[Scilab-users] a linear equation

[Tim Wescott]

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.
> 
> 
> 
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Tim Wescott
www.wescottdesign.com
Control & Communications systems, circuit & software design.
Phone: 503.631.7815
Cell:  503.349.8432