I need M since a*b*c return the original matrix and I want the approximation.
Yoel
On Jan 15, 2008 7:00 PM, Devon McCormick <[EMAIL PROTECTED]> wrote:
> Given that the shapes returned by the SVD are already conformable for matrix
> multiplication, do you really need to get "M" involved at all?
>
> You can just multiply the result "s" simply like this:
>
> >mp&.>/s
>
> Be aware that this multiplies in the order "a mp (b mp c)" where 'a b c'=.
> s.
>
> On 1/15/08, Yoel Jacobsen <[EMAIL PROTECTED]> wrote:
> >
>
> > Hello,
> >
> > I want to implement matrix approximation using SVD.
> > The SVD algorithm returns three boxed matrices of the shapes x x ; x y ;
> > y y
> > I want to chop and multiply back:
> > Step 1: reshape as - x M; M M ; M y where M is a small value
> > Step 2: Unbox and multiply (x M * M M * M y => x y)
> >
> > My current implementation is:
> >
> > s =. dgesvd ...
> > a =. M {. "1 (> 0 { s)
> > b =. M {. "1 (M {. (> 1 { s))
> > c =. M {. (> 2 { s)
> >
> > mp =: +/ . *
> > approximated =. a mp b mp c
> >
> > Now this is 1) ugly (for me) and 2) slow as hell.
> >
> > Suggestions?
> >
> > Thanks,
> > Yoel
> > ----------------------------------------------------------------------
> > For information about J forums see http://www.jsoftware.com/forums.htm
> >
>
>
>
> --
> Devon McCormick, CFA
> ^me^ at acm.
> org is my
> preferred e-mail
> ----------------------------------------------------------------------
>
> For information about J forums see http://www.jsoftware.com/forums.htm
>
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