神经网络6--离散Hopfield神经网络
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% ------------------------standard number array-----------------------one=[-1 -1 -1 -1 1 1 -1 -1 -1 -1;-1 -1 -1 -1 1 1 -1 -1 -1 -1;... -1 -1 -1 -1 1 1 -1 -1 -1 -1; -1 -1 -1 -1 1 1 -1 -1 -1 -1;... -1 -1 -1 -1 1 1 -1 -1 -1 -1; -1 -1 -1 -1 1 1 -1 -1 -1 -1;... -1 -1 -1 -1 1 1 -1 -1 -1 -1; -1 -1 -1 -1 1 1 -1 -1 -1 -1;... -1 -1 -1 -1 1 1 -1 -1 -1 -1; -1 -1 -1 -1 1 1 -1 -1 -1 -1]; two=[-1 1 1 1 1 1 1 1 1 -1;-1 1 1 1 1 1 1 1 1 -1;... -1 -1 -1 -1 -1 -1 -1 1 1 -1;-1 -1 -1 -1 -1 -1 -1 1 1 -1;... -1 1 1 1 1 1 1 1 1 -1;-1 1 1 1 1 1 1 1 1 -1;... -1 1 1 -1 -1 -1 -1 -1 -1 -1;-1 1 1 -1 -1 -1 -1 -1 -1 -1;... -1 1 1 1 1 1 1 1 1 -1;-1 1 1 1 1 1 1 1 1 -1]; % ----------------------plot standard number figure----------------- ONE=imresize(one,20); subplot(3,2,1) imshow(ONE) title('stand number') TWO=imresize(two,20); subplot(3,2,2) imshow(TWO) title('stand number') % ----------------------create hopfield net-------------------------- T=[one;two]'; net=newhop(T); % ------------------------------generate noise---------------------------- % -------------------------noise array(fixed noise)--------------% no1=[-1 -1 -1 -1 1 1 -1 -1 -1 -1;-1 -1 -1 -1 1 -1 -1 -1 -1 -1;...% -1 -1 1 -1 1 1 -1 -1 -1 -1; -1 -1 -1 -1 1 1 1 -1 -1 -1;...% -1 -1 -1 -1 -1 1 -1 -1 -1 -1; -1 -1 -1 -1 1 1 -1 1 -1 -1;...% -1 -1 -1 -1 1 1 -1 -1 -1 -1; -1 1 -1 -1 1 1 -1 -1 -1 -1;...% -1 -1 -1 -1 -1 1 -1 -1 -1 -1; -1 -1 -1 -1 1 1 -1 -1 1 -1];% % no2=[-1 1 1 1 -1 1 1 -1 1 -1;-1 1 1 1 1 1 1 1 1 -1;...% -1 -1 1 -1 1 -1 -1 1 1 -1;-1 -1 -1 1 -1 1 -1 1 1 -1;...% -1 1 1 1 1 1 1 1 1 -1;-1 1 1 1 1 1 1 1 1 -1;...% -1 1 1 -1 -1 -1 -1 -1 -1 -1;-1 1 1 -1 -1 -1 -1 -1 -1 -1;...% -1 1 1 1 -1 1 1 1 1 -1;-1 1 1 -1 1 1 1 1 1 -1]; % -----------------------noise array(rand noise)----------------- rand('state',0); for i=1:100 a=rand; if a<0.1 one(i)=-one(i); two(i)=-two(i); end end no1=one; no2=two; % -------------------------plot noisy figure--------------- subplot(3,2,3) NO1=imresize(no1,20); imshow(NO1) title('noisy number') subplot(3,2,4) NO2=imresize(no2,20); imshow(NO2) title('noisy number') % --------------------------plot identify figure-------------- noise1={(no1)'};tu1=sim(net,{10,50},{},noise1);tu1{50}'subplot(3,2,5)imshow(imresize(tu1{50}',20))title('identify number')noise2={(no2)'};tu2=sim(net,{10,50},{},noise2);tu2{50}'subplot(3,2,6)imshow(imresize(tu2{50}',20))title('identify number')web -browser http://www.ilovematlab.cn/thread-30439-1-1.html
