Hello,
I am trying to solve a problem that appears in the next reference: http://www.gtti.it/GTTI09/files/papers/Telerilevamento/Telerilevamento_12.30_Colone.pdf the problem is represented by equation number 9 (sorry I can not upload images due to my “karma level”). I tried to implement it with the next Matlab code (partial implementation):
sec_Barker = [1 -1 1 1 -1 1 1 1 -1 -1 -1];
xb=xcorr(sec_Barker);
M=12;
cvx_begin
variable alfa(2*M+1)
maximize(sum(xb.*alfa(M-10+1:M+10+1)))
subject to
(abs(sum(z.*flipdim(alfa(M-10+1+1:M+10+1+1),2))))<=1;
%more restrictions would be here
cvx_end
The problem comes from the maximize statement when I try “alfa(M-10+1:M+10+1)”, I get the next error ??? Error using ==> cvx.times at 46 Matrix dimensions must agree.
I am not an expert on optimization, so anyone has an idea that can solve it?
Thanks in advance to everybody.
Regards.