Talk:Beginning with CVX
From Wikimization
lamda_W=eig(full(W))
Thanks for the idea
full(W)it's great, it works!!! Thank you very much :D.
I have an answer, how to calculate the normalized eigenvector.
Maybe?v_W=eig(full(W))/max(eig(full(W)))
And... how does i have to undersand the result?
In the tutorial don't explain anything, or, with type K in Matlab(is the variable I want to know) thats all?
Thanks a lot again.
Here is the new code:
clear all; n=2; m=1; A_a=3*eye(2*n,2*n) B_a=4*eye(2*n,2*m) W=eye(4) R=(zeros(2,4)) cvx_begin expression K(2*m,2*n) H=W*A_a'+A_a*W-B_a*R-R'*B_a' variables p1 p2 Epsilon1 Epsilon2 W(4,4) R(2,4) minimize (p1+p2) subject to for p=1:2 W(1,1)<=p1 W(2,2)<=p1 W(3,3)==W(1,1) W(4,4)==W(2,2) for q=1 R(1,1)>=-p2 R(1,1)<=p2 R(2,3)==R(1,1) R(1,2)>=-p2 R(1,2)<=p2 R(2,4)==R(1,2) end end W>=Epsilon1*eye(2*n,2*n) H<=-Epsilon2*eye(2*n,2*n) cvx_end lamda_W=eig(full(W)) lamda_H=eig(H) v_W=eig(full(W))/max(eig(full(W)))%%normalized eigenvector :| v_H=eig(H)/max(eig(H)) para=0 %STOP while para==0 if ( Epsilon1 - lamda_W )>(lamda_H+Epsilon2) cvx_begin H=W*A_a'+A_a*W-B_a*R-R'*B_a' variables p1 p2 Epsilon1 Epsilon2 W(4,4) R(2,4) minimize (p1+p2) subject to for p=1:2 W(1,1)<=p1 W(2,2)<=p1 W(3,3)==W(1,1) W(4,4)==W(2,2) for q=1 R(1,1)>=-p2 R(1,1)<=p2 R(2,3)==R(1,1) R(1,2)>=-p2 R(1,2)<=p2 R(2,4)==R(1,2) end end W>=Epsilon1*eye(2*n,2*n) H<=-Epsilon2*eye(2*n,2*n) v_W'*W*v_w>=Epsilon1 cvx_end else cvx_begin H=W*A_a'+A_a*W-B_a*R-R'*B_a' variables p1 p2 Epsilon1 Epsilon2 W(4,4) R(2,4) minimize (p1+p2) subject to for p=1:2 W(1,1)<=p1 W(2,2)<=p1 W(3,3)==W(1,1) W(4,4)==W(2,2) for q=1 R(1,1)>=-p2 R(1,1)<=p2 R(2,3)==R(1,1) R(1,2)>=-p2 R(1,2)<=p2 R(2,4)==R(1,2) end end W>=Epsilon1*eye(2*n,2*n) H<=-Epsilon2*eye(2*n,2*n) v_H'*W*v_H<=-Epsilon2 cvx_end end lamda_W=eig(full(W)) lamda_H=eig(H) v_W=eig(full(W))/min(eig(full(W)))%%Cálculo del normalized eigenvector v_H=eig(H)/min(eig(H)) %STOP if(lamda_W>=Epsilon1) if(lamda_H<=-Epsilon2) para=1 else para = 0 end else para =0 end end R W K=R/W