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 Kommentare
Walter Roberson
am 27 Apr. 2018
Is x constant for this purpose? Is x a complex scalar or a complex vector? Is y a complex scalar or a complex vector? Are you trying to find an (x,y) pair that leads to minimal E?
Johan Johan
am 27 Apr. 2018
Walter Roberson
am 27 Apr. 2018
At any one invocation, is x a scalar or a vector? Is a particular value for x input, or does the x have to be found? Could you confirm that d(x) and r(x) return complex vectors that are the same length as the y being searched for? And could you confirm that you are searching for a vector y, not a scalar y?
Johan Johan
am 27 Apr. 2018
Walter Roberson
am 28 Apr. 2018
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.
Johan Johan
am 28 Apr. 2018
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