[SciPy-user] Solve for symmetric matrix?
Thu Apr 26 10:45:46 CDT 2007
On 26/04/07, Anand Patil <firstname.lastname@example.org> wrote:
> If the matrix has a zero eigenvalue, it has a nullspace so it's singular so you can't really invert it. However, if you know in advance that the RHS vector is orthogonal to the nullspace you can solve for the remaining components using a low-rank submatrix.
Let me reiterate my support for the SVD. It allows you to find a
least-squares solution for matrices with nullspaces, real or
numerical, even if the result vector is not in the span of the matrix.
It also lets you check how far your answer is from being a real
solution, in both spaces.
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