Dictor recognize based on LVQ trained by autocorrelation.

% инициализируемся: вычисляем T, загружаем АКФы
count = [1:3]; P = []; T = [];
for i=count
    for n={'parx', 'pash', 'sir'}
        l = load(strcat(strcat(n{:}, i+48), '.mat'));
        P = [P transpose(l.Pol_akf)];
        T = [T i];
    end
end
T = full(ind2vec(T));

% формируем нейронную сеть
net = newlvq(minmax(P), 3, [.34 .33 .33], 0.1);

% тренируем
net.trainParam.epochs = 500;
net.trainParam.show = 100;
net.trainParam.lr = 0.05;
net = train(net, P, T);

% смотрим результат
Y = sim(net, P(1:size(P, 1), 1));
Yc = vec2ind(Y);
disp(Yc);