x[n]=d^[n]=e[n]+s^[n]*y[n]
y[n]=w[n]*x[n]
x'[n]=s^[n]*x[n]
w[n+1]=w[n]+u.e[n].x'[n]
e[n]=d[n]-y'[n]

%%%%%%%%%% Initalize Wz %%%%%%%%%%
    Wz = zeros(M,1);          % adaptive filter weigths; coloumn array

    %%%%%%%%%% Initalize step size mu %%%%%%%%%%
    % Initialize "mu"

    %%%%%%%%%% Initialize input %%%%%%%%%%
    % Initialize input "x[n]" of length"N"

    %%%%%%%%%% Generate desired response %%%%%%%%%%
    % Generate the desired response d[n]

    %%%%%%%%%% Generate x'[n] %%%%%%%%%%
    x_prime = conv(Szh,x);           % x'[n] = x[n]*s^[n]

    % Make sure that x and d are coloumn arrays
    x = x(:);
    d = d(:);

    %%%%%%%%%% FBFXLMS algorithm %%%%%%%%%%
    for n=M:N
        x_reverse = x(n:-1:n-M+1);        % input in reverse order
        x_prime_reverse = x_prime(n:-1:n-M+1);      % x'[n] in reverse order
        y = Wz'*x_reverse;                % y[n] = w[n]*x[n];
        y_prime = conv(Sz,y);             % y'[n] = y[n]*s[n]
        e(n) = d(n)-y_prime(n);           % update error: e[n]=d[n]-y'[n]
        Wz = Wz+mu*x_prime_reverse*(e(n));         % update weigths
    end

    %%%%%%%%%% generate y''[n] %%%%%%%%%%
    y_second = conv(Szh,y);      % y'[n] = y[n]*s[n]

    %%%%%%%%%% generate x[n] %%%%%%%%%%
    x = e + y_second;            % x[n] = d^[n] = e[n]+y''[n]