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From: Torsten Hennig <Torsten.Hennig@umsicht.fhg.de>
Newsgroups: comp.soft-sys.matlab
Subject: Re: solve command
Date: Wed, 25 Mar 2009 05:37:52 EDT
Organization: The Math Forum
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> Torsten Hennig <Torsten.Hennig@umsicht.fhg.de> wrote
> in message
> <30971896.1237971730030.JavaMail.jakarta@nitrogen.math
> forum.org>...
> > > "Roger Stafford"
> > > <ellieandrogerxyzzy@mindspring.com.invalid> wrote
> in
> > > message <gqb5f0$cuc$1@fred.mathworks.com>...
> > >  
> > > >   I am not sure what your problem is, Shane.
> > > Matrix multiplication obeys the associative law,
> so
> > > o A*(R*x) is equal to (A*R)*x.  Why not just do
> this:
> > > > 
> > > >  x = (A*R)\b;
> > > > 
> > > > It is a standard problem of n linear equations
> in n
> > > unknowns.  If A*R is non-singular it has a unique
> > > solution.
> > > > 
> > > > Roger Stafford
> > > 
> > > my problem is, that i cant build up the inverse
> > > matrix of R and therefor i need a solve command.
> > 
> > x = (A*R)\b  _is_ the command to solve the equation
> > A*(R*x) - b = 0 for x.
> > 
> > Of course, you could also solve in two steps for x:
> > y = A\b
> > x = R\y.
> > 
> > Best wishes
> > Torsten.
> 
> 
> I hav tried this sloution method, but the problem is
> tht the condition of A-matrix is very bad and the
> det(R)=0. So this solution causes to no results.

If an exact solution of the equation A*(R*x) - b = 0
exists, x = (A*R)\b will produce it.
Otherwise, x will be an "approximate" solution, i.e.
a vector which minimizes the "error"  A*(R*x) - b in the Euclidean norm.

Best wishes
Torsten.