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jngiam
sparseFiltering
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runExample.m
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%% Startup (addpaths)
startup
%% Clear
clear ; close all ; clc ;
%% Load Data
% You can obtain patches.mat from
% http://cs.stanford.edu/~jngiam/data/patches.mat
fprintf('Loading Data\n');
% Loads a variable data (size 256x50000)
load patches.mat
%% Remove DC
data = bsxfun(@minus, data, mean(data));
%% Train Layer 1
L1_size = 256; % Increase this for more features
L1 = sparseFiltering(L1_size, data);
% Show Layer 1 Bases
displayData(L1);
pause;
%% Feed-forward Layer 1
data1 = feedForwardSF(L1, data);
data1 = bsxfun(@minus, data1, mean(data1));
%% Train Layer 2
L2_size = 256;
L2 = sparseFiltering(L2_size, data1);
%% Visualize Layer 2
figure;
% Number of L2 units to visualize
num_viz = 10;
% Visualize different units
offset = 1;
% Plot the units
for i = 1:num_viz
j = offset+i;
% Find the sign of the unit with the maximum absolute values
[a, b] = max(abs(L2(j, :)));
sgn = sign(L2(j, b));
% Sort and plot units in those direction
[a, b] = sort(sgn*(L2(j, :)), 'descend');
% Plot
subplot(1, num_viz, i, 'align');
displayData(L1(b(1:10), :), [] , 1);
end
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