clear, clc
input=[1 2 3]; target=[5 8 4];
n=2; net=feedforwardnet(n);
net=configure(net,input,target);
% 1. EXPLICIT CONFIGURATION IS UNNECCESSARY IF YOU TRAIN THE NET
net.layers{1}.transferFcn = 'purelin';
% 2. NON OUTPUT LAYERS SHOULD HAVE NONLINEAR TRANSFER FUNCTIONS
net.layers{2}.transferFcn = 'purelin'; ukuran1=size(input); ukuran2=size(target); m=ukuran1(1,1); %ini banyak input o=ukuran2(1,1); %ini banyak output kk=((m+1+o)*n)+1; %ini banyak bobot net.iw{1}=[0;0]; net.lw{2}=[0 0]; net.b{1}=[0;0]; net.b{2}=[0];
% 3. INITIAL WEIGHTS SHOULD BE RANDOM. YOU CAN ASSIGN RANDOM VALUES, OR USE CONFIGURE OR JUST TRAIN THE NET WHICH WILL AUTOMATICALLY INITIALIZE WEIGHTS.
y=net(input)
% THE NET HAS NO WEIGHTS! YOU NEED TO TRAIN THE NET.
SEE MY ANSWER
GREG
