Left unsaid in this comment is the fact that matrix inversion of any
sizable matrix is almost always a mistake because it is (a) inaccurate, (b)
In scalable numerics it is also commonly true that the only really scalable
problems are sparse. The reason for that is that systems whose cost grows
with O(n^2) cannot be scaled to arbitrary size n. Sparse systems with only
k items on average per row can often be handled with o(n) complexity which
a requirement for a practical system.
On Thu, Jan 17, 2013 at 8:49 PM, Koobas <[EMAIL PROTECTED]> wrote: