input_len = length(input);
shuffled_array = randperm(input_len);
input = input(shuffled_array,:);
output = output(shuffled_array,:);
%disp(output);
net = feedforwardnet([3 2]);
%net = feedforwardnet([4 3]);
net.layers{3}.transferFcn = 'logsig';

% podesavanje parametara za treniranje
net.divideParam.trainRatio = 0.8; % training set [%]
net.divideParam.valRatio = 0; % validation set [%]
net.divideParam.testRatio = 0.2; % test s
% neural network training
[net,tr,Y,E] = train(net,input',output');
netoutput = sim(net, input');