Is there a reason not to do SVD, and throw out the singular values that are too small?
On Sun, 2018-12-02 at 09:56 -0700, fujimoto2005 wrote: > This problem is an economic problem. The i-th row of the square > constraint > matrix A with m dimension expresses certain economic constraints. > The elements of the constraint matrix are either 0 or 1. > Suppose the rank of A is r and by changing the row number a_1, ..., > a_r are > linearly independent. > I guess the coefficient cj (1 ≤ j ≤ r) in a_i = c1 * a_1 + ... cr * > a_r for > any m>=i> r is found to be 0, -1, 1 for some economic reasons. > I would like to find such a_1, ..., a_r pairs. > > The following matrix is the constraint matrix which I am dealing > with. > > A=zeros(27,27) > > A(1,10)=1 > A(2,5)=1 > A(3,14)=1 > A(4,23)=1 > A(5,9)=1 > A(6,18)=1 > A(7,27)=1 > A(8,17)=1 > A(9,1)=0,A(9,18)=1 > A(10,2)=1,A(10,3)=1 > A(11,4)=1,A(11,5)=1,A(11,6)=1 > A(12,7)=1,A(12,8)=1,A(12,9)=1 > A(13,10)=1,A(13,11)=1,A(13,12)=1 > A(14,13)=1,A(14,14)=1,A(14,15)=1 > A(15,19)=1,A(15,20)=1,A(15,21)=1 > A(16,22)=1,A(16,23)=1,A(16,24)=1 > A(17,1)=0,A(17,25)=1,A(17,26)=1,A(17,27)=1 > A(18,4)=1,A(18,7)=1 > A(19,2)=1,A(19,5)=1,A(19,8)=1 > A(20,10)=1,A(20,13)=1,A(20,16)=1 > A(21,11)=1,A(21,14)=1,A(21,17)=1 > A(22,19)=1,A(22,22)=1,A(22,25)=1 > A(23,1)=0,A(23,20)=1,A(23,23)=1,A(23,26)=1 > A(24,4)=1,A(24,7)=1 > A(25,2)=1,A(25,5)=1,A(25,8)=1 > A(26,10)=1,A(26,13)=1,A(26,16)=1 > A(27,20)=1,A(27,23)=1,A(27,26)=1 > > Best regards. > > > > -- > Sent from: http://mailinglists.scilab.org/Scilab-users-Mailing-Lists- > Archives-f2602246.html > _______________________________________________ > users mailing list > [email protected] > http://lists.scilab.org/mailman/listinfo/users -- Tim Wescott www.wescottdesign.com Control & Communications systems, circuit & software design. Phone: 503.631.7815 Cell: 503.349.8432 _______________________________________________ users mailing list [email protected] http://lists.scilab.org/mailman/listinfo/users
