Singular Value Decomposition
Dear all?
I'd like to have some deeper / practical information on SVD function.
From theoretical lectures it seems to me that Singular Value Decomposition could me a useful tool to tackle ill-conditioned matrix in eigenvectors search for homogeneous linear system.
It appears also that SVD can solve a variety of problems; that does not help that much me as explanations are often at a too "high level".....
The material in MathCAD help is, sorry to say, in the same league: too abstract...I had also a look to the only one post on similar subject, and again sorry not so easy to be adapted to my problem (not so specialized by the way...)
Could you:
1) confirm me that what I've understood from theoretic is reasonably correct
2) give a more workable example: for example the search for eigenvectors (linked to eigenvalues) for a linear system 4 equations in 4 unknowns (using the MathCAD SVD algorithm)? The best would be that the square matrix linked with the said system is ill-conditioned.....
Thank you very much in advance

