Re: Octave/C++ matrix Inv() comparison

[CdeMills]

Hello,

before starting to invest your time into comparing algorithms and toolboxes
... first look at your data. Perform a singular value decomposition, look at
the ratio of the biggest singular value (top left of the S matrix) to the
smallest one (bottom right). A ratio greater than 1/sqrt(eps), around 1e8,
is calling for rounding issues. If this is the case, try understanding why
this ratio is so low: it is the symptom that some of your columns are
strongly linearly correlated. Common cures: compute pseudo-inverse (pinv),
i.e. neglecting "directions" where noise sensitivity is great; or
minimal-norm solutions.

Regards

Pascal 



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