//// Letter recognition with threshold perceptron
 clear; clf;
 nIn=12*13; nOut=26; // number of input and output channels
 wOut=rand(nOut,nIn)-0.5; //random initial weight matrix

 // training vectors
  pattern1=read('pattern1',26*12,13);
  rIn=matrix(pattern1', nIn, 26); 
  rDes=diag(ones(1,26)); // matrix of desired outputs

 // Updating and training network
 for training_step=1:20;
     // test all pattern
       rOut=(wOut*rIn)>0; // threshold activation function
       dist=sum(sum(abs(rDes-rOut)))/26;
       errorNet(training_step)=dist;
     // training with delta rule
       wOut=wOut+0.1*(rDes-rOut)*rIn';
 end

 plot(0:19,errorNet)
 xlabel('Training step')
 ylabel('Average number of wrong bits')