How to solve these problem using cvx?I want to solve this generalized eigenvalue optimization problem, but there are some mistakes

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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
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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.

3

thank you very much, i got it. thank you