indent preformatted text by 4 spaces
Nt = 10;
Ne = 4;
sigma = 1;
H = rand(Nt,Ne);
Pmax = 1;
cvx_begin sdp
variable F1(Nt,Nt) hermitian semidefinite
variable F2(Nt,Nt) hermitian semidefinite
minimize (lambda_max((H'*F2*H+sigma^2*eye(Ne))\(H'*F1*H)))
subject to
real(trace(F1) + trace(F2))<=Pmax
cvx_end
How to solve these problem using cvx?I want to solve this generalized eigenvalue optimization problem, but there are some mistakes
You can’t use this formulation in CVX.
To model generalized eigenvalue problems, read Linear Matrix Inequalities in System and Control Theory - Stephen Boyd, Laurent El Ghaoui, Eric Feron, and Venkataramanan Balakrishnan. Then form a DCP based on the approaches there.
And please don’t keep starting multiple threads with the same topic, which makes clean up work for me.

