how to calculate optimal value of a unknown constant of an equation with known data points?
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pooja sudha
am 10 Sep. 2020
Kommentiert: pooja sudha
am 11 Sep. 2020
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)
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Walter Roberson
am 11 Sep. 2020
k0 = rand() * 10;
bestk = lsqcurvefit( @(k,x)1./sqrt(k.^2+x.^2), k0, x, y);
7 Kommentare
Adam Danz
am 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.
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Adam Danz
am 10 Sep. 2020
k = sqrt((1/y)^2 - x^2)
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Adam Danz
am 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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