Wolfy42

%%%
% Feed forward with back propagation algorithm
%
% @param    X ... all possible inputs
% @param    Y ... all expected outputs
% @param    T ... the network topology
% @param    l ... the iteration limit for the error min. func.
% @returns  W ... the optimal weight matrix
% @returns Ev ... the error dynamic vector
%%

Wolfy42

%%%
% Feed forward with back propagation algorithm
%
% @param    X ... all possible inputs
% @param    Y ... all expected outputs
% @param    T ... the network topology
% @param    l ... the iteration limit for the error min. func.
% @returns  W ... the optimal weight matrix
% @returns Ev ... the error dynamic vector
%%

Wolfy42

clear all;
	
	function y_i = ForwardProp(W, T, X)
		n = length(T);
		y_i = [X, zeros(1,n-length(X))];
		for j= 3:n
			s = 0;
			for i = 1:n
				if (T(i,j) == 1)  
					s = s + W(i,j)*y_i(i);