function [moyennes, variances, poids] = estimation_non_super(I, nb_classes, nb_tirages)

    [fx, x] = ksdensity(I(:), 1:255);

    MU = rand(nb_classes, nb_tirages) * 255;
    SIGMA = rand(nb_classes, nb_tirages) * 15 + 10;
    
    POIDS = zeros(nb_classes, nb_tirages);
    R = zeros(nb_tirages, 1);

    for i=1:nb_tirages
        A = (1 ./ (SIGMA(:, i).*sqrt(2*pi))) .* exp( -(x-MU(:, i)).^2 ./ (2*SIGMA(:, i).^2) );
        POIDS(:, i) = A' \ fx';
        R(i) = sum( ( fx - sum( POIDS(:, i) .* A  ) ).^2 );
    end

    [~, index] = min(R);
    moyennes = MU(:, index);
    variances = SIGMA(:, index).^2;
    poids = POIDS(:, index);

end