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From: Torsten Hennig <Torsten.Hennig@umsicht.fhg.de>
Newsgroups: comp.soft-sys.matlab
Subject: Re: m non-linear equations and two unkowns
Date: Tue, 23 Mar 2010 03:34:13 EDT
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> Hi Matt, 
> Thanks a lot for your response and your
> considearations about the system. Yes, We can to do
> this aproximation to linear system. In Mathlab How We
> solve this new system.
> 
> Thanks again..
> 
> "Matt J " <mattjacREMOVE@THISieee.spam> wrote in
> message <ho2q4r$2i7$1@fred.mathworks.com>...
> > "Daniel Duarte" <danieldarioduarte@hotmail.com>
> wrote in message <ho2o8s$5mq$1@fred.mathworks.com>...
> > > Nice day for everybody....
> > > 
> > > I'm no expert in MAthLab, I'm working in the
> Software World, specifically in software Project
> estimation field. In our investigation we get an
> equation system like next:
> > > 
> > > 120 = A*342^B
> > > 130 = A*143^B
> > > .
> > > .
> > > .
> > > 145 = A* 214^B
> > > 
> > ===========
> > 
> > If you're just lokoing for an approximation, you
> can log() both sides of these equations, so that they
> become linear
> > 
> > log(120) = C+342*B
> > log(130) = C+143*B
> > etc...
> > 
> > where C=log(A). You can use any linear equation
> solver to solve this. Although, if the data 120, 130,
> etc... are noisy, the log operation may induce a
> sub-optimal transformation of the noise.

Create a matrix A with n rows and 2 colums 
where the rows are given by [1 342], [1 143] etc.
Create an n-vector b given by [log(120) log(130) ...].
Calculate p = A\b.
Then p(1) = C and p(2) = B.

Best wishes
Torsten.