function [y,y1,y2,inp]=XOR(wini,alfa)
%
%	This function implements the XOR boolean fucntion using the AND and OR perceptrons derived previously
%
%	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
%

% obtain the AND percepton
load AND
w=perlearn(inp,t,[0 0 0],0.05);

% obtain the x(neg)y and the output
w1=w(41,:);
w1(3)=w1(3)+w1(1);
w1(1)=-w1(1);
y1=perrecal(inp,w1);

% obtain the xy(neg)
w2=w(41,:);
w2(3)=w2(3)+w2(2);
w2(2)=-w2(2);
y2=perrecal(inp,w2);

% obtain the OR perceptron
load OR
w=perlearn(inp,t,[0 0 0],0.05);
w3=w(41,:);

%obtain the XOR output
y=perrecal([y1' y2'], w3);