fminsearch for multi-input and single output
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I have unknown function with two inputs ('x1' and 'x2') and one output ('Y') and a constant parameter 'p'. Each input is a vector of order [3000 x 3] and a output vector with order [3000 x 3]. Constant is [1 x 1]
best guess of unknown function is Y = (1-p)* 0.003* x1 + 275*p* x2.^4
i want to find a optimum value of parameter 'p' for which the error between the (Ymes - ) is minimum.
Ymes , X1 and X2 are known.
i tried fminsearch but it is not working
Ymes = rand(3000,3);
x1= rand(3000,3);
x2 = rand(3000,3);
fun = @(p) sum((Ymes - (1-p)*0.003* x1 + 275*p*x2.^4)).^2;
pguess = 1500;
[p,fminres] = fminsearch(fun,pguess)
0 Kommentare
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Torsten
am 28 Feb. 2018
Bearbeitet: Torsten
am 28 Feb. 2018
Ymes = rand(3000,3);
x1= rand(3000,3);
x2 = rand(3000,3);
Ymes = Ymes();
x1 = x1();
x2 = x2();
fun = @(p) sum((Ymes - ((1-p)*0.003* x1 + 275*p*x2.^4)).^2);
%starting guess
pguess = [0.15];
%optimise
[p,fminres] = fminsearch(fun,pguess)
or simply:
Ymes = rand(3000,3);
x1= rand(3000,3);
x2 = rand(3000,3);
Ymes = Ymes();
x1 = x1();
x2 = x2();
p = (-0.003*x1+275*x2.^4)\(Ymes-0.003*x1)
7 Kommentare
Torsten
am 1 Mär. 2018
My guess was that you want to fit
Ymes(i,j)
against
(1-p)*0.003* x1(i,j) + 275*p*x2(i,j).^4
for 1<=i<=3000 and 1<=j<=3.
This is what the code I suggested does.
If you want to do something else, you will have to clarify.
Best wishes
Torsten.
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