how to calculate optimal value of a unknown constant of an equation with known data points?

3 vues (au cours des 30 derniers jours)
Hey, I wanted to solve for the optimal value of constant. I have data points of the equation .
please help, how can I do that.
equation is:
y= 1/sqrt(k^2+x^2)

Réponse acceptée

Walter Roberson
Walter Roberson le 11 Sep 2020
k0 = rand() * 10;
bestk = lsqcurvefit( @(k,x)1./sqrt(k.^2+x.^2), k0, x, y);
  7 commentaires
Adam Danz
Adam Danz le 11 Sep 2020
We don't know what to do either without knowing the full error message :)
If you're looking for an optimal k, Walter's approach is probably the one you want to pursue. If you have questions about your results, we need the inputs you're using so we can reproduce the results.
pooja sudha
pooja sudha le 11 Sep 2020
Hey Thanks Adam and Walter , I found the result :)

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Plus de réponses (1)

Adam Danz
Adam Danz le 10 Sep 2020
k = sqrt((1/y)^2 - x^2)
  3 commentaires
Adam Danz
Adam Danz le 11 Sep 2020
% assign demo values
k = 2.2; % = 2.2
x = 1:10; % = [1,2,3,4,5,6,7,8,9,10]
y = 1./sqrt(k^2 + x.^2); % = [0.41 0.33 0.26 0.21 0.18 0.15 0.13 0.12 0.10 0.09]
% Solve for k
k = sqrt((1./y).^2 - x.^2) % = [2.2 2.2 2.2 2.2 2.2 2.2 2.2 2.2 2.2 2.2 ]
k = sqrt((1/y(1))^2 - x(1)^2) % = 2.2
Or, as Walter shows, you can use mean(), mode(), median().

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