XOR using backpropagation in matlab (I)

% XOR calculator using BackPropagation
clear all;clc;
%specify input samples (creating trainings set)
pattern = [1 1;
           0 0;
           1 0;
           0 1];
[patternRows,patternCols] = size(pattern);
%creating targets or desired answers for each set
target = [0,0,1,1];
%initializing weights with random values
w1 = [-1 1 ;    %neuron 1
      -1 2];    %neuron two
w2 = [-2,0.5];  %outputneuron
%bias
b12 = [1 -1]; % for neuron one and two respectively
b3 = -1.5;    % for neuron three (output neuron)
lr  = 0.01;     %learning rate
a12 = [2 1];    %layer 1 outputs (neuron one and twos output respectively)
a3  = 1;        %layer 2 output  (neuron 3 output)
delta = 0;
i=1;
while (i<1000 || error ~=0)
      for row_number = 1: patternRows
          for neuron = 1:2
              %calculate the output of each neuron
              a12(neuron) = logsig( pattern(row_number,:) * w1(neuron,:)' + b12(neuron) );
          end
          %calculate the output
          a3 = hardlim(w2(:)'*a12(:)+ b3 );
          %calculate the error
          error = target(row_number) - a3;
          %calculate the local gradient (sensivity)
          %which is f'(n) * e(n) for output layer
          SM = a3*error;
          %calculating delta which is learningrate * localgradient*inputs
          delta = lr * SM * a12;
          %updating the weights of last layer
          w2_new = w2 + delta;
          %updating the last layers bias
          b3_new = b3 + lr * SM;
          %calculating local gradients(sensivities) for hiddent layers
          %which is f(n)*SumOfNextLayers(localgradient*weights)
          Sm = [a12(1)*(1-a12(1)) 0;
                0  a12(2)*(1-a12(2)) ] * w2' * SM ;
          %calculating delta which is the same as before
          delta = (lr .* Sm)* pattern(row_number,:);
          %updating the weights and biases of hidden layer
          w2 = w2_new;
          b3 = b3_new;
          w1 = w1 + delta;
          b12 = b12 + (lr * Sm)';
           sss = sprintf('%d ) a3= %d # e= %d # w1=%d,%d # w2 =%d,%d \n',i,a3 ,error,w1(1),w1(2),w2(1),w2(2));
           fprintf(' %s ',sss);
      end
     i= i+1;
  end