PCA（主成分分析法）和ICA（独立成分分析法）的MATLAB源程序

clear all; close all; class_num = 40; sample_num = 10; row = 112; line = 92; row_line = min(row, line); rowline = row * line; load orl_face2; disp('orl_eigenface now begin'); right_num = []; rr_0 = []; for count = 8 train_num = count; train_num train_total = train_num * class_num; test_num = sample_num - train_num; test_num test_total = test_num * class_num; %% -------- 1.calculate Sb Sw -------- %% orl_train = zeros(rowline, train_total); orl_m_all = zeros(rowline,1); orl_m = zeros(rowline,class_num); for i = 1:class_num for j = 1:train_num kk = (i-1)*train_num + j; orl_temp = double(orl(:,:,j,i)); for p = 1:row for q = 1:line site = (p-1)*line + q; orl_train(site, kk) = orl_temp(p,q); end end orl_m_all = orl_m_all + orl_train(:,kk); orl_m(:,i) = orl_m(:,i) + orl_train(:,kk); end orl_m(:,i) = orl_m(:,i)/train_num; end orl_m_all = orl_m_all / train_total; orl_test = zeros(rowline, test_total); for i = 1:class_num for j = 1:test_num kk = (i-1)*test_num + j; orl_temp = double(orl(:,:,j+train_num,i)); for p = 1:row for q = 1:line site = (p-1)*line + q; orl_test(site, kk) = orl_temp(p,q); end end end end Sb = zeros(rowline,class_num); for i = 1:class_num Sb(:,i) = orl_m(:,i) - orl_m_all; end % Sb0 = (Sb * Sb') / class_num; %% [rowline, rowline] St = zeros(rowline,train_total); for i = 1:class_num for j = 1:train_num kk = (i-1)*train_num + j; St(:,kk) = orl_train(:,kk) - orl_m_all; end end % St0 = (St * St') / train_total; %% [rowline, rowline] %% -------- 2.calculate transform of St -------- %% ss = (St' * St) / train_total; %% [train_total, train_total] rr = rank(ss)-class_num; rr_0 = [rr_0; rr]; [V_St, D_St] = eig(ss); dd = abs(eig(ss)); [dd_value, dd_site] = sort(dd); temp2 = rank(ss)-class_num; temp1 = train_total - temp2 + 1; yy = []; Dt = zeros(rr); jj = 0; dd_demo = zeros(temp2,1); dd_count = 1; for i = train_total:-1:temp1 yy = [yy; V_St(:,dd_site(i))']; jj = jj + 1; Dt(jj,jj) = dd_value(i)^(-0.5); dd_demo(dd_count) = dd_value(i); dd_count = dd_count + 1; end yy = yy'; zz = St * yy * Dt; ww = zz'; figure, plot(dd_demo); for ii = 1:20 ww_temp = ww(ii,:); ww_temp = ww_temp - min(ww_temp); ww_temp = ww_temp / max(ww_temp); ww_temp = floor(ww_temp * 255); orl_temp = zeros(row, line); for p = 1:row for q = 1:line site = (p-1)*line + q; orl_temp(p,q) = ww_temp(site); end end orl_temp = uint8(orl_temp); ss = sprintf('eigenorl_%d.bmp',ii); imwrite(orl_temp, ss,'bmp'); end disp('orl_eigenface is over'); %% -------- 4.calculate transform of test and train -------- %% orl_train_new = ww * orl_train; orl_test_new = ww * orl_test; error = []; for i = 1:class_num for j = 1:test_num %i,j kk = (i-1)*test_num + j; res_y = orl_test_new(:,kk); dis = []; for ii = 1:class_num for jj = 1:train_num res_x = orl_train_new(:,(ii-1)*train_num+jj); res = (res_y - res_x).^2; temp = sqrt(sum(res)); %res = abs(res_y - res_x); % temp = sum(res); dis = [dis; temp]; end end [value, site] = min(dis); site_new = floor((site-1)/train_num) + 1; if site_new ~= i error = [error; i*test_num+j]; end end end right_num = [right_num; (1.0-length(error)/(class_num*test_num))*100 ]; right_num end