Optimization with genetic algorithm
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I have this objective function :
E = @(x,y) norm((d(x)-r(x).*y).^2);
I want to optimize vector 'y' using ga ,
if 'd' and 'r' is complex function and 'y' is complex coefficient
I tried with many methods in matlab for find objectiv function appropriate with genetic algorithm,
can i use the method in this link https://www.mathworks.com/help/optim/ug/fit-model-to-complex-data.html
such as the objective function 'E'.
6 件のコメント
Walter Roberson
2018 年 4 月 28 日
The objective function does need to return a real-valued scalar.
I am trying to understand what the various lengths involved are.
If x is a given scalar (at the time of any given optimization) then that implies that d(x) and r(x) can be computed ahead of time. Let
D = d(x);
R = r(x);
then
E = @(y) norm((D-R.*y).^2);
and we know that D and R and y are complex.
But I am not clear as to whether D and R are (complex) scalars, or if they are vectors, and if y will be a vector or a scalar ?
At the moment I am suspecting that the problem can be solved in other ways.
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