function [w,y]=perlearn(inp,tar,wini,alfa)
%
%	This function implements the perception learning rule
%
%	Input arguments:
%
%	inp - input matrix (m patterns, n inputs)
%	tar - target vector
%	wini - initial value of the weight vector (bias is the (n+1)th weight
%	alfa - learning rate
%
%	Output arguments:
%
%	w - weight vector history
%	y - output vector
%
[m,n]=size(inp);

w=wini;
for i=1:m
   y(i)=w(i,:)*[inp(i,:) 1]';
   if y(i)>=0
      y(i)=1;
   else
      y(i)=0;
   end   
   w(i+1,:)=w(i,:)+alfa*(tar(i)-y(i))*[inp(i,:) 1];
end