X=[1,0.5,-1,-0.5;1,-1,1,0.5];
T=[-1,1,-1,1];
net2=feedforwardnet([5,3]);
net2=train(net2,X,T);

P1=net2.IW{1}*X(:,1)+net2.b{1};  %Prestate of first hidden layer
S1=tansig(P1);                   %State of the first hidden layer
P2=net2.LW{2,1}*S1+net2.b{2};    %Prestate of the second hidden layer
S2=tansig(P2);                   %State of the second hidden layer
P3=purelin(net2.LW{3,2}*S2+net2.b{3});    %Output of the network