期    时间   名称
----------- ---------  ---------- -----  ----
     目录           0  2017-04-09 19:32  deeplearing\
     目录           0  2017-04-09 19:32  deeplearing\DeepLearnToolbox\
     文件         249  2017-04-09 19:29  deeplearing\DeepLearnToolbox\.travis.yml
     目录           0  2017-04-09 19:32  deeplearing\DeepLearnToolbox\CAE\
     文件        1219  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CAE\caeapplygrads.m
     文件         917  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CAE\caebbp.m
     文件        1011  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CAE\caebp.m
     文件         259  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CAE\caedown.m
     文件         754  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CAE\caeexamples.m
     文件        3618  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CAE\caenumgradcheck.m
     文件         845  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CAE\caesdlm.m
     文件        1148  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CAE\caetrain.m
     文件         489  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CAE\caeup.m
     文件         173  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CAE\max3d.m
     文件        1937  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CAE\scaesetup.m
     文件         270  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CAE\scaetrain.m
     目录           0  2017-06-26 20:29  deeplearing\DeepLearnToolbox\CNN\
     文件         575  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CNN\cnnapplygrads.m
     文件        2141  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CNN\cnnbp.m
     文件        1774  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CNN\cnnff.m
     文件        3430  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CNN\cnnnumgradcheck.m
     文件        2021  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CNN\cnnsetup.m
     文件         193  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CNN\cnntest.m
     文件         845  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CNN\cnntrain.m
     文件    14735220  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CNN\mnist_uint8.mat
     文件         165  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CNN\runalltests.m
     文件         552  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CNN\test_cnn_gradients_are_numerically_correct.m
     文件         982  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CNN\test_example_CNN.m
     文件         749  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CNN\test_nn_gradients_are_numerically_correct.m
     文件         544  2017-04-09 19:29  deeplearing\DeepLearnToolbox\CONTRIBUTING.md
     文件         744  2017-04-09 19:29  deeplearing\DeepLearnToolbox\create_readme.sh
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