How to apply adaptive algorithm using k=block.CurrentTime in the s-function level2?

Here is my s-function level2 algorithm for EKF

function Update(block)

Q = block.DialogPrm(2).Data;   ??? this Q will be adapt later if k>M
R = block.DialogPrm(3).Data;

D =  block.InputPort(2).Data;
W =  block.InputPort(3).Data;
meas = block.InputPort(1).Data;

xhat = block.Dwork(1).Data;
P=reshape(block.Dwork(2).Data,4,4);

k=block.CurrentTime;  ??????

%%1. Find the Jacobian

      .....

%%2. Propagate the covariance matrix: (Time update)

      P = A*P*A' + Q;    ####to apply adaptive method for Q

%%3. Propagate the estimate:(Time update)

      xhat(1) = ...
      xhat(2) = ...
      xhat(3) = ...
      xhat(4) = ...
      xhat-=[xhat(1);xhat(2);xhat(3);xhat(4)];

%%4 a). Compute observation estimates:(Measurement Update)

H = [1 0 0 0;0 1 0 0;0 0 1 0];
yhat =   H*xhat;

%%4 c).  Compute residual (Measurement Update)

residual = meas - yhat;

%%5. Compute Kalman Gain:(Measurement Update)

K = P*H'/(H*P*H'+ R);

%%6. Update estimate (Measurement Update)

xhat = xhat- + K*residual;

%%7. Update Covariance Matrix (Measurement Update)

P = (eye(4)-K*H)*P*(eye(4)-K*H)' + K*R*K'; 

block.Dwork(1).Data = xhat;
block.Dwork(2).Data = P(:);

---------------------------------------------------- Supposed i want to apply adaptive method for Q where at time k, the algorithm is defined as below:

ep(:,k)=meas(:,k)-H*xhat(:,k);
eta(:,k)=meas(:,k)-H*xhat-(:,k);
w(:,k)=K*(meas(:,k) - yhat);
Is(:,2*k)=ep(:,k);
Is(:,2*k-1)=eta(:,k);

if k>M     
    for i=1:4
        DVQ=sum(w(i,k-M:k).^2)/(M);
    end
    Q=diag(DVQ)
end

------------------------------------------------- My question. how do i integrate the adaptive algorithm defined above into my s-function level2 (update)? in the s-function i have defined k=block.CurrentTime. Any advise? Thank you.