Indeed it is one of the first things one learns in numerical lectures that one has to avoid explicitely calculating an inverse matrix. Still, I think that there various small problems in geometry where I don't see an issue of invering a 2x2 or 3x3 matrix. It depends, as so often, a lot on the context. When considering not so well posed problems it is quite essential to take regularization into account. A simple x = A\b would not produce satisfying results in those cases.
Am Donnerstag, 17. Juli 2014 06:25:27 UTC+2 schrieb Stefan Karpinski: > > It's a bit of numerical computing lore that inv is bad – both for > performance and for numerical accuracy. It turns out it may not be so bad > <http://arxiv.org/pdf/1201.6035v1.pdf> after all, but everyone is still > kind of wary of it and there are often better ways to solve problems where > inv would be the naive way to do it. > > On Wed, Jul 16, 2014 at 3:59 PM, Alan Chan <[email protected] > <javascript:>> wrote: > >> any reason of avoiding inv? > > >
