[ADD] cost_function an train algorithm

Author: Jeffresh

cost_function.m

@@ -0,0 +1,8 @@
+function [c,d_c] = cost_function(so,sd)
+%COST_FUNCTION Summary of this function goes here
+%   Detailed explanation goes 
+
+c =mean((so-sd).^2);
+d_c = so-sd;
+end
+

train.m

@@ -0,0 +1,23 @@
+
+function [neural_net,y_predicted, learning_rate]= train(neural_net,X,Y,...
+cost_function,learning_rate)
+
+%TRAIN Summary of this function goes here
+%   Detailed explanation goes here
+
+out(1,1:2)={nan,X};
+
+% forward, get z(output) values of all layers.
+
+out = fordwarding(neural_net, out);
+
+%back propagation, modify the weights of the nn.
+
+neural_net = backpropagation(neural_net,cost_function, out, learning_rate, Y);  
+
+% la salida se almacena en la última posición de out.
+
+y_predicted = out{end,2};
+
+end
+