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

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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?

Accepted Answer

Ben McMahon
Ben McMahon on 12 Jul 2021
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);

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