cyfra3 = [1 1 1 1 1 0 0 0 0 1 0 0 0 0 1 1 1 1 1 1 0 0 0 0 1 0 0 0 0 1 1 1 1 1 1 ];
cyfra2 = [1 1 1 1 1 0 0 0 0 1 0 0 0 0 1 1 1 1 1 1 1 0 0 0 0 1 0 0 0 0 1 1 1 1 1];
cyfra1 = [0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1];
cyfra0 = [1 1 1 1 1 1 0 0 0 1 1 0 0 0 1 1 0 0 0 1 1 0 0 0 1 1 0 0 0 1 1 1 1 1 1];
cyfra4 = [1 0 0 0 1 1 0 0 0 1 1 0 0 0 1 1 1 1 1 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1];
cyfra5 = [1 1 1 1 1 1 0 0 0 0 1 0 0 0 0 1 1 1 1 1 0 0 0 0 1 0 0 0 0 1 1 1 1 1 1];
cyfra6 = [1 1 1 1 1 1 0 0 0 0 1 0 0 0 0 1 1 1 1 1 1 0 0 0 1 1 0 0 0 1 1 1 1 1 1];
cyfra7 = [1 1 1 1 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1];
cyfra8 = [1 1 1 1 1 1 0 0 0 1 1 0 0 0 1 1 1 1 1 1 1 0 0 0 1 1 0 0 0 1 1 1 1 1 1];
cyfra9 = [1 1 1 1 1 1 0 0 0 1 1 0 0 0 1 1 1 1 1 1 0 0 0 0 1 0 0 0 0 1 1 1 1 1 1];
cyfratest = [1 1 1 0 1 1 1 1 0 1 1 0 0 0 1 1 1 1 1 1 0 0 0 0 1 1 0 0 0 1 1 0 1 1 1];

for i=0:1:6

        A(i+1, :) = cyfratest(i*5+1:i*5+5);

end
A
x0 = [10 0 0 0 0 0 0 0 0 0];
x1 = [0 10 0 0 0 0 0 0 0 0];
x2 = [0 0 10 0 0 0 0 0 0 0];
x3 = [0 0 0 10 0 0 0 0 0 0];
x4 = [0 0 0 0 10 0 0 0 0 0];
x5 = [0 0 0 0 0 10 0 0 0 0];
x6 = [0 0 0 0 0 0 10 0 0 0];
x7 = [0 0 0 0 0 0 0 10 0 0];
x8 = [0 0 0 0 0 0 0 0 10 0];
x9 = [0 0 0 0 0 0 0 0 0 10];
net = newff([0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1; 0 1], [30 10], {'tansig', 'purelin'}, 'trainlm');

net.trainParam.epochs = 200;
net.trainParam.goal = 0.0001;
net = init(net);
net = train(net, [cyfra0' cyfra1' cyfra2' cyfra3' cyfra4' cyfra5' cyfra6' cyfra7' cyfra8' cyfra9'], [x0' x1' x2' x3' x4' x5' x6' x7' x8' x9']);

Y = sim(net, cyfratest');

max = 0;
maxind = -1;
for i = 1:10
    if Y(i) > max
        max = Y(i);
        maxind = i-1;
    end
end
maxind