Is there a way to compute average norm after a series of trials?

Suppose I have a matrix and I am solving a least-square problem using QR using my own algorithm.

A and b are both generated randomly.

Is there a way to run this least square algorithm several time and at each run the norm is computed and finally the average of all these norms is taken?

Answer 1

[Ben McMahon]

I am a bit confused by your question, as x is not defined. If you want to run your algorithim for a set number of randomly generated matrices and vectors then something similar to the code below should work:

numIterations = 10; % Number of random samples of your matrix / vector combo you want to compute

for Iteration = 1:numIterations   
    A = rand(100,100);
    b = rand(100,1);
   
    x = myLeastSquareAlgo(A,b); % Your algorithim function that calculates 'x'. 
    
    normArray(Iteration) = norm(b-A*x);
end 

meanNorm = mean(normArray);

[Tarek Hajj Shehadi]

Exactly what I am looking for thank you very much.