33 lines
754 B
Matlab
33 lines
754 B
Matlab
%% mnist data
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clear all; close all; clc;
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load mnist_uint8;
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x = cell(100, 1);
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N = 600;
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for i = 1 : 100
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x{i}{1} = reshape(train_x(((i - 1) * N + 1) : (i) * N, :), N, 28, 28) * 255;
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end
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%% ex 1
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scae = {
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struct('outputmaps', 10, 'inputkernel', [1 5 5], 'outputkernel', [1 5 5], 'scale', [1 2 2], 'sigma', 0.1, 'momentum', 0.9, 'noise', 0)
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};
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opts.rounds = 1000;
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opts.batchsize = 1;
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opts.alpha = 0.01;
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opts.ddinterval = 10;
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opts.ddhist = 0.5;
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scae = scaesetup(scae, x, opts);
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scae = scaetrain(scae, x, opts);
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cae = scae{1};
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%Visualize the average reconstruction error
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plot(cae.rL);
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%Visualize the output kernels
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ff=[];
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for i=1:numel(cae.ok{1});
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mm = cae.ok{1}{i}(1,:,:);
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ff(i,:) = mm(:);
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end;
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figure;visualize(ff')
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