cvx目标函数内的总和

时间:2019-06-03 12:44:34

标签: optimization iteration convex-optimization cvx

我具有以下目标函数:

enter image description here

我不确定如何在cvx中编写它。

这是我的尝试:

cvx_begin sdp
variable Q(T,n,N)
%variable X_0T*Q(:,:,N) symmetric
obj = trace(X_0T*Q(:,:,N));
for j = 1:N-1
    obj= obj + trace(X_0T*Q(:,:,j)))
    subject to
     [X_0T*Q(:,:,j+1)-eye(n), X_1T*Q(:,:,j); Q(:,:,j)'*X_1T', X_0T*Q(:,:,j)] >= 0;
      X_0T*Q(:,:,1) >= eye(n);

end
minimize(obj)
cvx_end

K_cvx_df = -U_01T*Q(:,:,N)*pinv(X_0T*Q(:,:,N))

但是,当我尝试求解N到无穷大时,它为我提供了与无限时域情况不同的解决方案,

 cvx_begin sdp
variable Q(T,n)
minimize( trace(X_0T*Q))
subject to
    [X_0T*Q-eye(n), X_1T*Q; Q'*X_1T', X_0T*Q] >= 0
 cvx_end
 K_cvx_d = -U_01T*Q*inv(X_0T*Q)

0 个答案:

没有答案