Minimization of two variables
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I cant seem to figure this out on my own. I need to minimize the following function where xi and yi are given data sets (points in 2D),
f(x,y) = minimize{maximize[sqrt((xi-x)^2+(yi-y)^2)]-minimize[sqrt((xi-x)^2+(yi-y)^2)]}
I will need to find x,y.
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infinity
2019 年 6 月 27 日
編集済み: infinity
2019 年 6 月 27 日
Hello,
Here is an example for your problem, which you can refer
clear
xiyi = [0,1;
1,3;
-1 2];
x0 = zeros(size(xiyi));
fun = @(x) max(sqrt((x(:,1)-xiyi(:,1)).^2 + (x(:,2)-xiyi(:,2)).^2))...
- min(sqrt((x(:,1)-xiyi(:,1)).^2 + (x(:,2)-xiyi(:,2)).^2));
xsol = fminsearch(fun,x0)
It is assumed that xi and yi are the first and second column of vector xiyi (in the code).
The solution (x,y) will be stored in xsol.
3 件のコメント
infinity
2019 年 6 月 28 日
Hello,
In the case of searching only one index, for example,
max(sqrt((x(1,1)-xiyi(1,1)).^2 + (x(1,2)-xiyi(1,2)).^2))...
- min(sqrt((x(1,1)-xiyi(1,1)).^2 + (x(1,2)-xiyi(1,2)).^2))
the usage of max and min functions are not necessary since only one value in these functions. I am still unclear with your description of the problem. You may illustrate by picture, which will be more easy.
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